METHODS FOR DIAGNOSING A COLORECTAL CANCER (CRC) HEALTH STATE OR CHANGE IN CRC HEALTH STATE, OR FOR DIAGNOSING RISK OF DEVELOPING CRC OR THE PRESENCE OF CRC IN A SUBJECT

Abstract

The present invention relates to the diagnosis of colorectal and ovarian cancers (CRC and OC, respectively). The present invention describes the relationship between endogenous small molecules and CRC or OC. Specifically, the present invention relates to the diagnosis of CRC and OC through the measurement of vitamin E isoforms and related metabolites. The present invention also relates to diagnostic markers identified in said method. The present invention relates to the underlying case and pre-symptomatic phases of CRC, the diagnosis of various stages and severity of CRC, the early detection of CRC, monitoring and diagnosing the effect of therapy on CRC and OC health states.

Claims

1. (canceled)

2. An analytical method for diagnosing a patient's colorectal cancer (CRC) health state, or change in CRC health state, or for diagnosing risk of CRC or the presence of CRC in a patient, comprising the steps of: a) performing a mass spectrometry assay on at least one blood sample from said patient using a Fourier transform ion cyclotron resonance, time of flight, magnetic sector, quadrupole or triple quadrupole mass spectrometer to obtain a collision induced dissociation (CID) MS/MS fragmentation pattern for one or more than one metabolite marker and to obtain quantifying data for said one or more than one metabolite marker; b) generating a result of said mass spectrometry assay, said result comprising at least the presence or absence of a decrease in the level of said one or more than one metabolite marker in said blood sample based on a comparison of said quantifying data for said one or more than one metabolite marker to corresponding data obtained for one or more than one reference blood sample; and c) assigning the patient as having or not having colorectal cancer (CRC), or having or not having a change in CRC health state, or having or not having a risk of CRC, wherein the one or more than one metabolite marker comprises one or more molecule selected from the molecular formulae consisting of: C2H.sub.50O.sub.4, C2H.sub.50O.sub.5, C.sub.28H.sub.52O.sub.5, C.sub.32H.sub.58O.sub.6, C.sub.36H.sub.64O.sub.6 and C.sub.36H.sub.66O.sub.6, the metabolite having the molecular formula of C.sub.28H.sub.50O.sub.4 being characterized by a CID MS/MS fragmentation pattern using N.sub.2 as collision gas and analyzed under negative ionization comprising the following daughter ions: 449, 405, 431, 417, 413, 399, 387, 371, 281, and 277, the metabolite having the molecular formula of C.sub.28H.sub.50O.sub.5 being characterized by a CID MS/MS fragmentation pattern using N.sub.2 as collision gas and analyzed under negative ionization comprising the following daughter ions: 465, 403, 447, 433, 421, 405, 349, 297, 279, 241, 223, and 185, the metabolite having the molecular formula of C.sub.28H.sub.52O.sub.5 being characterized by a CID MS/MS fragmentation pattern using N.sub.2 as collision gas and analyzed under negative ionization comprising the following daughter ions: 467, 423, 449, 431, 405, 389, 297, 279, 263, 215, 187, 169, and 141, the metabolite having the molecular formula of C.sub.32H.sub.58O.sub.6 being characterized by a CID MS/MS fragmentation pattern using N.sub.2 as collision gas and analyzed under negative ionization comprising the following daughter ions: 537, 519, 501, 493, 491, 475, 459, 315, 297, 285, 281, 239, and 237, the metabolite having the molecular formula of C.sub.36H.sub.64O.sub.6 being characterized by a CID MS/MS fragmentation pattern using N.sub.2 as collision gas and analyzed under negative ionization comprising the following daughter ions: 591, 573, 559, 556, 527, 415, 313, 297, 295, 175, 149, 115, 113, 95, and 59, and the metabolite having the molecular formula of C.sub.36H.sub.66O.sub.6 being characterized by a CID MS/MS fragmentation pattern using N.sub.2 as collision gas and analyzed under negative ionization comprising the following daughter ions: 593, 575, 557, 550, 532, 529, 515, 315, 313, 297, 277, 215, 201, and 171, wherein a decrease in the level of said one or more than one metabolite marker in the blood sample from the patient relative to a reference blood sample indicates that the patient has CRC, a change in CRC, or is at risk of CRC.

3. The method of claim 2, wherein the mass spectrometer is equipped with a chromatographic system.

4. The method of claim 2, wherein the blood sample is a whole blood sample, a subfraction of whole blood, a blood serum sample, or a blood plasma sample.

5. The method of claim 2, wherein a liquid/liquid extraction is performed on the sample whereby non-polar metabolites are dissolved in an organic solvent and polar metabolites are dissolved in an aqueous solvent.

6. The method of claim 5, wherein the extracted samples are analyzed by positive or negative electrospray ionization, positive or negative atmospheric pressure chemical ionization, or combinations thereof.

7. The method of claim 5, wherein the extracted samples are analyzed by MS/MS transition.

8. The method of claim 5, wherein the extracted samples are analyzed by extracted ion current (EIC) chromatography and MS/MS transition.

9. The method of claim 2, wherein said one or more than one reference sample is from one or more CRC-negative humans.

10. The method of claim 2, further comprising performing a mass spectrometry assay on a blood sample from said patient to obtain quantifying data for one or more than one internal standard molecule; and obtaining a ratio for each of the levels of said one or more than one metabolite marker to the level obtained for the one or more than one internal standard molecule; wherein step (b) comprises generating said result based on a comparison of each ratio to one or more corresponding ratios obtained for the one or more than one reference blood sample.

11. The method of claim 7, wherein at least one MS/MS transition is identified for the metabolite having the molecular formula of C.sub.28H.sub.50O.sub.4, said at least one MS/MS transition being selected from the group consisting of 449.4/405.4, 449.4/431.4, 449.4/417.3, 449.4/387.4, 449.4/371.3, 449.4/281.3, 449.4/277.3 and combinations thereof.

12. The method of claim 7, wherein the MS/MS transition for the metabolite having the molecular formula of C.sub.2H.sub.50O.sub.5 is 465.4/403.4.

13. The method of claim 7, wherein at least one MS/MS transition is identified for the metabolite having the molecular formula of C.sub.28H.sub.52O.sub.5, said at least one MS/MS transition being selected from the group consisting of 467.4/423.4, 467.4/449.4, 467.4/481.4, 467.4/405.4, 467.4/389.4, 467.4/297.3, 467.4/279.3, 467.4/263.3, 467.4/215.2, 467.4/187.16, 467.4/169.2, 467.4/141.2 and combinations thereof.

14. The method of claim 7, wherein at least one MS/MS transition is identified for the metabolite having the molecular formula of C.sub.32H.sub.58O.sub.6, said at least one MS/MS transition being selected from the group consisting of 537.5/519.5, 537.5/501.5, 537.5/491.4, 537.5/457.5, 537.5/459.4, 537.5/315.3, 537.5/297.3, 537.5/285.1, 537.5/239.2, 537.5/237.2, 537.5/475.5 and combinations thereof.

15. The method of claim 7, wherein at least one MS/MS transition is identified for the metabolite having the molecular formula of C.sub.36H.sub.64O.sub.6, said at least one MS/MS transition being selected from the group consisting of 591.5/573.5, 591.5/559.5, 591.5/555.5, 591.5/527.4, 591.5/415.4, 591.5/313.3, 591.5/297.3, 591.5/295.3, 591.5/175.1, 591.5/149.1, 591.5/113.0, 591.5/115.0 and combinations thereof.

16. The method of claim 7, wherein at least one MS/MS transition is identified for the metabolite having the molecular formula of C.sub.36H.sub.66O.sub.6, said at least one MS/MS transition being selected from the group consisting of 593.6/575.6, 593.6/557.5, 593.6/549.5, 593.6/531.5, 593.6/529.4, 593.6/515.4, 593.6/315.3, 593.6/313.3, 593.6/297.3, 593.6/277.3, 593.6/215.1, 593.6/201.1, 593.6/171.1 and combinations thereof.

17. The method of claim 10, wherein the internal standard molecule is cholic acid.

18. An analytical method for diagnosing a patient's colorectal cancer (CRC) health state, or change in CRC health state, or for diagnosing risk of CRC or the presence of CRC in a patient, comprising the steps of: a) performing a mass spectrometry assay on at least one blood sample from said patient using a Fourier transform ion cyclotron resonance, time of flight, magnetic sector, quadrupole or triple quadrupole mass spectrometer to obtain a collision induced dissociation (CID) MS/MS fragmentation pattern for one or more than one metabolite marker and to obtain quantifying data for said one or more than one metabolite marker; b) generating a result of said mass spectrometry assay, said result comprising at least the presence or absence of a decrease in the level of said one or more than one metabolite marker in said blood sample based on a comparison of said quantifying data for said one or more than one metabolite marker to corresponding data obtained for one or more than one reference blood sample; and c) assigning the patient as having or not having colorectal cancer (CRC), or having or not having a change in CRC health state, or having or not having a risk of CRC, wherein the one or more than one metabolite marker comprises one or more molecule selected from the molecular formulae consisting of: C.sub.2H.sub.48O.sub.4 and C.sub.28H.sub.48O.sub.5 the metabolite having the molecular formula of C.sub.28H.sub.48O.sub.4 being characterized by a CID MS/MS fragmentation pattern using N.sub.2 as collision gas and analyzed under negative ionization comprising the following daughter ions: 447, 385, 429, 403, and 279, the metabolite having the molecular formula of C.sub.28H.sub.48O.sub.5 being characterized by a CID MS/MS fragmentation pattern using N.sub.2 as collision gas and analyzed under negative ionization comprising the following daughter ions: 463, 419, 445, 401, 383, 315, 297, and 241, wherein a decrease in the level of said one or more than one metabolite marker in the blood sample from the patient relative to a reference blood sample indicates that the patient has CRC, a change in CRC, or is at risk of CRC.

19. The method of claim 18, wherein the extracted samples are analyzed by MS/MS transition.

20. The method of claim 18, wherein at least one MS/MS transition is identified for the metabolite having the molecular formula of C.sub.28H.sub.48O.sub.4, said at least one MS/MS transition being selected from the group consisting of 447.4/385.4, 447.4/429.4, 447.4/403.4, 447.4/279.2 and combinations thereof.

21. The method of claim 18, wherein at least one MS/MS transition is identified for the metabolite having the molecular formula of C.sub.28H.sub.48O.sub.5, said at least one MS/MS transition being selected from the group consisting of 463.4/419.4, 463.4/445.3, 463.4/401.3, 463.4/383.3, 463.4/315.3, 463.4/297.3, 463.4/241.2, 463.4/223.2 and combinations thereof.

22. An analytical method for detecting a colorectal cancer (CRC) disease marker, comprising the steps of: providing at least one blood sample from a patient; and performing a mass spectrometry assay on the at least one blood sample using a Fourier transform ion cyclotron resonance, time of flight, magnetic sector, quadrupole or triple quadrupole mass spectrometer to obtain a collision induced dissociation (CID) MS/MS fragmentation pattern for one or more than one metabolite marker and to obtain quantifying data for said one or more than one metabolite marker; wherein the one or more than one metabolite marker comprises one or more molecule selected from the molecular formulae consisting of: C.sub.28H.sub.50O.sub.4, C.sub.28H.sub.50O.sub.5, C.sub.28H.sub.52O.sub.5, C.sub.32H.sub.58O.sub.6, C.sub.36H.sub.64O.sub.6 and C.sub.36H.sub.66O.sub.6, the metabolite having the molecular formula of C.sub.28H.sub.50O.sub.4 being characterized by a CID MS/MS fragmentation pattern using N.sub.2 as collision gas and analyzed under negative ionization comprising the following daughter ions: 449, 405, 431, 417, 413, 399, 387, 371, 281, and 277, the metabolite having the molecular formula of C.sub.28H.sub.50O.sub.5 being characterized by a CID MS/MS fragmentation pattern using N.sub.2 as collision gas and analyzed under negative ionization comprising the following daughter ions: 465, 403, 447, 433, 421, 405, 349, 297, 279, 241, 223, and 185, the metabolite having the molecular formula of C.sub.28H.sub.52O.sub.5 being characterized by a CID MS/MS fragmentation pattern using N.sub.2 as collision gas and analyzed under negative ionization comprising the following daughter ions: 467, 423, 449, 431, 405, 389, 297, 279, 263, 215, 187, 169, and 141, the metabolite having the molecular formula of C.sub.32H.sub.58O.sub.6 being characterized by a CID MS/MS fragmentation pattern using N.sub.2 as collision gas and analyzed under negative ionization comprising the following daughter ions: 537, 519, 501, 493, 491, 475, 459, 315, 297, 285, 281, 239, and 237, the metabolite having the molecular formula of C.sub.36H.sub.64O.sub.6 being characterized by a CID MS/MS fragmentation pattern using N.sub.2 as collision gas and analyzed under negative ionization comprising the following daughter ions: 591, 573, 559, 556, 527, 415, 313, 297, 295, 175, 149, 115, 113, 95, and 59, and the metabolite having the molecular formula of C.sub.36H.sub.66O.sub.6 being characterized by a CID MS/MS fragmentation pattern using N.sub.2 as collision gas and analyzed under negative ionization comprising the following daughter ions: 593, 575, 557, 550, 532, 529, 515, 315, 313, 297, 277, 215, 201, and 171.

Description

BRIEF DESCRIPTION OF THE DRAWINGS

[0040] These and other features of the invention will become more apparent from the following description in which reference is made to the appended drawings wherein:

[0041] FIG. 1 shows a summary of the steps involved in the identification of the CRC/OC diagnostic biomarker panel in accordance with an embodiment of the present invention

[0042] FIGS. 2A-2B are graphs that show the prediction of microarray analysis (PAM) training error (FIG. 2A) and cross validation misclassification error (FIG. 2B) plots.

[0043] FIG. 3 shows the PAM output cross-validated diagnostic probabilities for all samples based on the classifier created in FIGS. 2A-2B.

[0044] FIG. 4 shows the receiver-operator characteristic curve based on cross-validated probabilities.

[0045] FIG. 5 shows the diagnostic predictions for blinded test samples when half the samples are used for training and the other half are used as a blinded test set.

[0046] FIGS. 6A-6B show the prediction results (FIG. 6A) and receiver-operator characteristic curve (FIG. 6B) based on blinded test set diagnosis.

[0047] FIGS. 7A-7F show the raw FTMS spectra for six of the selected biomarkers (FTMS neutral mass shown; FIGS. 7A to 7F). Top panel for each of FIGS. 7A-7F, 5 normal samples; bottom panel for each of FIGS. 7A-7F, 5 CRC-positive samples.

[0048] FIGS. 8A-8F show the QSTAR extracted ion chromatograms for six of the biomarkers (nominal detected mass indicated; FIGS. 8A to 8F). Top panel for each of FIGS. 8A-8F, 5 normal samples; bottom panel for each of FIGS. 8A-8F, 5 CRC-positive samples.

[0049] FIGS. 9A-9C show the average extracted mass spectra for retention time window; 16-17 minutes for 5 normal (FIG. 9A) and 5 CRC (FIG. 9B) serum samples as detected on the QSTAR and the net difference (FIG. 9C).

[0050] FIGS. 10A-10B show the averaged CRC biomarker intensities of five CRC and five normal samples from FTMS (FIG. 10A) and Q-star (FIG. 10B) analysis. CRC-positive in the first column for each biomarker; normals shown in the second column for each biomarker.

[0051] FIG. 11 shows a graph of 30 metabolites that are part of the vitamin E-like family as detected in the FTMS dataset. These can be broken into groups depending on the numbers of carbons they contain. The intensities of gamma (GT) and alpha tocopherol (AT) are also shown.

[0052] FIG. 12 shows the structures of gamma tocopherol and tocotrienol (Structures A and B, respectively) and six of the C28-containing vitamin-E-like molecules (Structures C to H, respectively) as determined by MSMS and NMR.

[0053] FIG. 13 shows the putative structures of key MS/MS fragments for neutral mass biomarker 448.3726 (C.sub.28H.sub.48O.sub.4).

[0054] FIG. 14 shows the putative structures of key MS/MS fragments for neutral mass biomarker 464.3522 (C.sub.28H.sub.48O.sub.5).

[0055] FIG. 15 shows the putative structures of key MS/MS fragments for neutral mass biomarker 446.3522 (C.sub.28H.sub.46O.sub.4).

[0056] FIG. 16 shows the putative structures of key MS/MS fragments for neutral mass biomarker 466.3661 (C.sub.28H.sub.50O.sub.5).

[0057] FIG. 17 shows putative structures of key MS/MS fragments for neutral mass biomarker 450.3726 (C.sub.28H.sub.50O.sub.4).

[0058] FIG. 18 shows putative structures of key MS/MS fragments for neutral mass biomarker 468.3840 (C.sub.2H.sub.52O.sub.5).

[0059] FIGS. 19A-19B show putative structures of key MS/MS fragments for neutral mass biomarker 538.4259 (C.sub.32H.sub.58O.sub.6).

[0060] FIGS. 20A-20B show putative structures of key MS/MS fragments for neutral mass biomarker 592.4711 (C.sub.36H.sub.64O.sub.6)

[0061] FIGS. 21A-21B show putative structures of key MS/MS fragments for neutral mass biomarker 594.4851 (C.sub.36H.sub.66O.sub.6).

[0062] FIG. 22 shows .sup.1H-NMR spectra of 448.3406 (C28H48O4)

[0063] FIG. 23 shows .sup.1H-NMR analysis of 464.3522 (C28H48O5)

[0064] FIG. 24 shows .sup.1H-NMR analysis of 446.3406 (C28H46O4)

[0065] FIG. 25 shows .sup.1H-NMR analysis of 466.3661 (C28H50O5)

[0066] FIG. 26 shows a summary of the MS/MS high throughput screening method.

[0067] FIGS. 27A-27G show Analyst screenshots of the 6 CRC biomarker transitions and internal standard transitions (FIG. 27A to 27F), and housekeeping transitions (FIG. 27G). Each page shows the peak areas for the transitions of two biomarkers in a typical normal and typical CRC positive individual. For each of FIGS. 27A to 27G, the top four plots are from the normal, the bottom four are from the CRC positive. BM: biomarker, IS: internal standard.

[0068] FIG. 28 shows the normal population distribution based on the final HTS output of 288 disease-free individuals. The 1.3 indicates the cutoff value selected as the point below which a person would be considered high risk for CRC (see FIG. 29).

[0069] FIG. 29 shows the HTS diagnostic output. Cutoff ratios based on the distribution of normal subjects, as shown in FIG. 28, were selected as to achieve a specificity of 90.5%. This means that patient scores between 4 and 1.3 are high risk for CRC, scores between 1.3 and 0.8 are medium risk, and scores greater than 0.8 are low risk. The recommended courses of actions are shown.

[0070] FIGS. 30A-30D show the Gamma-tocopherol/tocotrienol neutralization of lipid peroxidation. The figures show the auto-oxidation of an unsaturated fatty acid (FIG. 30A), the stabilization of peroxyl radical by gamma-tocopherol (FIG. 30B), the reaction with a peroxyl radical by gamma-tocopherol radical (FIG. 30C) and the two semi-stable peroxides formed by gamma-tocopherol (FIG. 30D).

[0071] FIGS. 31A-31C show the internal degradation of gamma-tocopherol peroxide in the presence of iron. FIG. 31A shows the C30 series of tocopherol metabolites that arise from linolenic acid. FIG. 31B shows the C32 series of tocopherol metabolites that arise from linoleic acid. FIG. 31C shows the C36 series of tocopherol metabolites that arise from oleic acid.

[0072] FIG. 32 shows the hydroperoxide degradation in the presence of iron.

[0073] FIGS. 33A-33B show the spontaneous break down of free radicals. FIG. 33 A shows the short-chain alkane radical and long-chain aldehyde which results from breakdown at the bond indicated by the dotted line A, and FIG. 33B shows the short-chain aldehyde and long-chain alkane radical that would result from spontaneous breakdown at bond B (dotted line B).

