System and method for analyzing tissue for the presence of cancer using bio-marker profiles

Abstract

A system and method for intra-operative sample analysis including acquiring a tissue sample, preparing the tissue sample for mass spectrometry imaging, conducting a mass spectrometry imaging procedure on the tissue sample to produce an image, and analyzing the image to determine the presence or absence of a bio-marker.

Claims

1. A method for intra-operative sample analysis, the method including steps comprising: (a) preparing a breast tissue sample from a subject for mass spectrometry imaging; (b) imaging the breast tissue sample to produce a spectrographic report, the imaging of step (b) using a desorption electrospray ionization (DESI) mass spectrometry imaging (MSI) procedure in negative ion mode; (c) determining a presence of a lipid bio-marker in the breast tissue sample from the spectrographic report, including detecting ion peaks at m/z 89.1, m/z 365.4, m/z 391.4, m/z 413.4, m/z 445.4, m/z 572.6, m/z 626.8, m/z 656.8, and m/z 682.8 in the spectrographic report; and (d) generating a report indicating a likelihood of breast cancer in the subject based on step (c).

2. The method of claim 1, wherein the lipid bio-marker comprises a fatty acid.

3. The method of claim 2, wherein the fatty acid comprises oleic acid.

4. The method of claim 1, wherein the ion peaks are further detected at m/z 281.3 or m/z 303.3.

5. The method of claim 1, further comprising performing histological staining of the breast tissue sample.

Description

BRIEF DESCRIPTION OF DRAWINGS

(1) The invention will be better understood and features, aspects and advantages other than those set forth above will become apparent when consideration is given to the following detailed description thereof. Such detailed description makes reference to the following drawings.

(2) FIG. 1 is a summary of tissues samples used in exemplary experiments.

(3) FIG. 2 is a detail of an exemplary bio marker.

(4) FIG. 3 is a detail of another exemplary bio marker.

(5) FIG. 4 is a detail of another exemplary bio marker.

(6) FIG. 5 is a detail of another exemplary bio marker.

(7) FIGS. 6(a-c) is a profiled spectra taken in a negative ion mode in accordance with the present invention using DESI-MSI.

(8) FIGS. 7(a-e) is a series of images taken in accordance with the present invention using DESI-MSI.

(9) FIGS. 8(a-d) is another series of images taken in accordance with the present invention using DESI MSI.

(10) FIGS. 9(a-c) is an averaged and normalized spectra of ions taken in the negative ion mode in accordance with the present invention using DESI MSI on the samples of FIG. 1.

(11) FIGS. 10(a-b) illustrate a principle component analysis (PCA) of cases 9 and 14 using the software suite ClinProTools (Bruker Daltonics). In particular, FIG. 10a shows case 9 samples representing normal signatures such as contralateral breast, 5 cm and 2 cm away, clustered together, while the tumor edge and tumor samples derive from the normal cluster. Individual points each represent a spectrum (pixel) from the samples, and the samples harboring tumor derive from normal in a gradient suggesting an infiltrating edge or heterogenous composition of the tissue. FIG. 10b shows case 14 spectra from the tumor edge clustered between normal and cancerous sample. A combine analysis of both cases shows an overlap between tumor and tumor edge of both cases, and a clustering of 2 cm away, 5 cm away, and contralateral.

(12) FIGS. 11(a-e) is another series of images taken in accordance with the present invention using DESI-MSI.

(13) FIGS. 12(a-c) is another profiled spectra taken in the negative ion mode in accordance with the present invention using DESI-MSI.

(14) FIG. 13 is another series of images taken in accordance with the present invention using DESI-MSI.

(15) FIG. 14 is a schematic of a system in accordance with the present invention.

(16) While the invention is susceptible to various modifications and alternative forms, specific embodiments thereof have been shown by way of example in the drawings and are herein described in detail. It should be understood, however, that the description herein of specific embodiments is not intended to limit the invention to the particular forms disclosed, but on the contrary, the intention is to cover all modifications, equivalents, and alternatives falling within the spirit and scope of the invention as defined by the appended claims.

DETAILED DESCRIPTION OF THE INVENTION

(17) The following description of the invention is divided into three sections. The first section discusses various details an exemplary method methodology of sample acquisition and imaging in accordance with the present invention. The second section illustrates exemplary results of the use thereof. The third section discusses how various portions of the method work together toward the inventive system and method.