[0074] FIGS. 34A-34B show that gamma-tocopherol can neutralize the free alkane radical. The unhindered aromatic ring structure of gamma-tocopherol/tocotrienol can accept a hydrogen radical from the radical alkane, resulting in a ring-stabilized tocopherol/tocotrienol radical and a stable alkene (FIG. 34A). This hydrogen radical acceptance reaction can occur four times, reducing the ring structure to a single double bond (FIG. 34B).

[0075] FIG. 35 shows the omega carboxylation resulting from liver P450 metabolism.

[0076] FIGS. 36A-36B show a hypothesis for the role of vitamin E and related metabolites in a normal state (FIG. 36A) and in CRC and OC (FIG. 36B).

DETAILED DESCRIPTION OF THE INVENTION

[0077] The present invention relates to the diagnosis of colorectal and ovarian cancers (CRC and OC, respectively). The present invention describes the relationship between endogenous small molecules and CRC or OC. Specifically, the present invention relates to the diagnosis of CRC and OC through the measurement of vitamin E isoforms and related metabolites. More specifically, the present invention relates to the relationship between vitamin E-related metabolites in human serum and the implications thereof in CRC and OC.

[0078] The present invention discloses for the first time clear and unambiguous biochemical changes specifically associated with CRC. These findings also imply that the measurement of these biomarkers may provide a universal means of measuring the effectiveness of CRC therapies. This would dramatically decrease the cost of performing clinical trials as a simple biochemical test can be used to assess the viability of new therapeutics. Furthermore, one would not have to wait until the tumor progresses or until the patient dies to determine whether the therapy provided any benefit. The use of such a test would enable researchers to determine in months, rather than years, the effectiveness of dose, formulation, and chemical structure modifications of CRC therapies.

[0079] The present invention relates to a method of diagnosing CRC or OC by measuring the levels of specific small molecules present in human serum and comparing them to normal reference levels. In one embodiment of the present application there is described a novel method for the early detection and diagnosis of CRC or OC and the monitoring the effects of treatment on CRC and OC.

[0080] The preferred method involves the use of a high-throughput screening (HTS) assay developed from a subset of metabolites selected from Table 3 for the diagnosis of one or more diseases or particular health-states. The utility of the claimed method is demonstrated and validated through the development of a HTS assay capable of diagnosing a CRC-positive health-state.

[0081] The impact of such an assay on CRC and OC would be tremendous, as literally everyone could be screened longitudinally throughout their lifetime to assess risk and detect these diseases early. Given that the performance characteristics of the test are representative for the general CRC population, this test alone may be superior to any other currently available CRC screening method, as it may have the potential to detect disease progression prior to that detectable by conventional methods. The early detection of disease is critical to positive treatment outcome.

[0082] In order to determine whether there are biochemical markers of a given health-state in a particular population, a group of patients representative of the health state (i.e. a particular disease) and a group of normal counterparts are required. Biological samples taken from the patients in a particular health-state category can then be compared to the same samples taken from the normal population to identify differences between the two groups, by extracting the samples and analyzing using various analytical platforms including, but not limited to, Fourier transform ion cyclotron resonance mass spectrometry (FTMS) and liquid chromatography mass spectrometry (LC-MS). The biological samples could originate from anywhere within the body, including, but not limited to, blood (serum/plasma), cerebrospinal fluid (CSF), urine, stool, breath, saliva, or biopsy of any solid tissue including tumor, adjacent normal, smooth and skeletal muscle, adipose tissue, liver, skin, hair, kidney, pancreas, lung, colon, stomach, or other.

[0083] For the invention of the CRC diagnostic assay described, serum samples were obtained from representative populations of healthy CRC- and OC-negative individuals, and of professionally diagnosed CRC-positive patients. Throughout this application, the term serum will be used, but it will be obvious to those skilled in the art that plasma, whole blood, or a subfraction of whole blood may be used in the method.

[0084] When a blood sample is drawn from a patient there are several ways in which the sample can be processed. The range of processing can be as little as none (i.e. frozen whole blood) or as complex as the isolation of a particular cell type. The most common and routine procedures involve the preparation of either serum or plasma from whole blood. All blood sample processing methods, including spotting of blood samples onto solid-phase supports, such as filter paper or other immobile materials, are also contemplated by the invention.

[0085] The processed blood sample described above is then further processed to make it compatible with the analytical analysis technique to be employed in the detection and measurement of the biochemicals contained within the processed blood sample (in our case, a serum sample). The types of processing can range from as little as no further processing to as complex as differential extraction and chemical derivatization. Extraction methods include, but are not limited to, sonication, soxhlet extraction, microwave assisted extraction (MAE), supercritical fluid extraction (SFE), accelerated solvent extraction (ASE), pressurized liquid extraction (PLE), pressurized hot water extraction (PHWE), and/or surfactant-assisted extraction in common solvents such as methanol, ethanol, mixtures of alcohols and water, or organic solvents such as ethyl acetate or hexane. The preferred method of extracting metabolites for FTMS non-targeted analysis is to perform a liquid/liquid extraction whereby non-polar metabolites dissolve in an organic solvent and polar metabolites dissolve in an aqueous solvent. In one embodiment of the present invention, the metabolites contained within the serum samples were separated into polar and non-polar extracts by sonication and vigorous mixing (vortex mixing).

[0086] Extracts of biological samples are amenable to analysis on essentially any mass spectrometry platform, either by direct injection or following chromatographic separation. Typical mass spectrometers are comprised of a source, which ionizes molecules within the sample, and a detector for detecting the ionized particles. Examples of common sources include electron impact, electrospray ionization (ESI), atmospheric pressure chemical ionization (APCI), matrix assisted laser desorption ionization (MALDI), surface enhanced laser desorption ionization (SELDI), and derivations thereof. Common ion detectors can include quadrupole-based systems, time-of-flight (TOF), magnetic sector, ion cyclotron, and derivations thereof.

[0087] In accordance with the present invention the small molecules are identified by a method known as non-targeted analysis. Non-targeted analysis involves the measurement of as many molecules in a sample as possible, without any prior knowledge or selection of the components prior to the analysis (see WO 01/57518, published Aug. 9, 2001). Therefore, the potential for non-targeted analysis to discover novel metabolite biomarkers is high versus targeted methods, which detect a predefined list of molecules. The present invention uses a non-targeted method to identify metabolite components that differ between CRC-positive and healthy individuals, followed by the development of a high-throughput targeted assay for a subset of the metabolites identified from the non-targeted analysis. However, it would be obvious to anyone skilled in the art that other metabolite profiling strategies could potentially be used to discover some or all of the differentially regulated metabolites disclosed in this application and that the metabolites described herein, however discovered or measured, represent unique chemical entities that are independent of the analytical technology that may be used to detect and measure them.

[0088] According to this analysis many hundreds of small molecules, metabolites, or metabolite fragments can be identified that have differential abundances between CRC-positive serum and normal serum. The present invention discloses 480 metabolite masses, as listed in Table 3, which were found to have statistically significant differential abundances between CRC-positive serum and normal serum. All of these features, which differ statistically between the two populations have potential diagnostic utility. However, the incorporation of 480 signals into a commercially diagnostic assay is impractical, so well known methods of selecting an optimum diagnostic set of markers or metabolites was conducted.

[0089] From the methods described in this patent, a panel of nine metabolites was chosen as optimal for discriminating CRCs form normals. In the present invention colorectal cancer-specific metabolic markers selected from the group consisting of metabolites with an accurate neutral mass (measured in Daltons) of, or substantially equivalent to, 446.3406, 448.3563, 450.3726, 464.3522, 466.3661, 468.3840, 538.4259, 592.4711, and 594.4851 where a +/5 ppm difference would indicate the same metabolite, were identified. These markers can thus be used in a diagnostic test to screen patients for the presence of CRC.

[0090] Of the nine metabolites described above, six were selected further for implementation into a high-throughput screening (HTS) assay. The HTS assay is based upon conventional triple-quadrupole mass spectrometry technology (See FIG. 26 for summary). The HTS assay works by directly injecting a serum extract into the triple-quad mass spectrometer, which then individually isolates each of the six parent molecules by single-ion monitoring (SIM). This is followed by the fragmentation of each molecule using an inert gas (called a collision gas, collectively referred to collision-induced dissociation or CID). The intensity of a specific fragment from each parent biomarker is then measured and recorded, through a process called multiple-reaction monitoring (MRM). In addition, an internal standard molecule is also added to each sample and subject to fragmentation as well. This internal standard fragment should have the same intensity in each sample if the method and instrumentation is operating correctly. When all six biomarker fragment intensities, as well as the internal standard fragment intensities are collected, a ratio of the biomarker to IS fragment intensities are calculated, and the ratios log-transformed. The lowest value of the six for each patient sample is then compared to a previously determined distribution of disease-positive and controls, to determine the relative likelihood that the person is positive or negative for the disease.

[0091] There are multiple types of cost-effective assay platform options currently available depending on the molecules being detected. These can include colorimetric chemical assays (UV, or other wavelength), antibody-based enzyme-linked immunosorbant assays (ELISAs), chip-based and polymerase-chain reaction for nucleic acid detection assays, bead-based nucleic-acid detection methods, dipstick chemical assays, image analysis such as MRI, petscan, CT scan, and various mass spectrometry-based systems.

[0092] According to this aspect of the invention, there is provided the development of a commercial method for screening patients for CRC using the MS/MS fragmentation patterns identified in the previous section. There are numerous options for the deployment of the assay world-wide. The two most obvious are: 1, the development of MS/MS methods compatible with current laboratory instrumentation and triple-quadrupole mass spectrometers which are readily in place in many labs around the world, and/or 2, the establishment of a testing facility where samples could be shipped and analyzed at one location, and the results sent back to the patient or patient's physician.

[0093] The structural elucidation of the selected metabolites was determined following a series of physical and chemical property investigations. For example the principal characteristics that are normally used for this identification are accurate mass and molecular formula determination, polarity, acid/base properties, NMR spectra, and MS/MS or MSn spectra. With the elucidation of the identity of the metabolites of the present invention it is possible to identify the metabolic pathway or pathways involved in the progression of the disease.

[0094] The molecular formulas of the nine preferred diagnostic markers (446.3406, 448.3563, 450.3726, 464.3522, 466.3661, 468.3840, 538.4259, 592.4711, and 594.4851), were determined to be C28H46O4, C28H48O4, C28H50O4, C28H48O5, C28H50O5, C28H52O5, C32H58O6, C36H64O6, C36H66O6 based on their accurate neutral mass, polarity, and ionization characteristics. These metabolites have been determined, according to the present invention to consist of a semi-saturated chroman ring and phytyl side chain and therefore consistent with a vitamin E-related structure.

[0095] A significant amount of research has been performed on the effects of vitamin E in vitro and on animals models of CRC whereas very little research has been done regarding vitamin E and OC. As early as 1980, Cook and McNamara [12] showed a protective effect of vitamin E on chemically induced colon cancer in mice. However, human studies have failed to provide any compelling evidence that vitamin E plays a significant role in any of the prevention, cause, treatment, or supportive treatment of CRC. Coulter et al showed that out of 38 studies there was no significant effect of alpha-tocopherol treatment for any individual cancer, and that a pooled relative risk alone was 0.91 (95% CI: 0.74 m 1.12)[13].

[0096] The term vitamin E collectively refers to eight naturally occurring isoforms, four tocopherols (alpha, beta, gamma, and delta) and four tocotrienols (alpha, beta, gamma, and delta). The predominant form found in western diets is gamma-tocopherol whereas the predominant form found in human serum/plasma is alpha-tocopherol. Tocotrienols are also present in the diet, but are more concentrated in cereal grains and certain vegetable oils such as palm and rice bran oil. Interestingly, it is suggested that tocotrienols may be more potent than tocopherols in preventing cardiovascular disease and cancer [14]. This may be attributable to the increased distribution of tocotrienols within lipid membranes, a greater ability to interact with radicals, and the ability to be quickly recycled more quickly than tocopherol counterparts [15]. It has been demonstrated that in rat liver microsomes, the efficacy of alpha-tocotrienol to protect against iron-mediated lipid peroxidation was 40 times higher that that of alpha-tocopherol [15]. However, measurements in human plasma indicate that trienols are either not detected or present only in minute concentrations [16], due possibly to the higher lipophilicity resulting in preferential bilary excretion [17].

[0097] A considerable amount of research related to the discrepancy between the distribution of alpha and gamma tocopherol has been performed on these isoforms. It has been known and reported as early as 1974 that gamma- and alpha-tocopherol have similar intestinal absorption but significantly different plasma concentrations [18]. In the Bieri and Evarts study [18], rats were depleted of vitamin E for 10 days and then fed a diet containing an alpha:gamma ratio of 0.5 for 14 days. At day 14, the plasma alpha:gamma ratio was observed to be 5.5! The authors attributed this to a significantly higher turnover of gamma-tocopherol, however, the cause of this increased turnover was unknown. Plasma concentrations of the tocopherols are believed to be tightly regulated by the hepatic tocopherol binding protein. This protein has been shown to preferentially bind to alpha-tocopherol [19]. Large increases in alpha-tocopherol consumption result in only small increases in plasma concentrations [20]. Similar observations hold true for tocotrienols, where high dose supplementation has been shown to result in maximal plasma concentrations of approximately only 1 to 3 micromolar [21]. More recently, Birringer et al [17]showed that although upwards of 50% of ingested gamma-tocopherol is metabolized by human hepatoma HepG2 cells by omega-oxidation to various alcohols and carboxylic acids, less than 3% of alpha-tocopherol is metabolized by this pathway. This system appears to be responsible for the increased turnover of gamma-tocopherol. In this paper, they showed that the creation of the omega COOH from gamma-tocopherol occurred at a rate of >50 than the creation of the analogous omega COOH from alpha-tocopherol. Birringer also showed that the trienols are metabolized via a similar, but more complex omega carboxylation pathway requiring auxiliary enzymes [17].

[0098] It is likely that the existence of these two structurally selective processes has biological significance. Birringer et al [17] propose that the purpose of the gamma-tocopherol-specific P450 omega hydroxylase is the preferential elimination of gamma-tocopherol/trienol as 2,7,8-trimethyl-2-(beta-carboxy-3-carboxyethyl)-6-hydroxychroman (gamma-CEHC). We argue, however, that if the biological purpose is simply to eliminate gamma-tocopherol/trienol, it would be far simpler and more energy efficient via selective hydroxylation and glucuronidation. The net biological effect of these two processes, which has not been commented on in the vitamin E literature, is that the two primary dietary vitamin E isoforms (alpha and gamma), upon entering the liver during first-pass metabolism, are shunted into two separate metabolic systems. System 1 quickly moves the most biologically active antioxidant isoform (alpha-tocopherol) into the blood stream to supply the tissues of the body with adequate levels of this essential vitamin. System 2 quickly converts gamma-tocopherol into the omega COOH. In the present invention it is disclosed that significant concentrations of six isoforms of gamma-tocopherol/tocotrienol omega COOH are present in normal human serum at all times. We were able to estimate that the concentration of each of these molecules in human serum is in the low micromolar range by measuring cholic acid, an organically soluble carboxylic acid-containing internal standard used in the triple-quadrupole method. This is within the previously reported plasma concentration range of 0.5 to 2 micromolar for -tocopherol (approximately 20 times lower than that of alpha-tocopherol) [22] The cumulative total, therefore, of all six novel -tocopheric acids in serum is not trivial, and likely exceeds that of -tocopherol itself. None of the other shorter chain length gamma-tocopherol/trienol metabolites described by Birringer et al [17] were detected in the serum. Also, the alpha and gamma tocotrienols were also not detected in the serum of patients used in the studies reported in this work, suggesting that the primary purpose of the gamma-tocopherol/trineol-specific P450 omega hydroxylase is the formation of the omega COOH and not gamma-CEHC. Not to be bound by the correctness of the theory, it is therefore suggested that the various gamma-tocopherol/tocotrienol omega COOH metabolites disclosed in the present application are novel bioactive agents and that they perform specific and necessary biological functions for the maintenance of normal health and for the prevention of disease.

[0099] Of relevance is also the fact that it has been shown that mammals are able to convert trienols to tocopherols in vivo [23, 24]. Since two of the novel six vitamin E-like metabolites contain a saturated phytyl side chain, and are therefore tocopherol-like, and the other four harbor a semi-saturated phytyl side chain, suggesting a tocotrienol origin. Since mammals cannot introduce the double-bonds, therefore, it is possible that all six molecules originate from a tocotrienol-like precursor.

[0100] Just as trienols have been reported to have biological activities separate from the tocopherols [25], gamma-tocopherol has been reported to have biological functions separate and distinct from alpha-tocopherol. For example, key differences between alpha tocopherol and alpha tocotrienol include the ability of alpha tocotrienol to specifically prevent neurodegeneration by regulating specific mediators of cell death [26], the ability of trienols to lower cholesterol [27], the ability to reduce oxidative protein damage and extend life span of C. elegans [28], and the ability to suppress the growth of breast cancer cells [29, 30]. Key differences between the gamma and alpha forms of tocopherol include the ability of gamma to decrease proinflammatory eicosanoids in inflammation damage in rats [31] and inhibition of cyclooxygenase (COX-2) activity [32]. In Jiang et al [32] it was reported that it took 8-24 hours for gamma-tocopherol to be effective and that arachadonic acid competitively inhibits the suppression activity of gamma-tocopherol. It is hypothesized that the omega COOH metabolites of gamma-tocopherol may be the primary bioactive species responsible for its anti-inflammation activity. The conversion of arachadonic acid into eicosanoids is a critical step in inflammation. It is more conceivable that omega COOH forms of gamma-tocopherol, due to their structural similarities to arachadonic acid, are more potent competitive inhibitors of this formation than native gamma-tocopherol.

[0101] In one aspect of this invention there is provided novel gamma-tocopherol/tocotrienol metabolites in human serum. These gamma-tocopherol/trienol metabolites have had the aromatic ring structure reduced. In this aspect of the invention, the gamma-tocopherol/tocotrienol metabolites comprise OC2H5, OC4H9, or OC8H17 moieties attached to the hydroxychroman structure in human serum.

[0102] Not to be bound to any particular theory, the present invention discloses a hypothesis as to how gamma-tocopherol/tocotrienol can react with alkane radicals to create a stable alkene and a stabilized gamma-tocopherol/tocotrienol radical. It is suggested that, through this mechanism, one molecule of gamma-tocopherol/tocotrienol can neutralize up to six alkane radicals. The present invention further suggests how a gamma-tocopherol/tocotrienol radical can react with a lipid peroxide and subsequently neutralize the lipid peroxide into a stable gamma-tocopherol/tocotrienol alkyl ether and a stable lipid aldehyde. It is also suggested that the presence of iron may catalyze this reaction.

[0103] The uptake and concentration of gamma-tocopherol is dramatically different in colon epithelial cells relative to plasma. Tran and Chan [33] showed that gamma-tocopherol is preferentially taken up by human endothelial cells versus alpha-tocopherol, and Nair et al [34] showed that the in vivo concentration of gamma-tocopherol in human colon epithelial cells is 2-fold higher than alpha-tocopherol. Therefore, tissues that are primarily fed by the blood supply are preferentially enriched with alpha-tocopherol [18] whereas colon epithelial cells, which absorb tocopherols directly from the large intestine have concentrations representative of the dietary ratio of these isoforms [34].

[0104] The present application discloses that alpha-tocopherol/tocotrienol concentrations are significantly decreased in the serum of CRC patients versus controls but not in OC, prostate, renal cell, breast, or lung cancers. It is further disclosed that gamma-tocopherol and gamma-tocopherol/tocotrienol-related metabolite intensities are significantly decreased in the serum of CRC and OC patients versus controls but not in prostate, renal cell, breast, or lung cancers.

[0105] Not wishing to be bound by any particular theory, in the present invention it is hypothesized that the novel metabolites disclosed herein are indicators of vitamin E activity and that the decrease of such metabolites is indicative of one of the following situations: [0106] 1. A hyper-oxidative or metabolic state that is consuming vitamin E and related metabolites at a rate in excess of that being supplied by the diet; [0107] 2. A dietary deficiency or impaired absorption of vitamin E and related metabolites; [0108] 3. A dietary deficiency or impaired absorption/epithelial transport of vitamin E-related metabolites

[0109] Specifically relating to the association of serum vitamin E concentrations and CRC, there have been no reports of significantly reduced vitamin E levels in CRC patients relative to controls. The most recent and robust study is that of Ingles et al [35]. In this study the authors stated: We assayed plasma alpha and gamma-tocopherol concentrations for 332 subjects with colorectal adenomas and 363 control subjects from this previously signoidoscopy-based study. Increasing alpha and decreasing gamma-tocopherol levels were associated with decreased occurence of large (>=1 cm) but not of small (<=1 cm) adenomas; however, after adjustment for potential confounding variables, these trends were not significant.

[0110] In all of the aforementioned related epidemiological studies concerning vitamin E and CRC, the focus of the research surrounded the implications of diet on disease incidence. None of these studies contemplate the effect of the disease on these endogenous metabolites. Therefore, one of the underlying hypothesis is that a dietary deficiency in a specific vitamin or nutrient leads to an increased risk of a particular disease. The hypothesis that the disease state leads to a deficiency in an essential nutrient or vitamin is not contemplated.

[0111] Based on the discoveries disclosed in this application, it is contemplated that although dietary deficiencies may increase the risk of CRC incidence (which has not been conclusively proven), the presence of CRC results in a decrease of vitamin E isoforms and related metabolites. These decreased levels are not likely to be the result of a simple dietary deficiency, as such a strong association would have been revealed in epidemiological studies. If CRC causes a decrease in these metabolites and not vice versa, then the weak epidemiological linkages between vitamin E concentrations and CRC may simply be the result of early, undetected CRC presence in the assumed normal cohort, as it is known that CRC can take many years to manifest to a size and degree that is detectable by colonoscopy.

[0112] Based on the discoveries disclosed in this application, it is also contemplated that the decreased levels of vitamin E-like metabolites are not the result of a simple dietary deficiency, but rather impairment in the colonic epithelial uptake of vitamin E and related molecules. This therefore represents a rate-limiting step for the sufficient provision of anti-oxidant capacity to epithelial cells under an oxidative stress load. In this model, the dietary effects of increased iron consumption through red meats, high saturated fat, and decreased fibre (resulting in a decreased iron chelation effect [36]) results in the previously mentioned Fenton-induced free radical propagation, of which sufficient scavenging is dependent upon adequate epithelial levels of vitamin E. Increases in epithelial free radical load, combined with a vitamin E-related transport deficiency, would therefore be reflected by a decrease in vitamin E-like metabolites as anti-oxidants, as well as decreases in the reduced carboxylated isoforms resulting from hepatic uptake and P450-mediated metabolism. It has recently been shown that the uptake of Vitamin E into CaCo-2 colonic epithelial cells is a saturable process, heavily dependent upon a protein-mediated event [37]. Because protein transporters are in essence enzymes, and follow typical Michaelis-Menton kinetics, the rate at which vitamin E can be taken up into colonic epithelial cells would reach a maximal velocity (Vmax), which may not be capable of providing a sufficient anti-oxidant protective effect for the development of CRC. At some point in time, therefore, increasing rates of oxidative stress above the rate at which vitamin E can be transported into colon epithelial cells will deplete the intracolonic/epithelial pool. Therefore, the hypothesis for the development of CRC is based not only on increases in iron and low fiber in the diet, but on a deficiency in epithelial uptake of vitamin E gamma and related metabolites. This is consistent with many of the epidemiological studies showing a lack of any significant correlation between CRC incidence and dietary vitamin E supplementation, as large doses of vitamin E under this model would not be reflected by increased intra-epithelia levels.

[0113] The accurate neutral masses of the nine metabolites (M-H ions converted to neutral mass) specific to CRC pathology were determined by FTICR-MS to be 446.3406, 448.3563, 450.3726, 464.3522, 466.3661, 468.3840, 538.4259, 592.4711, and 594.4851. Based on these accurate neutral mass values, the molecular formulas of the nine preferred diagnostic markers were determined to be C28H46O4, C28H48O4, C28H50O4, C28H48O5, C28H50O5, C28H52O5, C32H58O6, C36H64O6, C36H66O6, respectively.

[0114] The M-H ions of these metabolites are characterized as having a collision induced dissociation (CID) MS/MS fragmentation pattern comprising one or more than one of the daughter ions shown in FIGS. 13 to 21. More particularly, the M-H ions of these seven metabolites are characterized in having a collision induced dissociation (CID) MS/MS fragmentation pattern comprising each of the daughter ions shown in FIGS. 13 to 21.

[0115] Based upon the accurate mass MS/MS spectra, putative structures were assigned to each of the biomarkers. The collective interpretation of the MS/MS spectra of the biomarkers revealed that they all contain a carboxylic acid moiety (as evidenced by a loss of CO.sub.2) and at least one hydroxyl moiety (as evidenced by the loss of H2O). Furthermore all of the structures except the C28H46O4 produced a C.sub.15H.sub.xO.sub.y fragment where x31 and y2, suggestive of a highly saturated fatty acid side chain. This information is consistent with the C.sub.28 molecules being metabolites of gamma-tocopherol and gamma-tocotrienol. The C.sub.32 and C.sub.36 biomarkers were subsequently hypothesized to be metabolic byproducts resulting from the reaction of gamma-tocopherol and the lipid peroxides of linoleic and oleic acid residues, respectively.

[0116] The confirmed structures for four of, and putative structures for two of, the selected six metabolites are shown in FIG. 12.

[0117] The present invention is also defined with reference to the following examples that are not to be construed as limiting.

EXAMPLES

Example 1: Discovery and Identification of Differentially Expressed Metabolites in CRC-Positive Versus Normal Healthy Controls

[0118] The biochemical markers of CRC described in the invention were derived from the analysis of 40 serum samples from CRC-positive patients (24 TNM stage I/II and 16 stage III/IV) and 50 serum samples from healthy controls. All samples were single time-point collections, and the CRC samples were taken either immediately prior to or immediately following surgical resection of a tumor. All samples were taken prior to chemo- or radiation therapy.

[0119] Multiple non-targeted metabolomics strategies have been described in the scientific literature including NMR [38], GC-MS [39-41], LC-MS, and FTMS strategies [38, 42-44]. The metabolic profiling strategy employed for the discovery of differentially expressed metabolites in this application was the non-targeted FTMS strategy invented by Phenomenome Discoveries [40, 44-47].

[0120] The invention described herein involved the analysis of serum extracts from 90 individuals (40 CRC, 50 normal) by direct injection into an FTMS and ionization by either ESI or APCI, in both positive and negative modes. The advantage of FTMS over other MS-based platforms is the high resolving capability that allows for the separation of metabolites differing by only hundredths of a Dalton, many of which would be missed by lower resolution instruments. Organic (100% butanol) sample extracts were diluted either three or six-fold in methanol:0.1% (v/v) ammonium hydroxide (50:50, v/v) for negative ionization modes, or in methanol:0.1% (v/v) formic acid (50:50, v/v) for positive ionization modes. For APCI, ethyl acetate organic sample extracts were directly injected without diluting. All analyses were performed on a Bruker Daltonics APEX III FTMS equipped with a 7.0 T actively shielded superconducting magnet (Bruker Daltonics, Billerica, Mass.). Samples were directly injected using ESI and APCI at a flow rate of 600 L per hour. Ion transfer/detection parameters were optimized using a standard mix of serine, tetra-alanine, reserpine, Hewlett-Packard tuning mix and the adrenocorticotrophic hormone fragment 4-10. In addition, the instrument conditions were tuned to optimize ion intensity and broad-band accumulation over the mass range of 100-1000 amu according to the instrument manufacturer's recommendations. A mixture of the abovementioned standards was used to internally calibrate each sample spectrum for mass accuracy over the acquisition range of 100-1000 amu.

[0121] In total six separate analyses comprising combinations of extracts and ionization modes were obtained for each sample:

[0122] Aqueous Extract [0123] 1. Positive ESI (analysis mode 1101) [0124] 2. Negative ESI (analysis mode 1102)

[0125] Organic Extract [0126] 3. Positive ESI (analysis mode 1201) [0127] 4. Negative ESI (analysis mode 1202) [0128] 5. Positive APCI (analysis mode 1203) [0129] 6. Negative APCI (analysis mode 1204)

[0130] Using a linear least-squares regression line, mass axis values were calibrated such that each internal standard mass peak had a mass error of <1 ppm compared with its theoretical mass. Using XMASS software from Bruker Daltonics Inc., data file sizes of 1 megaword were acquired and zero-filled to 2 megawords. A sinm data transformation was performed prior to Fourier transform and magnitude calculations. The mass spectra from each analysis were integrated, creating a peak list that contained the accurate mass and absolute intensity of each peak. Compounds in the range of 100-2000 m/z were analyzed. In order to compare and summarize data across different ionization modes and polarities, all detected mass peaks were converted to their corresponding neutral masses assuming hydrogen adduct formation. A self-generated two-dimensional (mass vs. sample intensity) array was then created using DISCOVAmetrics software (Phenomenome Discoveries Inc., Saskatoon, SK, Canada). The data from multiple files were integrated and this combined file was then processed to determine all of the unique masses. The average of each unique mass was determined, representing the y-axis. A column was created for each file that was originally selected to be analyzed, representing the x-axis. The intensity for each mass found in each of the files selected was then filled into its representative x,y coordinate. Coordinates that did not contain an intensity value were left blank. Once in the array, the data were further processed, visualized and interpreted, and putative chemical identities were assigned. Each of the spectra were then peak picked to obtain the mass and intensity of all metabolites detected. These data from all modes were then merged to create one data file per sample. The data from all 90 samples were then merged and aligned to create a two-dimensional metabolite array in which each sample is represented by a column and each unique metabolite is represented by a single row. In the cell corresponding to a given metabolite sample combination, the intensity of the metabolite in that sample is displayed. When the data is represented in this format, metabolites showing differences between groups of samples (i.e., normal and cancer) can be determined.

[0131] A student's T-test was used to select for metabolites that differ between the normal and the CRC-positive samples (p<0.05). The metabolites (480) that met this criterion are shown in Table 3. These are all features that differ in a statistically significant way between the two populations and therefore have potential diagnostic utility. The features are described by their accurate mass and analysis mode, which together are sufficient to provide the putative molecular formulas and chemical characteristics (such as polarity and putative functional groups) of each metabolite. However, the incorporation and development of 480 signals into a commercially useful assay is impractical, so supervised statistical methods were used to extract the optimum diagnostic feature set from the 480, as described below.

[0132] A supervised statistical method called prediction analysis of microarrays (PAM) was used to select metabolite features having optimal diagnostic properties from the initial array [48]. The method involves training a classifier algorithm using samples with a corresponding known diagnosis, which can then be applied to diagnose unknown samples (i.e. a test set). Several supervised methods exist, of which any could have been used to identify the best feature set, including artificial neural networks (ANNs), support vector machines (SVMs), partial least squares discriminant analysis (PLSDA), sub-linear association methods, Bayesian inference methods, supervised principal component analysis (PCA), shrunken centroids (described here), or others (see [49] for review).

[0133] Since there were only 40 CRC samples to work with in the study, the validity of the PAM method for diagnosing CRC was tested in two ways. First, a cross-validated training classifier was created using all 90 samples (CRC and normal), leaving no samples for a test set. The second method involved randomly splitting the samples in half, using one half to generate a classifier and the other half as a blinded test set for diagnosis. Since the first method creates the classifier using more samples, its predictive accuracy would be expected to be higher than the second approach, and consequently should require fewer metabolites for high diagnostic accuracy. The key point is that the same diagnostic features identified in the first method are also inclusive to the subset identified in the second method. Based on these results, and signal-to-noise intensity information from the mass spectrometry data, seven metabolites were selected as the optimal CRC diagnostic biomarker set for further structural characterization. The graph in FIG. 2A shows the number of metabolites required to achieve given training errors at various threshold values (a user-definable PAM parameter). The plot shows that a training classifier with less than 10% error rate (0.1 training error) is possible with as few as 7 metabolite features (threshold value of approximately 5.8, see arrow). It is worthwhile to note that the lowest training error can be achieved using 300 or greater metabolite features, however, the error is only a few percent lower than using 7 metabolite features, and using hundreds of features would be impractical for clinical utility. The plot in FIG. 2B is conceptually similar to that in FIG. 2A, however, the graph in 2B shows the misclassification error of the trained classifier for CRC and normal individuals following the cross-validation procedure integral to the PAM program. The line connected by diamonds mirrors the previous result, showing that minimal cross-validated misclassification error for CRC-positive individuals can be achieved using as few as seven metabolites. It also shows that normal individuals, depicted by the squares, can be accurately diagnosed as normal using only one metabolite feature, but at this threshold, the misclassification error for CRC is greater than 95% (see arrows). Therefore, the best combination of metabolite features based on this method, which can both positively and negatively diagnose CRC comprises a combination of seven metabolite features. These included masses of, or substantially equivalent to 446.3406, 450.3726, 466.3661, 538.4259, 468.384, 592.4711, and 594.4851.

[0134] The individual cross-validated diagnostic probabilities for each of the 90 individuals in the study are shown in FIG. 3. All of the CRC-positive samples are listed on the left side of the graph, and the normal individuals on the right. Each sample contains two points on the graph, one showing the probability of having CRC (diamonds), and one showing the probability of not having CRC (i.e. normal, squares). As can be seen, there are seven CRC samples, which classify as normal (circled on the left side of the graph) and two normal samples that classify as CRC-positive (circled on the right side of the graph). The predicted probabilities were then used to create the receiver-operating characteristic (ROC) curve in FIG. 4 using JROCFIT, which shows the true positive fraction (those with CRC being predicted to have CRC) versus the false positive fraction (normal individuals predicted as having CRC). The area under the curve is 95%, with a sensitivity of 82.5%, and a specificity of 96%. Overall, the diagnostic accuracy is 90% based on the cross-validated design. These seven metabolites were further selected for structural characterization.

[0135] The more samples that are available as the training set, the more accurate the resulting classifier should be at diagnosing unknown samples. This was the reason for using all 90 samples to identify the optimal diagnostic marker panel described above. However, the drawback of this approach is that it leaves no samples available as blinded test set (which were not included in the training set). To address this problem, the samples were randomly split into two groups: one for creating the classifier and one to use as a test set. The training set comprised 21 CRC samples and 27 normals. The optimal number of metabolites required for the lowest misclassification error using these samples was 16, listed at the bottom of FIG. 5. Within these 16 are contained the subset of seven described above. The classifier was next used to predict the diagnosis of the remaining samples (blinded; 22 CRC and 27 normal). The predicted probabilities of the blinded test samples as either being CRC-positive or normal are plotted in FIG. 5. The results show that two of the CRC-positive samples are given a higher probability of being normal, and two of the normals are given a higher probability of being CRC-positive. FIG. 6A lists the patients, which were used in the test set, and their actual and predicted diagnosis. The probabilities from FIG. 5 were then translated into a ROC curve, as shown in FIG. 6B. The performance characteristics based on classification of the blinded test set were sensitivity of 91%, specificity of 92.6%, and overall diagnostic accuracy of 91.8%.

[0136] To verify that the seven metabolites selected by the classifier were indeed showing differences between CRC and normal serum, the raw spectral data were visualized. Spectra for six of the seven biomarkers for five of the normal and five of the CRC samples are shown in FIGS. 7A to 7F (normals on the top and CRCs on the bottom of each panel). In each case, the marker is present in the normal samples, and absent from the CRC samples.

[0137] Based upon these results, a clear distinction can be made between the serum of CRC-positive patients and healthy (non-CRC) individuals. Therefore, such findings, capable of identifying and distinguishing CRC-positive and CRC-negative serum, can form the basis for a CRC diagnostic test as described in this application.

Example 2: Independent Method Confirmation of Discovered Metabolites

[0138] The intensity differences between normal and CRC serums for the seven diagnostic metabolites discovered using the FTMS method were verified using an independent mass spectrometry method. Five representative CRC-positive sample extracts and five representative normal sample extracts were analyzed by LC-MS using an HP 1050 high-performance liquid chromatography interfaced to an ABI QSTAR mass spectrometer.

[0139] Ethyl acetate fractions from five CRC and five normal sample extracts were evaporated under nitrogen gas and reconstituted in 70 uL of isopropanol:methanol:formic acid (10:90:0.1). 10 L of the reconstituted sample was subjected to HPLC (HP 1050 with Hypersil ODS 5 u, 1254 mm column, Agilent Technologies) for full scan, and 30 L for MS/MS at a flow rate of 1 ml/min.

[0140] Eluate from the HPLC was analyzed using an ABI QSTAR XL mass spectrometer fitted with an atmospheric pressure chemical ionization (APCI) source in negative mode. The scan type in full scan mode was time-of-flight (TOF) with an accumulation time of 1.0000 seconds, mass range between 50 and 1500 Da, and duration time of 55 min. Source parameters were as follows: Ion source gas 1 (GS1) 80; Ion source gas 2 (GS2) 10; Curtain gas (CUR) 30; Nebulizer Current (NC) 3.0; Temperature 400 C.; Declustering Potential (DP) 60; Focusing Potential (FP) 265; Declustering Potential 2 (DP2) 15. In MS/MS mode, scan type was product ion, accumulation time was 1.0000 seconds, scan range between 50 and 650 Da and duration time 55 min. All source parameters are the same as above, with collision energy (CE) of 35 V and collision gas (CAD, nitrogen) of 5 psi.

[0141] The extracted ion chromatograms (EICs) as detected in the QSTAR for six of the biomarkers are shown in FIGS. 8A to 8F. The top panel shows the five normal EICs, and the bottom panel of each shows the five CRC EICs. Also, the sensitivity of the QSTAR is superior as compared to the FTMS, resulting in a greater magnitude in intensity difference between the normal and CRC populations for the selected biomarkers.

[0142] FIG. 9 shows three sets of extracted mass spectra (EMS) for six of the metabolites at a retention time window of 16-17 minutes. FIG. 9A represent the average EMS of the five normal samples, while FIG. 9B represents the average EMS for the five CRC samples. FIG. 9C shows the net difference between the top two spectra. As can be seen, all peaks in the mass range between approximately 445 and 600 Da are barely detectable in the CRC panel (boxed region). All seven of the biomarkers identified on the FTMS platform were detected on the Q-Trap, and were seven of the most abundant peaks in this mass range (highlighted by arrows).

[0143] Averages of the seven markers as detected on the FTMS and Q-Star for normals and CRC patients are shown in FIG. 10A and FIG. 10B, respectively. With both platforms, a reproducible and consistent depletion of these molecules was observed in the CRC-positive population.

[0144] Although the PAM algorithm had selected seven features with optimal diagnostic performance, we re-examined the initial FTMS discovery data for metabolites which appeared to be related to these seven based on molecular formula, chemical properties and ionization information. We were able to identify over 30 molecules related to the seven PAM had selected which all showed decreased expression in the CRC patient cohort. These could further be categorized according to the carbon content, that is, either 28, 32, or 36 carbons (see FIG. 11). In addition, native alpha and gamma-tocopherol were identified and also showed decreased intensity in the CRC cohort (FIG. 11, GT and AT). Based on this information, we re-evaluated which molecules should be carried forward into a high-throughput screening method, and decided to use the six C28-containing molecules, as they consistently appeared to be the most robust discriminators between the two populations (CRC and normals).

Example 3: Structure Elucidation of the Primary Metabolite Biomarkers (NMR, FTIR and MSMS)

[0145] The principal characteristics that are normally used for the structural elucidation of novel metabolites are accurate mass and molecular formula determination, polarity, acid/base properties, NMR spectra, and MS/MS or MSn spectra. However, it would be obvious to one skilled in the art that other characteristics of the metabolites could be used in an attempt to determine its structure.