(18) Methodology:

(19) Tissues Sample Preparation:

(20) During development of the invention, Applicants obtained sixty-one (61) cancerous breast samples removed via mastectomy from fourteen (14) research subjects from Brigham and Women Hospital. The samples (shown in FIG. 1) were collected at a tumor center, a tumor edge, 2 cm away from the tumor edge, 5 cm away from the tumor edge, and from a contralateral breast when available. The types of breast cancer were classified based on the status of three most important receptors: estrogen receptor (ER), progesterone receptor (PR) and human epidermal growth factor receptor 2 (Her2). Among the fourteen cases, nine of them have the tumor type ER positive, PR positive and Her2 negative (ER/PR+, Her2−), which is the most commonly found in breast cancer. As to the gender, one male was included.

(21) Samples were flash frozen and stored in −80° C. freezer prior to analysis. The tissues were sectioned at 12 μm thickness using Microm HM550 crystat (Mikron Instrument Inc). 20 μm thickness was selected in several cases with fatty tissue. All the samples were mounted on regular glass slides. The slides were dried in a dessicator before analysis.

(22) DESI Mass Spectrometry Imaging:

(23) All the samples were analyzed using AmazonSpeed mass spectrometer (Bruker Daltonics, Mass.) connected with a commercial DESI source (Prosolia Inc., IN). The stage holding the glass slides mounted with tissue sections moved horizontally at the speed of 200 μm/s and vertically by 200 μm step to generate 2D image. The stage movement was controlled by OminiSpray 2D (Prosolia Inc., IN). A nondestructive solvent containing 50% acetonitrile and 50% dimethylformamide was used. A flow rate of 1 μL/min was selected for the solvent spray. The spectra were acquired within the mass range m/z 50-1100 with Bruker software Hystar (Bruker Daltonics, Mass.). In order to display 2D image, FireFly (Prosolia Inc., IN) was used to convert the data to be compatible with Biomap. All the images obtained from Biomap were displayed with the same intensity scale in each figure.

(24) Histological Staining:

(25) Standard hematoxylin and eosin staining (H&E Staining) was performed on the same tissue section after DESI MS imaging as well as serial sections to visualize tissue morphological information. Glass coverslips were used to cover slides with toluene in between as mounting medium. All the reagents used for H&E staining were purchased from Sigma (Sigma-Aldrich, St. Louis, Mo.). The optical tissue images were scanned using Axio Imager M1 microscope (Zeiss, Chester, Va.) at 40× magnification. The morphology of tissue sections was evaluated on the Mirax Digital Slide Desktop Server system.

(26) Results:

(27) Lipid Profiling in Breast Cancer Tissues Using DESI-MSI in Negative Ion Mode:

(28) As discussed above, tissue samples from a total of fourteen research subjects with various ages were analyzed using DESI-MS imaging. All the samples were analyzed in a negative ion mode. The spectra were collected within the range of m/z 50-1100. Therefore, the negatively charged ions from lipids and metabolites were acquired. To validate day-to-day reproducibility, mouse brain sections were tested in exactly the same condition at the beginning of the day before acquiring breast cancer data.

(29) The representative profiled spectra from breast cancerous and healthy tissue sections are shown in FIGS. 6(a-c) with corresponding optical images after histological staining. DESI-MS analysis followed by standard H&E staining was performed on the same tissue sections. The nondestructive spray solvent containing 50:50 ACN/DMF was used in the experiment and the tissue integrity was preserved after DESI-MS, allowing the subsequent histological analysis. The feasibility of evaluating these H&E stained tissues was approved by a breast pathologist. In healthy tissue from mammary glands and normal fatty tissue, similar lipid ion species and relative abundance (e.g. PS18:0/18:1 with m/z 788.7 and PI18:0/20:4 with m/z 885.7) were observed (FIGS. 6a and 6b), whereas the signals in fatty tissue were less intense. The dominant ions from healthy tissues were within the mass range m/z 700-1000. It can be concluded that these lipids came from noncancerous cells and higher intensities were obtained from mammary glands only because of the high cell density. However, distinct lipid species and intensities were observed, in the profiled spectrum from breast cancer tissue, especially in low mass region (FIG. 6c). Distinctive fatty acid ions were detected in low mass range <m/z 400 and lipids around m/z 600 were more abundant in cancerous tissues. In contrast, only background peaks were observed in low mass range <m/z 500 in healthy tissue in FIGS. 6a and 6b.