[0146] The molecular formulas of the nine preferred diagnostic markers were determined to be C28H46O4, C28H48O4, C28H50O4, C28H48O5, C28H50O5, C28H52O5, C32H58O6, C36H64O6, C36H66O6 based on their accurate neutral mass, polarity, and ionization characteristics. These metabolites have been determined, according to the present invention to consist of a semi-saturated chroman ring and phytyl side chain and therefore consistent with vitamin E-related structures.

[0147] The extracts containing the metabolites of interest were subjected to reverse phase LC-MS using a C18 column and analysis by MS as described in the detailed methods above. The retention time for all said vitamin E-like biomarkers is approximately 16.5 minutes under these HPLC conditions.

[0148] The conditions of extraction also provide insights about the chemical properties of the biomarkers. All seven of the metabolite markers were extracted into an organic ethyl acetate fraction, indicating that these metabolites are non-polar under acidic condition. Furthermore, they were preferentially ionized in negative APCI mode indicating an acidic proton is present in the molecules.

[0149] The structure of a given molecule will dictate a specific fragmentation pattern under defined conditions that is specific for that molecule (equivalent to a person's fingerprint). Even slight changes to the molecule's structure can result in a different fragmentation pattern. In addition to providing a fingerprint of the molecule's identity, the fragments generated by CID can be used to gain insights about the structure of a molecule. MS/MS analysis was carried out on the ABI-QSTAR XL with all parameters as previously mentioned using nitrogen as the collision gas at 5 psi and CE settings of 25, 35 and 50 volts.

[0150] The six metabolites identified as having the best diagnostic ability and suitability for HTS development were subject to MS/MS fragmentation using collision-induced dissociation (CID). The six were selected from the original nine to narrow the group to all C28-containing molecules and to molecules that could be all detected in the same analysis mode. FIG. 12, at Structures A to F, compares the structures of the six molecules to the gamma forms of tocopherol and tocotrienol. This figure can be referred to for the following detailed structural descriptions below.

[0151] Based upon the accurate mass MS/MS spectra, putative structures were assigned to each of the biomarkers. In summary, the collective interpretation of the MS/MS spectra of the biomarkers revealed that they all contain a carboxylic acid moiety (as evidenced by a loss of CO2) and at least one hydroxyl moiety (as evidenced by the loss of H2O). Furthermore all of the structures except the C28H46O4 produced a C18HxOy fragment where x31 and y2, suggestive of a highly saturated fatty acid side chain. This information is consistent with the C28 molecules being metabolites of gamma-tocopherol. The C32 and C36 biomarkers were subsequently hypothesized to be metabolic byproducts resulting from the reaction of gamma-tocopherol and the lipid peroxides of linoleic and oleic acid residues, respectively (FIGS. 19 to 21). The MS/MS spectra support this hypothesis. As would be obvious to someone skilled in the art, minor modifications (including, but not limited to, the location of a double bond, the location of a hydroxyl group, the stereo or chiral orientation of certain carbon atoms) would not distract significantly from the identity of the biomarkers as described. The assignment of the structures to fragments are shown in FIGS. 13 to 21, and listed in Tables 5 to 10 for six of the markers further characterized below. The masses reported for MS-MS results refer to the detected mass, and not the neutral mass. These are referred to as M-1 masses, and will appear to lack one Dalton in mass or a hydrogen within the formula relative to their neutral counterparts mentioned in the previous sections, because they are detected in a negative ionization mode on the mass spectrometer. However, M-1 masses represent the same molecules as the neutral counterparts. The subsequent NMRsection refers to neutral masses.

[0152] Specifically, MS/MS data obtained in the negative ionization mode for each biomarker was individually analyzed for structural assignment, particularly the placement of functional groups. The MS/MS spectra of each biomarker showed peaks due to loss of water (M-18) and carbon dioxide (M-44). These stipulate the presence of free hydroxyl groups adjacent to a tertiary or secondary carbon molecule and a carboxylic acid group. Loss of the phytol chain fragment was also commonly observed but cleavage of the chain occurred at different places.

[0153] For C.sub.28H.sub.48O.sub.4 (Table 5, FIG. 13; [M-H].sup.: C.sub.28H.sub.47O.sub.4.sup.) an initial loss of water and carbon dioxide (m/z 385; C.sub.27H.sub.45O) is observed. Next fragment representing m/z 279 (C.sub.19H.sub.35O) is suggestive of a consequent chroman ring opening at O1-C9 and cleavage of the phytol chain at C10-C4 position.

[0154] For C.sub.28H.sub.48O.sub.5 (Table 6, FIG. 14; [M-H].sup.: C.sub.28H.sub.47O.sub.5.sup.), which possesses two free hydroxyl functionalities shows loss of two water molecules along with the regular carbon dioxide loss (m/z=383; C.sub.27H.sub.43O). Sequential ring opening at O1-C9 is indicative in here too, followed by the cleavage between C18-C19 generating a fragment of C.sub.22H.sub.35O (m/z 315). Subsequent signal corresponding to m/z 297 (C.sub.22H.sub.33), representing a loss of a water molecule from the open ring fragment was also observed. Unlike in biomarker 3 (m/z 448.3726) the cleavage of the phytol chain takes place at C12-C13 where the signals for the two halves of the molecules, m/z 241 (C.sub.14H.sub.25O.sub.3), 223 (C.sub.14H.sub.23O.sub.2) were observed in the MS/MS spectra of C28H48O5. This particular fragmentation is a strong evidence for the distribution of the functional groups between the chroman ring and the phytol chain.

[0155] MS/MS spectrum of C.sub.28H.sub.46O.sub.4 (Table 7, FIG. 15; [M-H].sup.: C.sub.28H.sub.45O.sub.4.sup.) exhibit a similar pattern to that of C.sub.28H.sub.48O.sub.5. Loss of water (m/z 427; C.sub.28H.sub.43O.sub.3) and carbon dioxide (m/z 401; C.sub.27H.sub.45O.sub.2) observed to be both alternate and instant (m/z 383; C.sub.27H.sub.43O). Like in C.sub.28H.sub.48O.sub.5 the cleavage of the phytol chain takes place at C12-C13, after an initial loss of water between C17-C18, generating a fragment of m/z 223 (C.sub.14H.sub.23O.sub.2). The other counter fragment, C.sub.14H.sub.21O (m/z 205) is also observed and is also representative as the parent ion of next two consecutive fragments, m/z 177 (C.sub.12H.sub.17O) and 162 (C.sub.11H.sub.114O) indicating losses of C.sub.2H.sub.8 and CH.sub.3 respectively.

[0156] Interestingly, in C.sub.28H.sub.50O.sub.5 (Table 8, FIG. 16; [M-H].sup.: C.sub.28H.sub.49O.sub.5.sup.), in addition to the accustom losses of water (m/z 447; C.sub.28H.sub.47O.sub.4) and carbon dioxide (m/z 421; C.sub.26H.sub.45O.sub.3), loss of an ethanol fragment (m/z 433; C.sub.27H.sub.45O.sub.4) followed by an ethylene fragment (m/z 405; C.sub.26H.sub.45O.sub.3) is also detected. These observations signify the proposed ring opening at C2-C3 of the chroman ring and hydroxylation of the C27 methyl group, generating viable precursors for methanol and ethylene fragments. Several different fragments were observed due to the fragmentation of the phytol side chain. Cleavage at C18-C19 (m/z 349; C.sub.22H.sub.37O.sub.3), cleavage at C1-C2 after an initial water loss between C18-C17 (m/z 297; C.sub.18H.sub.33O.sub.3) followed by a loss of another water molecule (m/z 279; C.sub.18H.sub.31O.sub.2) and cleavage at C15-C16 (m/z 185; C13H19O3) were among them. The anticipated fragmentation between C12-C13 were also observed as two counter molecular-ion halves, m/z 241 (C.sub.15H.sub.29O.sub.2) and 223 (C.sub.13H.sub.19O.sub.3).

[0157] The MS/MS spectrum of C.sub.28H.sub.50O.sub.4 (Table 9, FIG. 17; [M-H].sup.: C.sub.28H.sub.49O.sub.4.sup.) also displayed the expected water and carbon dioxide losses (m/z 431; C.sub.28H.sub.49O.sub.4, 405; C27H.sub.492). Similar to that of C.sub.28H.sub.48O.sub.5 this showed a fragment due to the loss of two water molecules (m/z 413; C.sub.28H.sub.45O.sub.2). This suggests the presence of two free hydroxyl groups in the structure. Cleavage of the phytol ring takes place at two positions, between C15-C16 (m/z 281; C.sub.18H.sub.33O.sub.2) and between C16-C17 followed by a loss of water molecule (m/z 277; C.sub.19H.sub.33O). These fragments establish the absence of a hydroxyl group in the phytol chain and the unsaturation between C17-C18. The structure of biomarker 7 is assembled accordingly.

[0158] The MS/MS spectra of C.sub.28H.sub.52O.sub.5 (Table 10, FIG. 18; [M-H].sup.: C.sub.28H.sub.51O.sub.5.sup.) indicated loss of two water molecules (m/z 431; C.sub.28H.sub.47O.sub.3) and another fragment for a loss of water and a carbon dioxide molecules at the same time (m/z 405; C.sub.27H.sub.49O.sub.2) suggesting for the presence of two free hydroxyl groups and a carbonyl functionality. Some of the fragments observed here are identical to that of C.sub.28H.sub.50O.sub.5, of which the only difference from C.sub.28H.sub.52O.sub.5 is an excess degree of unsaturation. Cleavage at C1-C2 after an initial water loss between C18-C17 (m/z 297; C.sub.18H.sub.33O.sub.3) followed by a loss of another water molecule (m/z 279; C.sub.18H.sub.31O.sub.2) were among them. Subsequent loss of a CH.sub.4 from C.sub.18H.sub.31O.sub.2 is represented by the molecular ion peak m/z 263 (C.sub.17H.sub.27O.sub.2). The molecular ion peak of m/z 215 (C.sub.12H.sub.23O.sub.3) is suggestive of a fragment of the phytol chain due to C13-C14 bond cleavage followed by a loss of CH.sub.3. Fragment due to the cleavage of the phytol chain at C15-C16 (m/z 187; C.sub.10H.sub.19O.sub.3) was observed as the parent ion for the next two consecutive fragments, resulted due to loss of a water molecule (m/z 169; C.sub.10H.sub.17O.sub.2) and an ethylene fragment (m/z 141; C.sub.8H.sub.13O.sub.2) respectively from C.sub.10H.sub.19O.sub.3.

[0159] In addition to the six C28-containing molecules, MSMS analysis of the non C28 vitamin E-like molecules was also performed as shown in FIGS. 19 through 21. These C32 and C36 biomarkers thought to be metabolic byproducts resulting from the reaction of gamma-tocopherol and the lipid peroxides of linoleic and oleic acid residues, respectively. The MS/MS spectra support this hypothesis as shown in FIGS. 19 to 21.

[0160] For the NMR and FTIR methods, all chemicals and media were purchased from Sigma-Aldrich Canada Ltd., Oakville, ON. All solvents were HPLC grade. Analytical thin layer chromatography (TLC) was carried out on precoated silica gel TLC aluminum sheets (EM science, Kieselgel 60 F.sub.254, 52 cm0.2 mm). Compounds were visualized under UV light (254/366 nm) or placed in iodine vapor tank and by dipping the plates in a 5% aqueous (w/v) phosphomolybdic acid solution containing 1% (w/v) ceric sulfate and 4% (v/v) H.sub.2SO.sub.4, followed by heating. Preparative thin layer chromatography (prep TLC) was performed on silica gel plates (EM science, 60 F.sub.254 2020 cm, 0.25 mm thickness). Compounds were visualized under UV light and in iodine. HPLC analysis were carried out with a high performance liquid chromatograph equipped with quaternary pump, automatic injector, degasser, and a Hypersil ODS column (5 m particle size silica, 4.6 i.d200 mm) and semi-prep column (5 m particle size silica, 9.1 i.d200 mm), with an inline filter. Mobile phase: linear gradient H.sub.2O-MeOH to 100% MeOH in a 52 min period at a flow rate 1.0 ml/min.

[0161] NMR spectra were recorded on a Bruker Avance spectrometers; for .sup.1H (500 MHz), values were referenced to CDCl.sub.3 (CHCl.sub.3 at 7.24 ppm) and for .sup.13C NMR (125.8 MHz) referenced to CDCl.sub.3 (77.23 ppm). High resolution (HR) mass spectra (MS) were recorded on Bruker apex 7T Fourier transform ion cyclotron resonance (FT-ICR) and QStar XL TOF mass spectrometers with atmospheric pressure chemical ionization (APCI) source in the negative mode. Fourier transform infrared (FT-IR) spectra were recorded on a Bio-Rad FTS-40 spectrometer. Spectra were measured by the diffuse reflectance method on samples dispersed in KBr.

[0162] A semi-purified pooled HPLC fraction (32 mg) of serum extracts which exhibited a mixture of gamma-tocopherol-like and gamma-tocotrienol-like compounds in .sup.1H NMR spectrum was purified by preparative TLC to yield the structures as shown in FIG. 12, Structures C (3, 3.6 mg), D (4, 2.5 mg), E (5, 3.4 mg), and F (6, 4.6 mg). We refer to these novel structures as gamma-tocoenoic acids in the following section.

[0163] The molecular formula of gamma-tocoenoic acid 3; FIG. 12, Structure C (3) was determined as C.sub.28H.sub.48O.sub.4 (neutral) by HRAPCI-MS, possessing five degrees of unsaturation. The FTIR absorptions at 3315 (br) and 1741 cm.sup.1 suggested hydroxyl and carbonyl groups. Analysis of the .sup.1H and .sup.13C NMR spectroscopic data (Tables 11 and 12) indicated the presence of six methyl groups, four olefinic carbons and a long phytol chain as present in gamma-tocotrienol; FIG. 12, Structure B (2)[50, 51]. Analysis of the HMQC and HMBC data were instrumental in the assignment of the structure. The only carbonyl-like carbon present at .sub.C 173.8 (C-23) which displayed one long range correlation with a methine proton at .sub.H 2.24 (H-22) was confirmed as carboxylic acid functionality using the loss of carbon dioxide observed in its MS/MS spectra. Likewise, the carbon at .sub.C 74.2 (C-9) displayed correlations with a methylene proton at .sub.H 2.28 (H-4) which together with another methylene proton at .sub.H 2.28 (H-6) showed HMBC correlations with a sp.sup.2 carbon at Sc 130.5 (C-10). These are indicative of a semi-saturated chroman ring system as present in gamma-tocotrienol (FIG. 12, Structure B). On the phytol side chain, long range correlations were observed between methyl protons at .sub.H 1.55 (H-26) and sp.sup.2 carbon at Sc 123.2 (C-13), methylene protons around .sub.H 1.01 (H-12, H-15) and sp.sup.2 carbon at Sc 140.2 (C-14), and methyl protons around .sub.H 0.91 (H-25) and the quaternary carbon at .sub.C 56.6 (C-18). The MS/MS spectral analysis confirms fragments due to a loss of water and carbon dioxide and ring opening at C9-01 position followed by the loss of phytol side chain fragment (m/z 279; C.sub.18H.sub.31O.sub.2). Hence, the structure of this gamma-tocoenoic acid was assigned as 3 (FIG. 12, Structure C).

[0164] Gamma-Tocoenoic acid 4; FIG. 12, Structure D (4) had a molecular formula of C.sub.28H.sub.48O.sub.5 (HRAPCI-MS) indicating five degrees of unsaturation. The FTIR absorptions at 3437 (br) and 1743 cm-1 suggested hydroxyl and carbonyl groups. The .sup.1H and .sup.13C NMR spectra were very similar to that of C28H48O4. The only difference included an additional hydroxy group, indicated by an additional H.sub.2O loss in the MS/MS fragmentations when compared to that of C28H48O4, which was assigned on C-6 considering the .sup.1H-.sup.1H COSY correlations of the methylene protons, H-5 (.sub.H 2.21-2.25) and H-7 ((.sub.H 1.47-1.53), to the methine proton, H-6 (.sub.H3.69-3.71). MS/MS spectral analysis also confirmed the presence of the carboxylic group indicative by the loss of CO.sub.2 molecule and MS/MS fragments due to the cleavage between C12 and C13, C.sub.14H.sub.25O.sub.3 (m/z 241) and C.sub.14H.sub.23O.sub.2 (m/z 223), which further supports the assignment of the diene on the phytol side chain and hydroxylation on the chroman ring. Hence, the structure of gamma-tocoenoic acid 4 was assigned as shown in FIG. 12, Structure D.

[0165] Gamma-Tocoenoic acid 5; FIG. 12, Structure E (5) had a molecular formula of C.sub.28H.sub.46O.sub.4 (HRAPCI-MS) indicating six degrees of unsaturation. The FTIR absorptions at 3125 (br) and 1736 cm.sup.1 suggested the presence of hydroxyl and carbonyl groups. The .sup.1H and .sup.13C NMR spectra were very similar to that of C28H48O4; the only difference was an additional double bond in the semi-saturated chroman ring system resulted by highly liable dehydration between C6 and C7. The MS/MS spectral analysis confirmed the presence of the carboxylic group, fragments due to water loss as well as the fragments due to the cleavage between C12 and C13, C.sub.14H.sub.23O.sub.2 [m/z 223; (C.sub.14H.sub.25O.sub.3H.sub.2O) and C.sub.14H.sub.21O (m/z 205; C.sub.14H.sub.23O.sub.2H.sub.2O) similar to those observed for C28H48O5. Hence, the structure of gamma-tocoenoic acid 5 was assigned as shown in FIG. 12, Structure E.

[0166] Gamma-Tocopheric acid 6 (FIG. 12, Structure F) had a molecular formula of C.sub.28H.sub.505 (HRAPCI-MS) indicating four degrees of unsaturation. The FTIR absorptions at 3314 (br) and 1744 cm.sup.1 suggested hydroxyl and carbonyl groups. The .sup.1H and .sup.13C NMR spectra showed some similarities to that of C28H48O4 and C28H48O5 but there were some significant differences observed as well. The similarities include the presence of six methyl groups, four sp.sup.2 hybridized carbons, and a carbonyl-like carbon at Sc 174.1 (C-23), displaying long range correlation with a methine proton at .sub.H 2.28 (H-22). The differences include the opening of the chroman ring system, with the .sup.1H NMR spectrum displaying a spin system containing two methylene protons at .sub.H 4.27-4.29 (H-27a, dd, J=4.0, 12.0 Hz) and .sub.H4.04-4.14 (H-27b, dd, J=6.0, 12.0 Hz) coupled together and to a methine proton at .sub.H 5.12 (H-2, m), established using .sup.1H-.sup.1H COSY and .sup.1H-.sup.1H homonuclear decoupling experiments. In addition HMBC and .sup.1H-.sup.1H COSY of C28H50O5 did not exhibit the long range correlations between methyl protons and sp.sup.2 carbon which was a common fact for the other tocotrienoic acids C28H48O4, C28H48O5 and C28H46O4, indicating the saturation of the phytol side chain, which confine this structure as a derivative of gamma-tocopheric acid. The MS/MS spectral analysis confirmed the presence of the carboxylic group, fragments due to water loss as well as the two common fragments as a consequence of the cleavage between C12 and C13, m/z 241 and 223. This suggests that despite the ring opening between C2 and C3 and the saturation of the phytol chain, the rest of the structural aspects are similar to those of other identified tocoenoic acids C28H48O4, C28H48O5 and C28H46O4. Hence, the structure of gamma-tocopheric acid was assigned as 6 of FIG. 12, Structure F.

[0167] The structures of the other two biomarkers that could not be isolated by prep TLC using the tested solvent systems, C.sub.58H.sub.50O.sub.4 (7, FIG. 12, Structure G) and C.sub.28H.sub.52O.sub.5 (8, FIG. 12, Structure H) were assembled by evaluating their MS/MS fragmentation data, as shown in 12, Structures G and H, respectively.

[0168] The metabolites were isolated from serum and the structure re-confirmed by NMR. A total of 200 mL of serum was extracted with ethyl acetate (500 mL, 3), dried using the nitrogen evaporator and the extract reconstituted in 4 mL of methanol. The extract was subjected to LC/MS in fraction collection mode (100 L injections, 40) with fractions collected in 1 min windows for 52 mins. The expected metabolites, which eluted within 15-17 mins, were pooled and concentrated to dryness using the nitrogen evaporator (about 32 mg). The semi purified fraction which exhibited a mixture of tocopherol related compounds in .sup.1H NMR spectrum was subjected to prep TLC, developed with CH.sub.2C.sub.12hexane (2:1) to yield gamma-tocoenoic acid 3 (3.6 mg) and gamma-tocoenoic acid 4 (2.5 mg). The remaining bands were combined (about 22 mg) and further applied to prep TLC using cyclohexaneCH.sub.2Cl.sub.2-EtOAc (35:5:1, for two times) to yield gamma-tocoenoic acid 5 (3.4 mg), gamma-tocopheric acid 6 (4.6 mg) and a fraction (6.6 mg) which turned out to be a mixture.

Gamma-Tocoenoic Acid 3

[0169] TLC R.sub.f=0.81 (cyclohexane-CH.sub.2C.sub.12-EtOAc, 10:4:1); for .sup.1H and .sup.13C NMR spectra, see Tables 11 and 12; FTIR (cm.sup.1) 3315 (br), 2935, 2852, 1741, 1465, 1377, 1178, 726; HRAPCI-MS m/z: measured 447.3490 ([M-H].sup., calcd. 447.3480 for C.sub.28H.sub.47O.sub.4). MS/MS m/z (relative intensity): 447 ([M-H].sup., 50%), 429 (45%), 403 (100%), 385 (20%), 279 (10%).

Gamma-Tocoenoic Acid 4

[0170] TLC R.sub.f=0.21 (cyclohexane-CH.sub.2C.sub.12-EtOAc, 10:4:1); for .sup.1H and .sup.13C NMR spectra, see Tables 11 and 12; FTIR (cm.sup.1) 3347 (br), 2935, 2868, 1743, 1466, 1377, 1057, 958; HRAPCI-MS m/z: measured 463.3449 ([M-H].sup., calcd. 463.3429 for C.sub.28H.sub.47O.sub.5); MS/MS m/z (relative intensity): 463 ([M-H].sup., 100%), 445 (50%), 419 (90%), 401 (25%), 241 (20%).

Gamma-Tocoenoic Acid 5

[0171] TLC R.sub.f=0.79 (cyclohexane-CH.sub.2C.sub.12-EtOAc, 10:4:1, UV active spot); for .sup.1H and 3C NMR spectra, see Tables 11 and 12; FTIR (cm.sup.1) 3125 (br), 2941, 2855, 1736, 1556, 1466, 1377, 1177, 1008, 773; HRAPCI-MS m/z: measured 445.3333 ([M-H].sup., calcd. 445.3323 for C.sub.28H.sub.45O.sub.4). MS/MS m/z (relative intensity): 445 ([M-H].sup., 100%), 427 (60%), 401 (85%), 383 (40%), 223 (12%), 205 (20%), 177 (10%), 162 (18%).

Gamma-Tocopheric Acid 6

[0172] TLC R.sub.f=0.62 (cyclohexane-CH.sub.2Cl.sub.2-EtOAc, 10:4:1, UV active spot); for .sup.1H and .sup.13C NMR spectra, see Tables 11 and 12; FTIR (cm.sup.1) 3314 (br), 2926, 2854, 1744, 1465, 1379, 1253, 1145, 722; HRAPCI-MS m/z: measured 465.3588 ([M-H].sup., calcd. 465.3585 for C.sub.28H.sub.49O.sub.5). MS/MS m/z (relative intensity): 465 ([M-H].sup., 100%), 447 (50%), 421 (35%), 403 (20%), 349 (10%), 279 (18%).

Example 4. High-Throughput Screening (HTS) Method Development and Analysis of Independent Sample Set

[0173] A high throughput analysis method was then developed for the six primary biomarkers discovered using the FTMS method and confirmed using the LC-MS method.

[0174] Serum samples are extracted as described for non-targeted FTMS analysis. The ethyl acetate organic fraction is used for the analysis of each sample. 15 uL of internal standard is added (1 ng/mL of (24-.sup.13C)-Cholic Acid in methanol) to each sample aliquot of 120 uL ethyl acetate fraction for a total volume of 135 uL. The autosampler injects 100 uL of the sample by flow-injection analysis into the 4000QTRAP. The carrier solvent is 90% methanol:10% ethyl acetate, with a flow rate of 360 uL/min into the APCI source.

[0175] The MS/MS HTS method was developed on a quadrupole linear ion trap ABI 4000QTrap mass spectrometer equipped with a TurboV source with an APCI probe. The source gas parameters were as follows: CUR: 10.0, CAD: 6, NC: 3.0, TEM: 400, GS1: 15, interface heater on. Compound settings were as follows: entrance potential (EP): 10, and collision cell exit potential (CXP): 20.0. The method is based on the multiple reaction monitoring (MRM) of one parent ion transition for each metabolite, one transition for the endogenous housekeeper and a single transition for the internal standard. Each of the transitions is monitored for 250 ms for a total cycle time of 2.3 seconds. The total acquisition time per sample is approximately 1 min. A summary of the overall method is shown in FIG. 26. Briefly, the method measures the intensities of each of the six biomarker and internal standard (IS) transitions (as shown in FIGS. 27A to 27F), as well as a housekeeping biomarker transition (FIG. 27G) previously determined to be endogenously present in human serum. The housekeeping biomarker is a metabolite that was identified to not change with disease state, and should be detected in any correctly prepared serum sample. The objective of the housekeeping biomarker is therefore to ensure that samples collected from multiple sites are compatible with the HTS test. A patient score is then generated by determining the lowest mean-normalized log(2) transformed ratio of the six measured biomarker:IS transitions per patient. This value is then compared to a distribution of scores generated from normal individuals, and a CRC risk factor is assigned accordingly. We confirmed that the ABI 4000QTrap was capable of accurately measuring the transition peak areas using the method described above by plotting the peak area ratios of the biomarker transitions versus the internal standard transitions for each of the six biomarkers as well as the housekeeping metabolite (FIG. 26). In addition, the HTS method also incorporates a series of dilutions of reference serum material, which allows for the determination and assurance of instrument linearity. If the housekeeping metabolite is not detected, or the calibration curve has a R.sup.2 value >0.98, then the sample run is considered a failure and the sample needs to be rerun.

[0176] To validate the initial discovery that said vitamin E-like molecules are associated with CRC, an independent set of samples comprising 186 CRC, 288 normals, 24 prostate cancer, 25 ovarian cancer, 30 renal cell carcinoma, 25 lung cancer and 20 breast cancer samples were analyzed using the HTS method described above. The results of this analysis are summarized in Tables 13A, which shows that the sensitivity of the method for CRC is approximately 78% when a cutoff ratio of 1.3 is used to determine who should be considered at high risk for the presence of CRC (see normal distribution in FIG. 28 and diagnostic output in FIG. 29). This result irrefutably verifies the decreased levels of these novel vitamin E-like molecules with the presence of colon cancer. However, here it was also determined that the cross-cancer comparison showed a sensitivity of 70% among the ovarian cancers, and 36 to 40% sensitivity for renal cell and lung cancer, respectively. These sensitivity values were selected based upon an 89% specificity cutoff for CRC (this equates to an approximate 5% false-positive rate, since the normal distribution, as shown in FIG. 28, was based upon individuals who were not confirmed to be disease-free via colonoscopy. It has been previously reported that up to 10% of the average to low-risk population is positive for high-grade dysplasia upon endoscopic examination, which were not accounted for in our distribution[52]. Although the non-CRC cancer sets were relatively small in numbers, the overlap of the test results with ovarian cancer is significant and therefore diagnosis of ovarian cancer was included in the claims. Ultimately, larger populations of non-CRC cancers will need to be tested to confirm these results.

[0177] We also used randomly selected subsets of normal and CRC-positive individuals to check for bias due to age, ethnicity, BMI and gender, and observed no significant differences in the levels of said biomarkers within any of these variable classes (Table 13B). In addition, we observed no bias towards patients grouped into either stage I/II or III/IV (TNM) for CRC or to the presence or absence of polyps (Table 13B).

Example 5: Biological Interpretation of Metabolic Pathways Perturbed in CRC and OC

[0178] Based on the structural elucidation of the six biomarkers, and further investigation of the FTMS data, additional insights related to free radical formation and CRC were hypothesized.

[0179] Further investigation into putative tocopherol and tocotrienal metabolites revealed that both alpha and gamma-tocopherol concentrations in serum were observed to be significantly decreased in the CRC patient population (see FIG. 11). We calculated the alpha/gamma-tocopherol ratio to be 6.3, which is consistent with previously reported literature values. Particularly revealing was the observation that although serum alpha-tocopherol intensities were observed to be significantly higher than those of gamma, six metabolites with molecular formulas corresponding to omega-oxidized gamma-tocopherol/tocotrienol metabolites, which have never been reported in the literature, were observed in both the normals and in the CRC patients, whereas no omega-oxidized alpha-tocopherol metabolites were observed. These findings are consistent with the recent findings of Sontag and Parker [53], in which it was shown that the formation of omega COOH was over 50 greater for gamma-tocopherol than alpha-tocopherol in human hepatic HepG2 cells. This omega carboxylation event and subsequent metabolism of tocopherols to various hydroxychromanols has also been observed for tocotrienols [17]. It is believed that the reason that these metabolites were not discovered by Sontag and Parker [53] or by Birringer et al. [17] is that the omega-oxidation mechanisms described by these scientists were performed on non-modified alpha- and gamma-tocopherol/tocotrienol metabolites. Our results indicate that the omega-oxidation occurs either after gamma-tocopherol/tocotrienol has reacted with free radicals, presumably in colon/ovarian epithelial cells, or simultaneously in colon/ovarian epithelial cells.

[0180] A number of other metabolites that were observed as decreasing in CRC had molecular formulas similar to those putatively identified as gamma-tocopherol or gamma-tocotrienol-related. These metabolites fell into three broad categories based on the number of carbon molecules, specifically whether they had 30, 32, or 36 carbons (FIG. 11). It was subsequently hypothesized that these metabolites are derived from reactions between gamma-tocopherol and peroxy radicals from linolenic, linoleic, and oleic acid lipid residues (described below). These metabolic derivatives of gamma-tocopherol/tocotrienol undergo subsequent omega oxidation via P450 during first pass metabolism in the liver.

[0181] Not wishing to be bound by any particular theory, the present invention discloses a hypothesis (FIG. 36) implicating the role of vitamin E and related metabolites in the establishment and progression of CRC and OC by contemplating that the decreased levels of specific fatty acids, vitamin E isoforms, and related metabolites are not the result of a simple dietary deficiency, but rather an impairment in the colonic epithelial uptake of vitamin E and related molecules. This impairment represents a rate-limiting step for the sufficient provision of antioxidant capacity under normal or elevated oxidative stress loads. In this model, the initiating event for the development of CRC or OC is a lack of vitamin E gamma in colonic epithelial cells. Assuming an equal diet in two individuals, the person with attenuated vitamin E transport into colonic epithelia cells will have elevated free radicals. This then becomes directly proportional to the decreased serum vitamin E metabolites as described in this application. However, the hypothesis also contemplates that the resulting reduced levels of omega-COOH metabolites in the serum will have a negative inhibition effect on the prostaglandin biosynthetic pathway, due to a decreased competitive inhibitory effect on arachidonic acid, as mentioned previously in this application. We hypothesize that the resulting activation of the prostaglandin pathway is implicated in the development of other cancers, particularly ovarian, of epithelial origin. We also contemplate the further activation of the COX pathway in CRC via this mechanism, which may explain the well-established role of non-steroidal anti-inflammatory drugs (NSAIDS) as preventive agents in CRC and other cancers.

[0182] These findings are significant regarding treatment strategies of CRC and OC. In both of these diseases, inflammation is a risk factor. Gamma-tocopherol and gamma-carboxyethyl hydroxychromanol (CEHC) has been shown to decrease arachadonic mediated inflammation. The delay in activity of gamma-tocopherol indicates that gamma-tocopherol may be a precursor to the actual biologically active molecule. The discovery of multiple omega COOH gamma-tocopherol/tocotrienol metabolites suggest that these are endogenous anti-inflammatory agents and that a decrease in these metabolites may result in or be indicative of inflammation associated with CRC and OC.

[0183] Free radicals have long been thought to play a role in the etiology of colon cancer [36],[54], [55]. In this application, we present for the first time an integrated hypothesis that indicates that CRC is associated with chronic hyperoxidative stress and that gamma-tocopherol has unique anti-oxidant properties that are important for maintaining a healthy oxidative state in colon and ovarian epithelial cells. Although [56] mention the anti-oxidant properties of gamma-tocopherol, these properties are assumed to be equivalent to those of alpha-tocopherol. The present invention identifies unique metabolites that indicate that gamma-tocopherol/trienol or related metabolites may have unique lipid radical scavenging mechanisms. The high degree of selectivity of these findings to CRC and OC versus other cancers (Table 13)in combination with previous reports showing a preferential uptake of gamma-tocopherol into colon epithelial cells, higher concentrations of gamma-tocopherol versus alpha-tocopherol in colon epithelial cells, increased bioactivity of trienols versus tocopherols, and an increased turn-over of gamma-tocopherol versus alpha-tocopherolis strong evidence supporting the hypothesis that gamma-tocopherol/trienol-related processes are selectively involved in epithelial cell homeostasis.

[0184] It has been well established that antioxidants are consumed over the course of their function and that this function operates in real time; that is, excess antioxidant capacity on one day does not make up for deficient antioxidant capacity on another day. Apart from relatively minor recycling mechanisms, antioxidants have a limited capacity and shelf life and, once they are used up, oxidation reactions proceed unchecked. For this reason, the selection of antioxidant molecules that are capable of neutralizing multiple free radical molecules would be biologically favored. A mechanism whereby a single gamma-tocopherol/tocotrienol molecule can neutralize up to six free radical molecules is proposed and supported by the analytical data and previous literature surrounding free radical propagation.

[0185] The process of lipid oxidation has been extensively studied. FIG. 30 illustrates the process of auto-oxidation of an unsaturated fatty acid (linolenic acid is used as an example). Briefly, a hydrogen radical is abstracted from a hydrocarbon molecule (FIG. 30A). This abstraction, mediated by light, heat, irradiation, metal ions, or radicals, is heavily favored in unsaturated hydrocarbons versus saturated hydrocarbons. In biological systems the formation of peroxide is the initiating step (FIG. 30A). The peroxide radical can then be either a) stabilized by gamma-tocopherol-hydroxide (FIG. 30B) or b) it can react with a gamma-tocopherol peroxide radical (FIG. 30C), in both cases forming semi-stable peroxides. The two peroxides are then converted to a hydroxide radical through the iron-catalyzed Fenton reaction [36] or in an iron-independent fashion through nitric oxide [57], [58]. Although gamma-tocopherol has been shown to be superior to alpha-tocopherol in detoxifying nitrogen dioxide in vitro [59], the in vivo study of Stone et al [60] clearly demonstrated that in rats fed either a high or low gamma-/alpha-tocopherol ratio diet, ratios of 2:1 and 1:18, respectively, with either the recommended daily amount of iron or an eight-fold enriched diet, the increased iron was observed to significantly decrease gamma-tocopherol levels in colonocytes (32%) and plasma (18%) and alpha-tocopherol levels in colonocytes (22%). The increased iron had no effect on either alpha- or gamma-tocopherol concentrations in either the liver or feces. The iron concentration in the gastrointestinal tract is substantially higher in the colon relative to the small intestine. It has been estimated that iron concentrations in the colon are greater than 10 times those found in other tissues [36]. Therefore, free radical formation in the colon is most likely an iron-catalyzed event.

[0186] The hydroxyl radical abstracts a hydrogen radical to form a stable molecule of water and leaves behind a lipid radical. All tocopherols and tocotrienols can neutralize these hydroxyl radicals, thereby preventing lipid free radical formation. However, once a lipid radical is formed, the activity of an antioxidant is related to its ability to be co-localized with the lipid radical. It has been shown that the vitamin E isoforms contain the optimal phytyl side chain length for incorporation into lipid membranes, making these molecules ideal for scavenging lipid radicals from membranes.

[0187] Lipid free radicals that are not scavenged readily react with oxygen to form a lipid peroxide radical (FIG. 30A). Tocopherols/tocotrienols can donate a hydrogen radical to a lipid peroxide, resulting in the formation of a tocopherol/tocotrienol radical that is stabilized by the chromanin ring structure and a resulting lipid hydroperoxide (FIG. 30B). Under normal conditions, free radical propagation is arrested at this step. The tocopherol/tocotrienol radical is capable of reacting with a second lipid peroxide radical to form a tocopherol/tocotrienol peroxide, which is an even electron molecule (FIG. 30C). Although hydro/alkyl peroxide molecules are not free radicals, the O-O bond is high energy, the breakdown of which is energetically favored (FIG. 30D). The two most potent catalysts known to facilitate the breakdown of hydroperoxides are copper and iron. As has been mentioned previously in this application, the large intestine is a particularly concentrated source of iron. Therefore, these hydroperoxides can be broken down into a hydroxyl radical and a lipid oxide radical, thereby restarting the free radical propagation sequence. Like a free lipid hydroperoxide, the tocopherol/tocotrienol peroxide is presumed to be sensitive to breakdown in the presence of iron or copper.

[0188] The present invention proposes a novel mechanism for the internal degradation of this peroxide into a stable tocopherol/tocotrienol alkyl ether and lipid aldehyde. The proposed reaction creates two thermodynamically stable products. It is proposed that the peroxides formed from three primary unsaturated fatty acid residues present in endogenous lipidslinolenic, linoleic, and oleic acidare neutralized by tocopherols/tocotrienols by this mechanism (FIG. 31A to C). This mechanism appears to be selective for gamma-tocopherol, and is supported by the observation that C30, C32, and C36, byproducts of gamma-tocopherol but not alpha-tocopherol, are formed in humans. There is no such mechanism to create stable products from the degradation of the initial hydroperoxide, generated from the reaction of the neutral tocopherol/tocotrienol degraded in the presence of iron (FIGS. 32A-32B). This reaction creates a hydroxyl radical and a lipid oxide radical, and therefore needs to be neutralized by classical means. The lipid oxide radical can spontaneously degrade to an aldehyde and a radical alkane or alkene (FIG. 33). We propose an additional mechanism whereby tocopherol/tocotrienols can neutralize the resultant free radical alkane. We propose that the unhindered aromatic ring structure of gamma-tocopherol/tocotrienol can accept a hydrogen radical from the radical alkane, resulting in a ring-stabilized tocopherol/tocotrienol radical and a stable alkene (FIG. 34). Through this mechanism gamma-tocopherol/tocotrienol would be capable of neutralizing up to six alkane radicals. This hypothesis is supported by the observation of gamma-tocopherol metabolites, wherein the aromatic ring is reduced to a single double bond. It therefore appears that gamma-tocopherol can accept a maximum of four hydrogen radicals (FIGS. 34A-B). As a result of these two mechanisms, one molecule of gamma-tocopherol/tocotrienol would be capable of neutralizing six free radicals.

[0189] As discussed previously, the gamma-tocopherol-related metabolite that results from these proposed mechanisms undergoes -oxidation via a P450 reaction during first pass metabolism in the liver (FIG. 35).

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[0250] All citations are hereby incorporated by reference.

[0251] The present invention has been described with regard to one or more embodiments. However, it will be apparent to persons skilled in the art that a number of variations and modifications can be made without departing from the scope of the invention.

TABLE-US-00001 TABLE 1 CRC Staging and Survival Statistics STAGE TNM GROUP GROUP DUKE'S Prognosis Stage I T1 N0 M0 Duke's A 5 year survival >90% T2 N0 M0 Stage II T3 N0 M0 Duke's B 5 year survival 70-85% T4 N0 M0 5 year survival 55-65% Stage III any T N1 M0 Duke's C 5 year survival 45-55% any T N2, N3 M0 5 year survival 20-30% Stage IV any T any N M1 (distant) Duke's D 5 year survival <5% T = tumor; N = node involvement; M = metastasis

TABLE-US-00002 TABLE 2 Comparison of current CRC screening tests (modified from Davies et al) Whole Non- Test Sensitivity Specificity Cost Colon invasive advantages disadvantages. Fecal occult Moderate to Moderate Low Yes Yes No bowel preparation, can Repeat samples needed, blood test low be combined with flexible dietary and drug sigmoidoscopy to improve restrictions required detection Digital rectal Low Low Low No No Simple to perform Patient discomfort examination Flexible Moderate to High Moderate No No Allows removal of Patient discomfort, bowel sigmoidoscopy high precancerous lesions prepration needed, risk of bowel perforation and bleeding, trained personnel needed, data from randomized trials still pending Barium enema Moderate Moderate to Moderate Yes No Lower risk of bowel Patient discomfort, bowel high performation than preparation needed, trained endoscopic screening personnel needed Colonoscopy High High High Yes No Allows removal of Patient discomfort, bowel precancerous polyps, preparation needed, risk of evidence of reduced cancer bowel perforation and incidence after polyp bleeding, mortability of 1- removal 3/10000, intravenous sedation required, highly trained personnel needed, no randomized control trials Virtual High High High Yes Yes Speed, no sedation needed, Patient discomfort, bowel Colonoscopy extracolonic and pelvic prepatation required, high organs can be imaged, high radiation dose, trained patient acceptability personnel needed, high inter-observer variability, limited specificity, unknown sensitivity for flat adenomas Cellular Moderate to Moderate to Unknown Yes Yes Single stool sample Research stage of markers high high adequate, no bowel development, assay might preparation required, be time-consuming, lack of specimens transportable, technology for large-scale potential high patient use acceptability DNA markers Moderate to Moderate to Unknown Yes Yes Single stool sample Research stage of low high adequate, no bowel development, time- preparation required, consuming assay, lack of specimens transportable, large-scale technology potential high patient acceptability Serum High High Low Yes Yes Single serum sample Validation trials still in Metabolite required, specimens progress, lack of Panel* transportable, high patient appropriate clinical action acceptability, portability for high-risk individuals and potentially simple not showing detectable integration of assay into adenomas or CRC. conventional clinical chemistry labs, quick turnaround time, very low cost, potential detection of risk prior to full CRC onset *As described in this application

TABLE-US-00003 TABLE 3 Accurate neutral mass features differing between CRC and normal serum (p < 0.05, log2 transformed) AVG AVG Detected Analysis (log2) Std Error (log2) Std Error Log(2) Mass Mode Normal Normal CRC CRC ratio P value 450.3726 1204 2.367 0.145 0.335 0.149 7.072 2.31E24 466.3661 1204 2.338 0.157 0.386 0.136 6.052 8.16E23 499.9401 1202 2.454 0.196 0.254 0.144 9.673 2.16E21 468.384 1204 3.078 0.139 1.062 0.201 2.899 8.85E21 592.4711 1204 2.769 0.159 0.794 0.189 3.487 1.54E19 538.4259 1204 2.843 0.131 1.000 0.199 2.842 3.04E19 502.405 1204 2.060 0.115 0.553 0.171 3.729 6.10E18 594.4851 1204 3.471 0.169 1.406 0.225 2.469 7.92E18 464.3522 1204 2.122 0.142 0.528 0.160 4.019 9.72E18 446.3406 1204 3.044 0.141 1.137 0.226 2.678 1.19E17 594.4876 1202 2.602 0.175 0.814 0.166 3.196 2.89E17 777.5285 1201 3.664 0.087 2.750 0.092 1.332 8.33E17 492.3829 1204 1.937 0.159 0.399 0.141 4.850 1.46E16 504.4189 1204 1.835 0.142 0.424 0.146 4.328 5.17E16 536.4108 1204 2.371 0.119 0.894 0.191 2.652 9.64E16 801.5542 1202 3.194 0.119 2.084 0.108 1.532 1.21E15 795.5182 1101 2.286 0.130 1.025 0.133 2.231 1.89E15 616.4672 1201 1.818 0.169 0.361 0.123 5.036 2.01E15 595.4896 1204 2.249 0.191 0.534 0.162 4.209 2.62E15 783.5777 1101 5.534 0.096 4.543 0.119 1.218 5.59E15 808.5794 1101 4.104 0.077 3.296 0.100 1.245 7.83E15 802.5576 1202 1.954 0.113 0.812 0.140 2.407 1.49E14 576.4766 1202 1.763 0.154 0.428 0.133 4.117 1.55E14 494.3977 1204 2.110 0.168 0.630 0.152 3.348 1.70E14 577.4798 1204 2.055 0.169 0.519 0.167 3.960 1.79E14 580.5092 1204 1.593 0.158 0.277 0.120 5.758 1.81E14 520.3353 1101 1.969 0.103 0.897 0.137 2.195 2.03E14 784.5809 1101 4.467 0.099 3.480 0.122 1.284 2.04E14 520.4144 1204 2.424 0.124 1.065 0.183 2.276 2.49E14 755.5466 1101 2.161 0.115 1.175 0.099 1.838 2.81E14 807.5761 1101 5.086 0.077 4.315 0.098 1.179 4.13E14 829.5604 1101 2.570 0.087 1.559 0.144 1.648 4.96E14 756.5498 1201 2.630 0.095 1.815 0.086 1.449 5.34E14 519.3318 1101 3.772 0.113 2.595 0.157 1.454 5.48E14 448.3563 1204 2.591 0.136 1.218 0.181 2.127 7.47E14 590.4597 1204 1.815 0.155 0.467 0.153 3.883 1.13E13 595.4925 1202 1.382 0.172 0.130 0.083 10.667 1.33E13 755.5463 1201 3.794 0.096 3.047 0.072 1.245 2.47E13 541.3138 1101 3.841 0.114 2.663 0.168 1.442 3.35E13 542.317 1101 2.075 0.127 0.887 0.157 2.338 3.53E13 576.4771 1204 3.435 0.154 1.899 0.218 1.809 5.17E13 579.4963 1204 1.842 0.180 0.437 0.146 4.213 6.58E13 574.463 1202 1.571 0.158 0.302 0.141 5.206 7.17E13 574.4607 1204 2.939 0.144 1.485 0.214 1.979 9.40E13 771.5778 1201 2.571 0.081 1.793 0.111 1.434 1.11E12 779.5445 1101 5.753 0.106 4.896 0.103 1.175 1.68E12 446.3406 1202 1.122 0.151 0.117 0.064 9.622 2.41E12 597.5068 1202 1.653 0.195 0.294 0.114 5.628 2.57E12 780.5475 1101 4.747 0.107 3.896 0.103 1.218 2.96E12 518.3976 1204 1.666 0.184 0.330 0.135 5.050 3.35E12 578.4931 1204 3.080 0.187 1.378 0.248 2.236 4.49E12 592.4701 1202 1.058 0.159 0.048 0.049 21.965 5.41E12 596.5029 1204 4.054 0.227 2.121 0.271 1.911 7.71E12 817.5827 1202 1.929 0.102 1.010 0.136 1.909 8.34E12 821.5337 1201 3.796 0.056 3.240 0.090 1.171 1.27E11 597.5076 1204 2.845 0.225 1.098 0.228 2.592 1.66E11 783.5778 1201 6.912 0.074 6.326 0.079 1.093 1.76E11 854.5885 1202 4.322 0.101 3.409 0.143 1.268 2.42E11 447.3433 1204 1.153 0.166 0.110 0.076 10.525 3.19E11 596.5048 1202 3.032 0.236 1.328 0.208 2.284 3.26E11 593.4742 1204 1.199 0.179 0.081 0.080 14.774 3.39E11 829.5599 1201 5.678 0.059 5.099 0.098 1.114 3.50E11 758.5657 1101 5.811 0.113 4.987 0.103 1.165 3.50E11 757.5627 1101 6.813 0.117 5.975 0.104 1.140 4.68E11 784.5811 1201 5.761 0.070 5.207 0.080 1.106 5.54E11 484.3786 1204 1.065 0.184 0.000 0.000 1.065 5.91E11 830.5883 1202 5.281 0.114 4.428 0.115 1.193 6.19E11 853.5845 1202 5.306 0.107 4.402 0.141 1.205 6.49E11 575.4635 1204 1.675 0.172 0.435 0.162 3.849 8.15E11 512.4086 1204 1.346 0.218 0.063 0.062 21.466 8.16E11 452.3876 1204 0.921 0.152 0.030 0.042 30.716 8.35E11 476.3873 1204 1.353 0.139 0.356 0.130 3.804 9.08E11 786.5965 1101 5.014 0.090 4.330 0.097 1.158 9.66E11 830.5632 1201 4.686 0.057 4.113 0.102 1.139 1.03E10 533.2881 1101 2.090 0.121 1.045 0.172 1.999 1.21E10 785.5932 1101 6.079 0.089 5.404 0.097 1.125 1.28E10 829.5846 1202 6.510 0.132 5.584 0.121 1.166 1.51E10 522.4313 1204 2.524 0.140 1.335 0.195 1.891 1.54E10 540.4404 1202 1.289 0.166 0.245 0.104 5.265 1.87E10 469.3865 1204 1.006 0.169 0.045 0.045 22.354 2.06E10 850.7049 1203 2.885 0.147 1.574 0.226 1.833 2.13E10 449.3614 1204 1.189 0.160 0.211 0.098 5.629 4.32E10 540.4397 1204 2.096 0.216 0.710 0.169 2.951 5.41E10 596.4796 1203 3.393 0.157 2.200 0.193 1.542 6.64E10 618.4831 1201 1.939 0.207 0.629 0.159 3.083 7.03E10 312.0014 1101 1.381 0.211 2.718 0.164 0.508 7.54E10 440.3529 1204 1.169 0.173 0.166 0.094 7.058 1.08E09 467.3718 1204 0.950 0.163 0.067 0.054 14.116 1.59E09 822.537 1201 2.677 0.069 2.133 0.096 1.255 1.72E09 578.4903 1202 1.141 0.171 0.182 0.088 6.270 2.17E09 339.9965 1101 2.070 0.228 3.376 0.133 0.613 2.35E09 558.4665 1202 2.384 0.145 1.060 0.264 2.250 3.15E09 382.1081 1101 0.233 0.094 1.105 0.176 0.211 3.79E09 599.5006 1203 5.116 0.137 4.193 0.150 1.220 5.59E09 803.5446 1101 4.329 0.111 3.539 0.139 1.223 6.60E09 831.5762 1101 3.397 0.080 2.792 0.112 1.217 6.92E09 804.5477 1101 3.349 0.114 2.551 0.141 1.313 9.08E09 598.4963 1203 6.342 0.142 5.413 0.153 1.172 1.03E08 797.5338 1201 3.695 0.071 4.125 0.065 0.896 1.36E08 416.3666 1204 0.987 0.175 0.079 0.080 12.444 1.39E08 826.5569 1202 2.314 0.139 1.360 0.173 1.702 1.64E08 761.5844 1201 3.463 0.078 3.926 0.073 0.882 2.56E08 879.7421 1203 4.626 0.167 3.620 0.167 1.278 3.85E08 597.4839 1203 2.015 0.179 0.922 0.185 2.186 4.01E08 878.7384 1203 5.443 0.166 4.437 0.169 1.227 4.16E08 851.7098 1203 2.239 0.170 1.100 0.215 2.035 4.28E08 519.332 1201 2.979 0.072 2.485 0.096 1.199 4.91E08 868.7532 1203 2.234 0.153 1.193 0.203 1.873 5.20E08 810.5967 1101 4.041 0.081 3.445 0.124 1.173 5.66E08 824.6891 1203 2.054 0.201 0.854 0.205 2.405 6.37E08 809.5934 1101 5.021 0.083 4.443 0.118 1.130 7.39E08 853.7241 1203 4.663 0.150 3.698 0.183 1.261 7.75E08 852.7206 1203 5.373 0.149 4.411 0.184 1.218 7.85E08 798.537 1201 2.627 0.067 3.017 0.066 0.871 8.85E08 496.4164 1204 2.089 0.186 1.019 0.179 2.050 9.50E08 858.6852 1202 2.103 0.096 2.673 0.101 0.787 1.12E07 558.4659 1204 4.053 0.131 3.023 0.235 1.341 1.50E07 563.595 1102 0.875 0.130 1.657 0.147 0.528 1.67E07 832.5797 1101 2.426 0.082 1.855 0.123 1.308 1.89E07 795.5179 1201 5.214 0.062 4.861 0.063 1.073 2.02E07 782.5653 1101 5.050 0.102 4.437 0.118 1.138 2.09E07 760.5811 1201 5.562 0.082 6.013 0.077 0.925 2.10E07 559.4695 1204 2.709 0.123 1.698 0.240 1.596 2.11E07 779.5439 1201 8.173 0.068 7.796 0.065 1.048 2.17E07 560.4796 1203 3.168 0.104 2.532 0.126 1.251 2.63E07 877.7266 1203 2.795 0.194 1.591 0.244 1.756 2.74E07 825.5533 1202 3.304 0.152 2.461 0.153 1.343 3.25E07 183.066 1101 3.212 0.092 2.455 0.185 1.308 3.33E07 758.5654 1201 7.099 0.085 6.647 0.077 1.068 3.36E07 290.0628 1101 1.143 0.256 0.032 0.045 36.180 3.39E07 541.3139 1201 2.953 0.076 2.495 0.094 1.184 4.09E07 565.3391 1202 7.189 0.115 6.499 0.139 1.106 4.17E07 796.5213 1201 4.064 0.062 3.723 0.063 1.091 4.87E07 440.2897 1201 0.000 0.000 0.776 0.226 0.000 5.04E07 845.5341 1201 2.938 0.063 2.518 0.095 1.167 5.07E07 781.5619 1101 6.005 0.103 5.417 0.116 1.109 5.33E07 847.5937 1202 1.831 0.157 0.979 0.157 1.869 5.47E07 422.3404 1204 0.642 0.144 0.025 0.036 25.237 5.47E07 495.4022 1204 0.753 0.166 0.042 0.041 18.100 5.47E07 202.0453 1101 3.261 0.222 4.340 0.158 0.751 5.70E07 803.5676 1202 8.206 0.144 7.440 0.137 1.103 5.76E07 804.5711 1202 6.699 0.135 6.008 0.118 1.115 6.58E07 544.4483 1203 2.547 0.142 1.728 0.168 1.474 7.19E07 561.5983 1102 1.422 0.132 2.159 0.145 0.658 7.20E07 560.4831 1204 3.752 0.107 2.718 0.276 1.380 7.41E07 648.3846 1101 0.378 0.102 1.014 0.141 0.372 7.73E07 218.0369 1102 1.332 0.196 2.429 0.221 0.548 8.72E07 827.7087 1203 3.409 0.166 2.410 0.217 1.415 9.04E07 807.5759 1201 7.358 0.050 7.060 0.065 1.042 9.23E07 826.7047 1203 4.145 0.171 3.170 0.203 1.307 9.68E07 757.5619 1201 8.087 0.100 7.586 0.085 1.066 9.71E07 566.3433 1202 5.332 0.101 4.739 0.127 1.125 9.98E07 805.5616 1101 4.724 0.081 4.184 0.128 1.129 1.03E06 586.4957 1203 2.208 0.109 1.500 0.165 1.471 1.03E06 244.056 1101 1.789 0.174 2.644 0.143 0.677 1.16E06 276.2093 1204 3.348 0.103 2.797 0.109 1.197 1.29E06 428.3651 1201 3.186 0.070 2.766 0.095 1.152 1.33E06 744.496 1204 3.432 0.077 2.882 0.139 1.191 1.43E06 541.4432 1204 0.842 0.183 0.079 0.064 10.679 1.59E06 823.5494 1201 3.978 0.068 3.612 0.075 1.101 1.68E06 673.6198 1204 3.299 0.093 3.737 0.072 0.883 1.82E06 798.6741 1203 1.579 0.205 0.598 0.171 2.641 2.06E06 521.3476 1101 3.429 0.100 2.753 0.170 1.246 2.07E06 543.3292 1101 3.593 0.101 2.921 0.168 1.230 2.09E06 780.5473 1201 7.108 0.059 6.801 0.062 1.045 2.15E06 743.5483 1204 3.857 0.086 3.407 0.092 1.132 2.20E06 429.3743 1204 2.242 0.123 1.618 0.122 1.386 2.27E06 560.4816 1202 1.965 0.128 1.002 0.257 1.962 2.46E06 744.5537 1204 2.960 0.084 2.515 0.094 1.177 2.71E06 561.4869 1204 2.350 0.125 1.372 0.267 1.713 2.92E06 763.5146 1201 1.401 0.131 2.052 0.128 0.683 3.11E06 555.3103 1102 1.936 0.126 1.230 0.162 1.574 3.19E06 260.2136 1203 1.742 0.129 1.080 0.139 1.614 3.40E06 876.7228 1203 3.508 0.201 2.521 0.193 1.391 3.42E06 524.3666 1101 1.671 0.122 0.952 0.173 1.756 3.43E06 268.132 1204 0.908 0.144 0.260 0.108 3.497 3.98E06 661.6227 1204 3.016 0.105 2.518 0.095 1.198 4.47E06 727.5563 1204 2.134 0.134 1.335 0.197 1.598 4.49E06 648.5862 1203 4.067 0.086 3.589 0.113 1.133 4.80E06 758.5096 1204 2.677 0.091 2.168 0.121 1.235 4.82E06 808.5793 1201 6.244 0.044 5.985 0.064 1.043 5.15E06 827.5684 1202 7.255 0.139 6.530 0.166 1.111 6.33E06 828.5726 1202 6.015 0.126 5.362 0.148 1.122 6.54E06 570.4649 1203 2.474 0.125 1.717 0.196 1.440 6.59E06 562.4993 1204 2.569 0.118 1.839 0.192 1.397 7.02E06 392.2932 1204 2.106 0.201 0.988 0.275 2.132 7.35E06 688.4688 1204 3.330 0.077 2.947 0.086 1.130 8.09E06 264.2453 1203 2.851 0.098 3.278 0.076 0.870 8.41E06 559.4698 1202 1.156 0.147 0.399 0.178 2.901 9.51E06 743.5463 1201 2.075 0.091 1.610 0.109 1.289 9.72E06 806.5648 1101 3.768 0.084 3.275 0.130 1.151 1.05E05 565.3398 1102 3.209 0.122 2.559 0.161 1.254 1.11E05 545.3451 1101 3.523 0.117 2.811 0.193 1.253 1.13E05 630.4874 1204 3.273 0.195 2.306 0.224 1.420 1.14E05 523.3633 1101 3.385 0.107 2.713 0.186 1.248 1.23E05 310.2881 1204 2.825 0.124 3.408 0.127 0.829 1.27E05 832.6026 1202 5.437 0.119 4.898 0.111 1.110 1.33E05 880.7535 1203 6.327 0.159 5.592 0.157 1.131 1.34E05 426.3714 1204 0.671 0.138 0.125 0.079 5.380 1.38E05 216.0399 1102 2.911 0.205 3.930 0.242 0.741 1.41E05 793.5987 1101 2.239 0.084 1.808 0.106 1.238 1.45E05 638.4885 1201 1.839 0.165 1.096 0.160 1.678 1.80E05 222.0699 1202 2.486 0.203 1.492 0.239 1.666 1.82E05 257.8107 1101 2.777 0.068 3.098 0.075 0.897 1.95E05 881.7573 1203 5.629 0.157 4.925 0.153 1.143 1.96E05 749.541 1204 2.884 0.097 2.271 0.178 1.270 1.99E05 831.5991 1202 6.714 0.146 6.084 0.128 1.104 2.03E05 805.5832 1102 2.664 0.094 3.152 0.126 0.845 2.06E05 550.4605 1204 1.671 0.170 0.881 0.182 1.897 2.10E05 759.5777 1201 6.723 0.089 7.100 0.074 0.947 2.22E05 802.5317 1201 2.811 0.137 2.206 0.132 1.274 2.39E05 253.8165 1101 3.252 0.073 3.571 0.068 0.911 2.41E05 692.5571 1204 2.642 0.103 3.179 0.144 0.831 2.76E05 606.415 1202 0.784 0.212 0.044 0.043 17.964 2.84E05 801.5283 1201 3.911 0.133 3.339 0.122 1.172 2.85E05 649.5893 1203 3.030 0.096 2.517 0.141 1.204 2.93E05 430.3817 1204 4.158 0.157 3.535 0.113 1.176 3.22E05 546.3482 1101 1.930 0.121 1.292 0.176 1.494 3.51E05 738.5445 1102 1.368 0.100 1.857 0.127 0.737 3.54E05 188.0491 1102 1.405 0.256 0.448 0.145 3.134 3.68E05 336.2664 1203 3.612 0.099 3.191 0.091 1.132 3.72E05 553.3853 1201 0.133 0.067 0.907 0.268 0.146 3.76E05 263.8453 1101 2.545 0.083 2.912 0.087 0.874 4.05E05 255.8136 1101 3.727 0.071 4.031 0.069 0.925 4.14E05 731.491 1204 3.147 0.123 2.568 0.148 1.225 4.16E05 855.7394 1203 6.558 0.154 5.877 0.161 1.116 4.23E05 824.5528 1201 2.869 0.069 2.566 0.071 1.118 4.35E05 772.5279 1204 2.216 0.107 1.624 0.172 1.364 4.42E05 785.5933 1201 7.132 0.070 6.820 0.075 1.046 4.47E05 278.2251 1204 5.577 0.108 5.109 0.109 1.091 4.78E05 566.4556 1204 0.666 0.155 0.110 0.076 6.046 5.03E05 759.5154 1204 2.271 0.119 1.671 0.167 1.359 5.36E05 854.7356 1203 7.289 0.158 6.609 0.162 1.103 5.37E05 763.5147 1202 1.289 0.148 1.919 0.147 0.672 5.37E05 812.6124 1101 2.277 0.089 1.827 0.126 1.246 5.55E05 495.3318 1101 5.159 0.100 4.604 0.166 1.121 5.75E05 249.9647 1101 2.274 0.161 1.511 0.204 1.505 5.79E05 568.3559 1201 0.018 0.025 0.535 0.191 0.034 6.01E05 799.6776 1203 0.955 0.193 0.251 0.118 3.804 6.53E05 563.396 1204 0.996 0.197 0.259 0.135 3.845 6.61E05 748.572 1102 2.381 0.107 2.886 0.138 0.825 6.91E05 518.3171 1101 3.505 0.112 2.935 0.165 1.194 6.94E05 279.2286 1204 3.300 0.109 2.824 0.120 1.168 7.10E05 517.3137 1101 5.483 0.113 4.913 0.165 1.116 7.11E05 496.3352 1101 3.327 0.108 2.766 0.165 1.203 7.26E05 431.3856 1204 2.686 0.149 2.064 0.149 1.302 7.78E05 328.2412 1204 3.467 0.149 4.078 0.143 0.850 7.97E05 408.2547 1201 0.447 0.130 1.096 0.190 0.408 8.53E05 631.491 1204 2.071 0.211 1.175 0.224 1.762 8.68E05 283.26 1204 7.010 0.124 7.515 0.120 0.933 9.26E05 277.886 1101 3.032 0.058 3.288 0.068 0.922 9.60E05 274.1936 1204 1.684 0.110 1.169 0.146 1.441 9.97E05 536.4799 1203 2.866 0.226 1.889 0.256 1.517 1.02E04 452.2381 1201 2.521 0.064 2.273 0.055 1.109 1.04E04 788.6128 1201 2.826 0.070 3.175 0.105 0.890 1.06E04 767.583 1101 2.301 0.088 1.881 0.122 1.223 1.08E04 855.6004 1202 6.120 0.134 5.526 0.161 1.107 1.10E04 282.257 1204 9.595 0.130 10.114 0.124 0.949 1.12E04 542.47 1203 1.218 0.174 0.532 0.162 2.291 1.21E04 856.6045 1202 5.073 0.122 4.531 0.149 1.119 1.21E04 771.5806 1204 2.315 0.089 1.836 0.153 1.261 1.24E04 494.434 1203 2.948 0.346 1.559 0.339 1.891 1.24E04 786.5967 1201 6.015 0.065 5.735 0.075 1.049 1.30E04 568.4729 1204 1.088 0.191 0.398 0.137 2.733 1.35E04 855.5756 1201 3.881 0.094 4.328 0.134 0.897 1.38E04 859.7708 1203 5.116 0.170 5.728 0.122 0.893 1.40E04 519.4376 1203 0.921 0.221 0.179 0.112 5.145 1.44E04 326.2197 1201 2.476 0.355 3.915 0.368 0.633 1.47E04 338.2823 1203 4.938 0.078 5.268 0.090 0.937 1.51E04 694.573 1204 1.900 0.163 2.530 0.151 0.751 1.56E04 352.2296 1201 0.691 0.197 1.581 0.260 0.437 1.61E04 259.9417 1101 2.617 0.136 1.986 0.191 1.318 1.81E04 749.5757 1102 1.277 0.136 1.823 0.144 0.700 1.86E04 226.0687 1102 1.303 0.192 2.053 0.194 0.635 2.18E04 748.5726 1202 3.195 0.104 3.585 0.095 0.891 2.19E04 217.9126 1101 2.667 0.133 3.135 0.098 0.851 2.24E04 745.4986 1204 2.011 0.166 1.294 0.212 1.555 2.36E04 495.4373 1203 1.699 0.297 0.620 0.254 2.738 2.54E04 215.9154 1101 4.225 0.094 4.601 0.103 0.918 2.55E04 843.518 1201 3.089 0.094 3.477 0.111 0.889 2.62E04 194.0802 1203 0.635 0.201 0.029 0.041 21.815 2.66E04 285.1365 1201 1.200 0.277 0.260 0.189 4.614 2.72E04 552.3819 1201 0.921 0.175 1.952 0.372 0.472 2.95E04 750.5441 1204 1.757 0.149 1.130 0.188 1.555 2.98E04 329.2441 1204 1.195 0.176 1.860 0.174 0.642 2.99E04 803.5441 1201 7.309 0.075 6.986 0.100 1.046 3.13E04 829.586 1102 2.482 0.112 1.983 0.158 1.251 3.21E04 870.7694 1203 2.133 0.152 1.468 0.208 1.453 3.23E04 530.3997 1201 0.063 0.043 0.568 0.208 0.111 3.72E04 819.5628 1202 1.666 0.185 0.998 0.174 1.670 4.06E04 691.1955 1102 1.840 0.082 2.128 0.071 0.865 4.06E04 853.5599 1201 2.536 0.090 2.159 0.117 1.174 4.08E04 466.4018 1203 1.299 0.308 0.270 0.225 4.807 4.09E04 856.5788 1201 2.843 0.108 3.299 0.145 0.862 4.29E04 625.5165 1203 2.293 0.074 1.852 0.168 1.238 4.58E04 751.5554 1204 3.149 0.107 2.612 0.193 1.206 4.98E04 537.4829 1203 1.394 0.228 0.591 0.219 2.360 6.17E04 469.3608 1201 2.840 0.087 2.517 0.096 1.128 6.56E04 750.5397 1202 1.844 0.076 1.385 0.182 1.331 6.92E04 217.0698 1202 0.000 0.000 0.533 0.239 0.000 6.92E04 805.5605 1201 7.202 0.053 6.978 0.076 1.032 7.15E04 724.5494 1201 2.164 0.152 2.644 0.108 0.818 7.29E04 752.5577 1204 2.057 0.132 1.473 0.208 1.397 7.56E04 642.5195 1201 2.218 0.124 2.644 0.118 0.839 7.85E04 205.8866 1101 2.131 0.163 2.642 0.119 0.807 8.48E04 328.2604 1202 2.681 0.229 3.545 0.276 0.756 8.54E04 577.5142 1203 8.031 0.134 8.453 0.102 0.950 9.73E04 693.56 1204 1.549 0.169 2.151 0.184 0.720 1.01E03 310.2152 1204 2.713 0.091 2.415 0.081 1.123 1.02E03 518.4343 1203 2.231 0.268 1.384 0.216 1.612 1.07E03 566.3437 1102 1.489 0.141 0.990 0.155 1.503 1.09E03 689.6527 1204 2.424 0.124 2.039 0.096 1.189 1.11E03 804.5474 1201 6.295 0.071 6.015 0.097 1.047 1.12E03 576.5109 1203 9.389 0.132 9.799 0.102 0.958 1.13E03 440.2713 1201 0.264 0.095 0.737 0.188 0.358 1.16E03 449.3171 1204 0.922 0.216 0.281 0.143 3.285 1.24E03 459.1582 1203 1.001 0.232 1.912 0.321 0.524 1.26E03 874.7062 1203 0.890 0.194 0.308 0.135 2.887 1.26E03 281.2447 1204 6.344 0.106 5.984 0.111 1.060 1.32E03 329.264 1202 0.790 0.183 1.472 0.232 0.537 1.35E03 537.4501 1204 2.198 0.165 1.531 0.246 1.435 1.43E03 280.2412 1204 8.699 0.109 8.331 0.114 1.044 1.46E03 825.6926 1203 1.229 0.204 0.595 0.171 2.066 1.46E03 804.5717 1102 2.955 0.096 2.601 0.121 1.136 1.47E03 588.5115 1203 3.617 0.089 3.315 0.096 1.091 1.52E03 602.5286 1203 8.518 0.111 8.889 0.115 0.958 1.53E03 444.3599 1201 1.999 0.068 1.694 0.121 1.181 1.54E03 218.0193 1101 2.686 0.184 3.262 0.161 0.823 1.56E03 283.9863 1101 0.029 0.040 0.430 0.187 0.066 1.58E03 858.766 1203 6.089 0.172 6.596 0.123 0.923 1.59E03 860.7756 1203 3.656 0.189 4.201 0.124 0.870 1.60E03 859.7718 1204 1.061 0.195 1.700 0.198 0.624 1.74E03 614.3424 1202 2.236 0.096 2.558 0.104 0.874 1.75E03 877.5815 1202 1.648 0.158 1.125 0.165 1.465 1.76E03 468.3574 1201 4.315 0.083 4.044 0.085 1.067 1.79E03 461.1552 1203 0.756 0.215 1.596 0.316 0.474 1.87E03 578.5176 1203 5.603 0.257 6.290 0.120 0.891 1.91E03 712.4704 1204 1.935 0.131 1.470 0.163 1.316 1.95E03 326.2261 1204 1.887 0.172 2.476 0.201 0.762 2.08E03 749.5359 1202 2.784 0.085 2.366 0.179 1.176 2.13E03 858.7678 1204 1.862 0.219 2.525 0.192 0.737 2.21E03 221.0733 1202 0.635 0.176 0.158 0.100 4.014 2.25E03 523.4675 1203 3.901 0.258 3.075 0.264 1.269 2.25E03 603.532 1203 7.217 0.111 7.576 0.117 0.953 2.27E03 626.5286 1203 3.408 0.067 3.168 0.087 1.076 2.33E03 269.9705 1101 3.238 0.143 2.783 0.145 1.164 2.33E03 589.3396 1202 6.112 0.115 5.739 0.122 1.065 2.34E03 564.513 1203 3.173 0.185 2.575 0.196 1.232 2.34E03 460.1603 1203 0.298 0.129 0.843 0.223 0.354 2.39E03 304.2379 1201 2.272 0.224 3.075 0.296 0.739 2.44E03 834.5961 1201 3.998 0.067 4.255 0.100 0.940 2.45E03 690.4865 1204 2.157 0.158 2.587 0.097 0.834 2.49E03 749.5767 1202 2.180 0.106 2.504 0.100 0.870 2.55E03 854.7373 1204 1.519 0.199 0.909 0.190 1.671 2.66E03 830.589 1102 1.478 0.127 1.069 0.137 1.382 2.73E03 558.4093 1204 1.158 0.209 1.868 0.255 0.620 2.76E03 339.285 1203 2.667 0.112 2.983 0.087 0.894 2.94E03 534.4658 1203 1.939 0.173 1.342 0.221 1.445 2.97E03 183.066 1201 4.591 0.102 4.277 0.102 1.073 3.05E03 575.2726 1101 2.063 0.102 1.683 0.151 1.226 3.14E03 342.2198 1204 0.668 0.156 1.178 0.183 0.567 3.28E03 282.2555 1202 2.757 0.245 3.580 0.304 0.770 3.29E03 262.2294 1203 3.003 0.113 2.708 0.066 1.109 3.30E03 819.5179 1201 4.478 0.065 4.242 0.093 1.056 3.31E03 588.3273 1202 0.618 0.135 0.251 0.093 2.458 3.31E03 842.7386 1203 1.913 0.190 1.345 0.182 1.422 3.38E03 292.204 1204 2.164 0.112 1.822 0.114 1.187 3.43E03 820.5213 1201 3.401 0.067 3.161 0.094 1.076 3.46E03 743.5455 1202 2.517 0.134 2.144 0.105 1.174 3.48E03 587.3228 1202 1.766 0.180 1.239 0.167 1.426 3.58E03 522.4639 1203 5.433 0.268 4.629 0.265 1.174 3.61E03 102.0621 1204 2.296 0.108 1.948 0.128 1.179 3.84E03 590.3426 1202 4.115 0.104 3.793 0.115 1.085 4.09E03 915.5193 1201 3.194 0.058 3.020 0.061 1.058 4.38E03 613.3402 1202 3.884 0.108 4.220 0.123 0.920 4.48E03 617.0614 1204 4.859 0.065 4.651 0.080 1.045 4.87E03 557.4528 1204 1.201 0.131 0.740 0.193 1.622 4.91E03 789.5649 1201 3.490 0.063 3.690 0.077 0.946 4.93E03 658.5913 1203 0.314 0.127 0.022 0.031 14.101 5.13E03 746.5139 1204 1.980 0.178 2.454 0.143 0.807 5.43E03 624.513 1203 3.469 0.078 3.208 0.108 1.081 5.56E03 283.2589 1202 0.856 0.181 1.443 0.237 0.593 5.65E03 589.5159 1203 2.441 0.093 2.154 0.110 1.133 5.68E03 723.5217 1204 2.597 0.106 2.121 0.230 1.224 5.77E03 556.4496 1204 2.541 0.091 2.166 0.178 1.173 6.26E03 817.5011 1201 1.369 0.130 1.027 0.106 1.333 6.32E03 803.5692 1102 4.118 0.106 3.792 0.129 1.086 6.40E03 831.7406 1203 3.546 0.181 4.021 0.149 0.882 6.47E03 493.422 1203 0.710 0.197 0.203 0.151 3.495 6.53E03 833.5927 1201 4.967 0.066 5.190 0.096 0.957 6.58E03 591.532 1203 2.662 0.116 2.334 0.118 1.141 6.66E03 328.2391 1202 1.395 0.197 2.013 0.251 0.693 6.68E03 296.2359 1204 4.596 0.125 4.259 0.115 1.079 6.95E03 233.0648 1202 0.000 0.000 0.299 0.171 0.000 7.11E03 223.9491 1101 2.665 0.135 3.041 0.137 0.876 7.48E03 519.5021 1203 2.640 0.117 2.989 0.140 0.883 7.72E03 350.2828 1204 1.458 0.166 1.008 0.161 1.447 7.87E03 806.5641 1201 6.132 0.050 5.971 0.072 1.027 8.56E03 623.5006 1203 1.607 0.141 1.167 0.191 1.377 8.77E03 492.4181 1203 1.564 0.279 0.851 0.249 1.837 9.77E03 564.5127 1202 0.208 0.096 0.576 0.186 0.361 9.98E03 768.4964 1204 2.254 0.119 1.921 0.135 1.173 1.02E02 807.5893 1202 2.736 0.126 3.050 0.106 0.897 1.03E02 635.34 1202 0.641 0.142 1.098 0.212 0.584 1.05E02 521.4526 1203 2.899 0.236 2.219 0.289 1.307 1.06E02 600.5128 1203 8.293 0.117 7.966 0.135 1.041 1.08E02 524.472 1203 1.524 0.269 0.839 0.249 1.817 1.08E02 767.5501 1204 3.193 0.090 2.957 0.089 1.080 1.09E02 844.5214 1201 2.139 0.090 2.427 0.136 0.881 1.15E02 520.4497 1203 4.589 0.221 3.985 0.248 1.152 1.16E02 695.646 1204 0.570 0.185 0.158 0.109 3.618 1.19E02 449.3152 1202 1.438 0.249 0.851 0.189 1.689 1.21E02 490.4024 1203 1.084 0.191 0.619 0.162 1.750 1.22E02 559.4131 1204 0.163 0.084 0.536 0.205 0.304 1.23E02 307.1185 1201 0.882 0.253 0.293 0.189 3.012 1.25E02 739.5157 1202 1.103 0.162 1.482 0.121 0.745 1.26E02 806.5863 1202 4.868 0.111 5.155 0.114 0.944 1.29E02 830.7368 1203 4.321 0.188 4.767 0.151 0.907 1.32E02 833.7567 1203 2.625 0.240 3.151 0.142 0.833 1.34E02 601.5163 1203 7.045 0.117 6.727 0.136 1.047 1.37E02 508.4487 1203 0.723 0.200 0.240 0.178 3.014 1.45E02 224.1416 1204 1.978 0.145 1.617 0.142 1.223 1.49E02 565.5157 1203 1.644 0.229 1.074 0.225 1.530 1.49E02 832.7528 1203 3.413 0.248 3.948 0.147 0.865 1.50E02 356.2929 1204 0.288 0.139 0.016 0.023 17.586 1.52E02 793.5383 1102 2.428 0.098 2.150 0.129 1.129 1.54E02 592.5453 1203 0.774 0.183 0.345 0.155 2.243 1.55E02 828.5475 1201 4.737 0.094 5.011 0.132 0.945 1.61E02 939.5193 1201 2.282 0.092 2.002 0.140 1.140 1.64E02 471.2953 1201 0.759 0.197 0.328 0.136 2.317 1.68E02 858.6202 1202 2.937 0.128 2.598 0.152 1.131 1.68E02 647.6057 1204 2.830 0.099 2.610 0.074 1.084 1.75E02 273.9573 1101 0.000 0.000 0.230 0.150 0.000 1.79E02 703.5709 1101 2.890 0.063 2.695 0.101 1.073 1.82E02 573.485 1203 4.750 0.113 4.450 0.139 1.067 1.85E02 300.2098 1204 2.097 0.103 1.828 0.123 1.147 1.88E02 805.5828 1202 6.134 0.120 6.429 0.127 0.954 1.99E02 607.5616 1203 0.757 0.254 0.226 0.163 3.349 2.01E02 632.5761 1203 1.009 0.202 0.556 0.170 1.815 2.04E02 294.2205 1204 4.901 0.151 4.551 0.146 1.077 2.23E02 716.4988 1204 2.371 0.109 2.106 0.119 1.126 2.25E02 677.5763 1203 1.718 0.148 1.349 0.171 1.274 2.26E02 572.4813 1203 6.067 0.112 5.782 0.136 1.049 2.28E02 745.5663 1204 2.558 0.108 2.787 0.084 0.918 2.47E02 732.4923 1204 1.802 0.165 1.430 0.163 1.260 2.71E02 874.8477 1102 0.276 0.120 0.055 0.045 4.969 2.73E02 464.3874 1203 0.584 0.183 0.205 0.140 2.847 2.74E02 882.7684 1203 6.327 0.155 5.988 0.142 1.057 2.74E02 569.3684 1102 2.360 0.124 2.045 0.160 1.154 2.81E02 615.354 1202 2.392 0.101 2.153 0.115 1.111 2.84E02 831.5536 1201 2.439 0.366 1.588 0.398 1.536 2.88E02 297.2386 1204 2.034 0.141 1.724 0.136 1.180 2.98E02 751.5514 1201 1.722 0.114 1.381 0.199 1.247 3.03E02 308.2717 1204 2.288 0.128 2.557 0.112 0.895 3.09E02 883.7727 1203 5.568 0.148 5.248 0.140 1.061 3.11E02 827.5442 1201 5.719 0.093 5.963 0.132 0.959 3.12E02 768.5545 1204 2.082 0.117 1.786 0.157 1.166 3.15E02 832.6028 1102 1.971 0.109 1.695 0.147 1.163 3.15E02 609.3247 1202 1.229 0.162 1.636 0.214 0.751 3.16E02 660.6083 1203 0.312 0.152 0.045 0.044 7.005 3.17E02 832.5788 1201 5.331 0.059 5.167 0.093 1.032 3.26E02 303.2293 1204 1.818 0.124 1.529 0.146 1.189 3.44E02 827.545 1101 2.585 0.105 2.320 0.145 1.114 3.49E02 616.504 1201 2.171 0.146 2.461 0.114 0.882 3.49E02 615.1693 1201 1.416 0.225 0.895 0.264 1.583 3.50E02 749.5358 1201 1.926 0.090 1.648 0.172 1.169 3.52E02 602.472 1204 2.476 0.080 2.206 0.173 1.122 3.58E02 295.2286 1204 3.056 0.165 2.723 0.142 1.123 3.75E02 244.2189 1203 3.033 0.067 2.898 0.058 1.047 3.80E02 622.4973 1203 2.765 0.120 2.463 0.173 1.123 3.96E02 252.0763 1201 0.462 0.253 0.041 0.058 11.223 4.01E02 195.0535 1202 0.293 0.181 0.000 0.000 0.293 4.16E02 467.4052 1203 0.500 0.188 0.148 0.136 3.385 4.17E02 293.0679 1202 0.000 0.000 0.207 0.158 0.000 4.32E02 847.5498 1201 3.490 0.057 3.344 0.088 1.044 4.48E02 592.3569 1202 2.197 0.103 1.946 0.151 1.129 4.84E02 670.57 1204 2.170 0.133 1.827 0.214 1.188 4.85E02 447.3848 1204 0.952 0.193 0.578 0.173 1.649 4.85E02 361.1439 1101 0.056 0.056 0.367 0.235 0.152 4.92E02 732.5496 1201 1.909 0.155 2.217 0.150 0.861 4.98E02 732.5496 1201 2.160 0.143 1.910 0.169 1.131 0.0498

TABLE-US-00004 TABLE 4 Retention Times of Seven CRC Biomarkers FT Accurate Theoretical Neutral Q- Q Star- Retention Mass Formula Mass Star Mass Detected Mass Time (min) 446.3406 C28H46O4 446.3406 446.40132 445.3935 16.5 450.3726 C28H50O4 450.3726 450.43052 449.4227 16.8 466.3661 C28H50O5 466.36581 466.42027 465.41245 16.5 468.384 C28H52O5 468.38145 468.42562 467.4178 16.5 538.4259 C32H58O6 538.42332 538.423335 537.415515 16.4 592.4711 C36H64O6 592.47026 592.521895 591.514075 16.5 594.4851 C36H66O6 594.48591 594.54482 593.537 16.8

TABLE-US-00005 TABLE 5 Structural assignments for the key MS/MS fragments for Biomarker 3, C.sub.28H.sub.48O.sub.4, (448.3726, neutral mass) m/z Formula Molecular fragment Fragment loss (a) 447 C.sub.28H.sub.47O.sub.4 [00001] H.sup.+ (b) 429 C.sub.28H.sub.45O.sub.3 [00002] H.sub.2O (c) 403 C.sub.27H.sub.47O.sub.2 [00003] CO.sub.2 (d) 385 C.sub.27H.sub.45O [00004] (CO.sub.2 + H.sub.2O) (e) 279 C.sub.18H.sub.31O.sub.2 [00005] Ring opening of (d) at C9-O1 -[00006]

TABLE-US-00006 TABLE 6 Structural assignments for the key MS/MS fragments for Biomarker 4, C.sub.28H.sub.48O.sub.5, (464.3522, neutral mass). m/z Formula Molecular fragment Fragment loss (a) 463 C.sub.28H.sub.47O.sub.5 [00007] H.sup.+ (b) 445 C.sub.28H.sub.45O.sub.4 [00008] H.sub.2O (c) 419 C.sub.27H.sub.47O.sub.3 [00009] CO.sub.2 (d) 401 C.sub.27H.sub.45O.sub.2 [00010] (CO.sub.2 + H.sub.2O) (e) 383 C.sub.27H.sub.43O [00011] (CO.sub.2 + 2H.sub.2O) (f) 315 C.sub.22H.sub.35O [00012] Ring opening at C9-O1 -[00013] (g) 297 C.sub.22H.sub.33 [00014] FH.sub.2O (h) 241 C.sub.14H.sub.25O.sub.3 [00015] [00016]

TABLE-US-00007 TABLE 7 Structural assignments for the key MS/MS fragments for Biomarker 5, C.sub.28H.sub.46O.sub.4, (446.3522, neutral mass) m/z Formula Molecular fragment Fragment loss (a) 445 C.sub.28H.sub.45O.sub.4 [00017] H.sup.+ (b) 427 C.sub.28H.sub.43O.sub.3 [00018] H.sub.2O (c) 401 C.sub.27H.sub.45O.sub.2 [00019] CO.sub.2 (d) 383 C.sub.27H.sub.43O [00020] (CO.sub.2 + H.sub.2O) (e) 223 C.sub.14H.sub.23O.sub.2 [00021] (b) -[00022] (f) 205 C.sub.14H.sub.21O [00023] [00024] (g) 177 C.sub.12H.sub.17O [00025] (f) - C.sub.2H.sub.8 (h) 162 C.sub.11H.sub.114O [00026] g - CH.sub.3

TABLE-US-00008 TABLE 8 Structural assignments for the key MS/MS fragments for Biomarker 6, C.sub.28H.sub.50O.sub.5, (466.3661, neutral mass) m/z Formula Molecular fragment Fragment loss (a) 465 C.sub.28H.sub.49O.sub.5 [00027] H.sup.+ (b) 447 C.sub.28H.sub.47O.sub.4 [00028] H.sub.2O (c) 433 C.sub.27H.sub.45O.sub.4 [00029] CH.sub.3OH (d) 421 C.sub.26H.sub.45O.sub.3 [00030] CO.sub.2 (e) 405 C.sub.26H.sub.45O.sub.3 [00031] (C) - C.sub.2H.sub.4 (f) 403 C.sub.27H.sub.47O.sub.2 [00032] (CO.sub.2 + H.sub.2O) (g) 349 C.sub.22H.sub.37O.sub.3 [00033] [00034] (h) 297 C.sub.18H.sub.33O.sub.3 [00035] (b) -[00036] (i) 279 C.sub.18H.sub.31O.sub.2 [00037] (h) - H.sub.2O (j) 241 C.sub.15H.sub.29O.sub.2 [00038] [00039] (k) 223 C.sub.13H.sub.19O.sub.3 [00040] [00041] (l) 185 C.sub.13H.sub.19O.sub.3 [00042] [00043]

TABLE-US-00009 TABLE 9 Structural assignments for the key MS/MS fragments for Biomarker 7, C.sub.28H.sub.50O.sub.4, (450.3726, neutral mass) m/z Formula Molecular fragment Fragment loss (a) 449 C.sub.28H.sub.49O.sub.4 [00044] H.sup.+ (b) 431 C.sub.28H.sub.49O.sub.4 [00045] H.sub.2O (c) 417 C.sub.27H.sub.45O.sub.3 [00046] (H.sub.2O + CH.sub.3) (d) 413 C.sub.28H.sub.45O.sub.2 [00047] 2 H.sub.2O (e) 405 C.sub.27H.sub.49O.sub.2 [00048] CO.sub.2 (f) 399 C.sub.27H.sub.49O.sub.2 [00049] (c) - H.sub.2O (g) 387 C.sub.27H.sub.47O [00050] (CO.sub.2 + H.sub.2O) (h) 371 C.sub.26H.sub.43O [00051] (g) - CH.sub.4 (i) 281 C.sub.18H.sub.33O.sub.2 [00052] [00053] (j) 277 C.sub.19H.sub.33O [00054] (c) -[00055]

TABLE-US-00010 TABLE 10 Structural assignments for the key MS/MS fragments for Biomarker 8, C.sub.28H.sub.52O.sub.5, (468.3840, neutral mass) m/z Formula Molecular fragment Fragment loss (a) 467 C.sub.28H.sub.51O.sub.5 [00056] H.sup.+ (b) 449 C.sub.28H.sub.49O.sub.4 [00057] H.sub.2O (c) 431 C.sub.28H.sub.47O.sub.3 [00058] 2 H.sub.2O (d) 423 C.sub.27H.sub.51O.sub.2 [00059] CO.sub.2 (e) 405 C.sub.27H.sub.49O.sub.2 [00060] (CO.sub.2 + H.sub.2O) (f) 389 C.sub.26H.sub.45O.sub.2 [00061] (e) - CH.sub.4 (g) 297 C.sub.17H.sub.33O.sub.3 [00062] (b) -[00063] (h) 279 C.sub.18H.sub.31O.sub.2 [00064] (g) - H.sub.2O (i) 263 C.sub.17H.sub.27O.sub.2 [00065] (h) - CH.sub.4 (i) 215 C.sub.12H.sub.23O.sub.3 [00066] i,[00067]ii, CH.sub.3 (j) 187 C.sub.10H.sub.19O.sub.3 [00068] [00069] (k) 169 C.sub.10H.sub.17O.sub.2 [00070] (J) - H.sub.2O (l) 141 C.sub.8H.sub.13O.sub.2 [00071] (k) - C.sub.2H.sub.4

TABLE-US-00011 TABLE 11 .sup.1H NMR (500 MHz) chemical shifts (ppm).sup.a, multiplicity and J (Hz).sup.b of -tocopherol (1) and related compounds 3, 4, 5 and 6 in CDCl.sub.3. H #'s 1 2 3 4 5 6 1 2 5.12, m 3 1.75, m 1.95-2.10, m 1.48-1.59, m 1.41-1.53, m 1.82-1.83, m 1.24-1.25, m 1.78-1.86, m 1.80-1.83, m 1.97-2.03, m 4 2.66, m 2.69, t 1.78-1.86, m 1.80-1.83, m 1.97-2.03, m 2.28-2.34, m 1.94-2.01, m 1.93-1.99, m 2.23-2.30, m 5 6.35, s 6.38, s 5.33-5.36, m 1.80-1.83, m 5.31-5.36, m 5.25-5.37, m 2.21-2.25, m 6 1.78-1.86, m 3.69-3.71, m 5.31-5.36, m 5.25-5.37, m 1.94-2.01, m 7 1.94-2.01, m 1.41-1.53, m 1.95-2.02, m 8 2..24-2.31, m 2.21-2.25, m 2.74-2.76, m 2.72-2.75, m 9 4.59-4.62, m 4.58-4.62, m 10 11 1.05-1.25, m 1.79, m 1.10-1.32, m 1.08-1.15, m 1.24-1.36, m 1.95-2.02, m 12 1.05-1.25, m 1.95-2.10, m 2.24-2.31, m 1.93-1.99, m 1.97-2.03, m 1.24-1.25, m 13 1.05-1.25, m 5.08-5.14, m 5.33-5.36, m 5.33-5.34, m 5.31-5.36, m 1.53-1.54, m 14 1.32-1.36, m 15 1.05-1.25, m 1.95-2.10, m 1.48-1.59, m 1.41-1.53, m 1.82-1.83, m 1.53-1.54, m 16 1.05-1.25, m 1.95-2.10, m 1.10-1.32, m 1.08-1.15, m 1.24-1.36, m 1.24-1.25, m 17 1.05-1.25, m 5.08-5.14, m 1.10-1.32, m 1.23-1.31, m 1.24-1.25, m 18 1.32-1.36, m 1.80-1.83, m 1.24-1.36, m 1.95-2.02, m 19 1.05-1.25, m 1.95-2.10, m 1.10-1.32, m 1.23-1.31, m 1.24-1.36, m 1.24-1.25, m 20 1.05-1.25, m 1.95-2.10, m 1.10-1.32, m 1.08-1.15, m 1.24-1.36, m 1.24-1.25, m 21 1.05-1.25, m 5.08-5.14, m 1.10-1.32, m 1.23-1.31, m 1.24-1.36, m 1.53-1.54, m 22 1.32-1.36, m 2..24-2.31, m 2.21-2.25, m 2.23-2.30, m 2.28-2.34, m 23 0.81-0.85, m 1.60, s 24 0.81-0.85, m 1.69, s 0.84-0.88, m 0.0.83-0.85, m 0.83-0.90, m 0.85-0.87, m 25 0.81-0.85, m 1.61, s 1.00.sup.c, s 0.95.sup.c, s 1.00.sup.c, s 0.85-0.87, m 26 0.81-0.85, m 1.61, s 1.55, s 1.53, s 1.54, s 1.53-1.54, m 27 1.53, s 1.27, s 0.91, s 0.89, s 0.90, s a: 4.04-4.14, dd (J = 6.0, 12.0) b: 4.27-4.29, dd (J = 4.0, 12.0) 28 2.12, s 2.13, s 0.84-0.88, m 0.0.83-0.85, m 0.83-0.90, m 1.24-1.25, m 29 2.09, s 2.14, s 0.67.sup.c, br s 0.66.sup.c, br s 0.66.sup.c, br s 1.24-1.25, m .sup.aThe signals were determined and assigned from the position of cross peaks in .sup.1H - .sup.1H COSY, .sup.1H - .sup.1H homonuclear decoupling, HMQC and HMBC spectra. .sup.bCoupling constants (J) are reported to the nearest 0.5 Hz. .sup.cThe assignments may be reversed

TABLE-US-00012 TABLE 12 .sup.13C NMR (125.8 MHz) chemical shifts (ppm).sup.a of tocopherol (1) and related compounds 3, 4, 5 and 6 in CDCl.sub.3. Carbon # 1 2 3 4 5 6 1 2 74.5 75.2 57.2 57.3 56.7 69.7 3 31.7 31.4 30.2 32.4 37.0 14.9 4 20.8 22.3 30.1 36.3 35.8 .sup.30.1 .sup.b 5 118.6 112.13 130.5 37.8 122.6 130.8 6 144.6 146.3 28.7 72.3 130.0 130.5 7 121.2 118.24 37.5 32.2 126.1 30.3 8 122.6 121.6 38.7 42.8 27.8 30.3 9 145.6 134.9 74.2 141.8 73.7 147.5 10 117.3 135.0 140.2 100.5 138.5 100.8 11 39.9 39.8 40.2 40.0 36.6 30.5 12 21.1 22.3 24.3 28.7 31.9 23.3 13 37.4 124.4 120.7 119.9 128.3 39.5 14 32.8 125.7 130.3 122.2 139.7 69.0 15 37.4 39.6 32.4 24.8 28.2 35.0 16 24.5 26.6 .sup.40.0 .sup.b .sup.19.9 .sup.b .sup.28.0 .sup.b .sup.23.5 .sup.b 17 37.4 124.4 .sup.37.1 .sup.b .sup.36.7 .sup.b 27.8 30.0 18 32.7 134.9 56.6 56.7 56.1 31.2 19 37.4 36.7 .sup.28.5 .sup.b .sup.40.2 .sup.b .sup.29.0 .sup.b 29.9 20 24.8 26.8 .sup.23.3 .sup.b .sup.23.3 .sup.b .sup.24.3 .sup.b 29.7 21 39.4 124.2 .sup.36.3 .sup.b .sup.28.5 .sup.b .sup.23.8 .sup.b 34.8 22 28.0 131.2 42.8 37.0 39.7 32.7 23 22.7 25.7 173.8 173.8 174.0 174.1 24 21.1 17.8 23.0 24.3 22.8 .sup.24.6 .sup.b 25 19.7 16.0 .sup.19.2 .sup.b .sup.19.2 .sup.b .sup.18.7 .sup.b 26.4 26 19.7 15.87 19.8 23.0 22.5 .sup.28.0 .sup.b 27 23.8 24.5 .sup.30.1 .sup.b .sup.21.6 .sup.b .sup.21.0 .sup.b 62.9 28 12.1 11.9 .sup.19.2 .sup.b .sup.24.3 .sup.b .sup.19.3 .sup.b .sup.25.7 .sup.b 29 11.8 11.8 .sup.19.8 .sup.b .sup.12.3 .sup.b .sup.11.8 .sup.b .sup.11.7 .sup.b .sup.aThe signals were determined and assigned from the position of cross peaks in HMQC and HMBC spectra. .sup.b The assignments may be reversed

TABLE-US-00013 TABLE 13 A. Summary of HTS results including cross-cancer specificities, demographic and disease staging data. B. P-values showing no statistical significance between randomly selected sets of patients based on ethnicity, gender, age, BMI, presence of polyps and staging. A Disease Normal CRC Ovarian Prostate Renal Cell Lung Breast Sample Size 288 186 20 24 30 25 25 Average CRC 0.45 0.076* 2.31 1.18* 1.96 0.94* 0.71 0.56* 1.10 1.03* 1.20 0.90* 0.76 0.71* Score** P-value versus 5.40E68 2.00E16 7.00E02 9.60E06 1.80E06 3.20E02 normal Predicted CRC 11.4 78.1 70.0 16.7 33.3 40.0 20.0 Positive (%) Predicted CRC 88.6 21.9 30.0 83.3 66.7 60.0 80.0 Negative (%) Mean age 58.7 13.7 60.3 14.8 60.7 12.8 63.1 9.9 67.6 12.1 61.2 13.0 57.7 12.8 Mean BMI 26.4 5.2 23.8 6.0 21.5 7.8 24.6 4.6 24.3 5.8 24.0 4.6 25.0 6.5 Gender Male 157 115 24 17 11 Female 131 71 20 13 14 25 Ethnicity Caucasian 218 76 13 24 26 22 18 Asian/Hispanic 42 101 7 2 1 3 African 20 6 24 2 4 American Other 8 3 Disease Stage 0 2 1 I 25 5 1 14 12 3 II 79 12 6 2 13 III 45 13 8 5 3 4 IV 15 1 2 2 1 Not Available 20 2 2 3 6 3 Pathology 186 Adeno- 2 Adeno- 22 Adeno- 19 Clear Cell 5 Non-small 4 Ductal carcinoma carcinoma carcinoma 4 Papillary cell adeno- 16 Infiltrating 7 Epithelial 2 Other 7 Other carcinoma Ductal 8 Papillary 3 Non-small 2 Lobular 3 Other cell carcinoma 2 Infiltrating 5 Carcinoid Lobular 3 Small cell 1 Pagets 2 Squamous non- small cell 2 Bronchio- alveolar Carcinoma 3 Other Polyp Status for CRC Polyps Present 29 Polyps Absent 143 Not Available 14 7.3 Gleason Score *Standard Deviation **Based on the lowest mean-normalized ratio among the six biomarker signals B Hispanic/Asian Male vs Age <60 BMI <25 Polyps Stage I/II vs Caucasian Female vs >60 vs >25 Yes vs No vs III/IV p-value 0.3.sup.1 0.6.sup.2 0.3.sup.3 0.2.sup.4 0.2.sup.5 0.5.sup.6 .sup.140 CRC-positive Hispanic/Asian, 40 normal Hispanic/Asian, 40 CRC-positive Causasian and 40 normal Caucasian .sup.2ALL subjects .sup.320 CRC-positive < age 60, 20 normal < age 60, 20 CRC-positive > age 60, 20 normal > age 60 .sup.425 CRC-positive BMI < 25, 25 normal BMI < 20, 25 CRC-positive BMI > 25, 25 normal BMI > 25 .sup.529 CRC-positive with polyps, 29 CRC-positive with no polyps .sup.630 CRC-positive TNM stage I or II, 30 CRC-positive TNM stage III or IV