(30) Based on the profiled spectra, significantly distinct lipids were detected from breast cancer and normal cells. Distinctive peak patterns in low mass region were observed in tumor tissue. However, the tissues from tumor edge, depending on cancer cell concentration, gave varying relative abundance in low mass range of the profiled spectra.

(31) DESI-MSI of Breast Cancer Tissues in Negative Ion Mode:

(32) DESI-MSI was performed on the breast cancer samples to display two-dimensional images correlating the lipid intensities with spatial distributions. Chemical information combining with tissue morphology is able to confirm the differentiation of tumor and healthy tissue based on molecular images from DESI-MSI.

(33) FIGS. 7(a-e) includes the DESI-MSI images from samples of a tumor center, a tumor edge, 2 cm away and 5 cm away from the tumor edge, and a contralateral breast of research subject #9 respectively. Four ions, m/z 281.250 (oleic acid), m/z 391.375, m/z 655.625 and m/z 885.750 (PI18:0/20:4), were selected as representatives. All these images were plotted with the same color scale. The lipid PI18:0/20:4, present in both healthy and cancerous cells, was used as a control to state successful ion detection. Evidently, PI18:0/20:4 is more abundant in the areas with mammary glands and tumor. The DESI-MS images from healthy tissues (2 cm away, 5 cm away from tumor and contralateral side) were highly consistent with mammary gland distributions stained by H&E staining of the same sections. However, distinct images were observed for ions with m/z 281.250, m/z 391.375 and m/z 655.625. These lipids were very abundant in the tumor center, where there was high tumor cell density (FIG. 7a), whereas these lipids were absent or weak in healthy tissues (FIGS. 7c, 7d and 7e). Interestingly, in the tissue section from the tumor edge the tumor margin was significantly delineated by the ion images of m/z 281.250, m/z 391.375 and m/z 655.625, which agreed well with the one demonstrated by the histological staining of the same section. The ion with m/z 655.625 was still present although very weak in normal cells.

(34) Another example from research subject #14 is shown in FIGS. 8(a-d) . Similarly, the ions with m/z 281.250 and m/z 391.375 were abundant in the tumor center (FIG. 8a), but absent in healthy tissues from 2 cm away and 5 cm away from the tumor (FIGS. 7c and 7d). The ion with m/z 655.625 was less intense but still observed in normal tissues with similar distributions as mammary glands in normal tissues. Interestingly, the DESI MSI of these ions were distinct in the tumor edge. In contrast with the ion with m/z 655.625, m/z 281.250 and m/z 391.375 were abundant only on the edge of tissue.

(35) Tumor and normal tissues were able to be distinguished unambiguously based on single molecular image of certain lipid obtained from DESI-MSI. Overall 12 out of 14 cases demonstrated striking difference for ion images with m/z 281.250 and m/z 391.375 between tumor and healthy tissues. The use of nondestructive solvent with 50/50 ACN/DMF allows the subsequent histopathological evaluation on the same section as the tissue integrity was retained. The tissues from the tumor edge revealed distinctive molecular images but consistent with the tumor cell distributions evaluated by breast pathologist, allowing the delineation of tumor margin. The results establish the possibility of incorporating DESI-MSI intra-operatively for rapid diagnosis of breast cancer tissue.

(36) A typical spectrum to represent unique peaks only from tumor cells can be obtained by subtracting the ions coming from normal cells from the ions coming from tumor as shown in FIGS. 9(a-c) . The average of 13 and 14 spectra from the tumor and normal tissues respectively are displayed in FIGS. 9a and 9b with the subtracted spectrum shown in FIG. 9c. The ion intensities were normalized before the subtraction. While the lipid abundance was decreased dramatically in the mass range >m/z 700 after subtraction with some even having negative intensity e.g. m/z 885.8, the representative peaks from tumor were significant in the subtracted spectrum, especially in low mass region. This distinctive subtracted spectrum can be used in the statistical analysis in the future to guide the intra-operative identification of tumor tissue.

(37) Principle Component Analysis:

(38) Although the tumor tissue can be differentiated from healthy tissue simply according to single molecular image from DESI-MSI, principle component analysis (PCA) was conducted for more accurate evaluation using ClinProTool. The statistical analysis of data from research subject #9 and #14 were shown in FIGS. 10a and 10b respectively. Separation of the spectra from the tumor and normal tissue was observed in both cases. In FIG. 10a, the spectra from tumor edge of research subject #9 were mostly clustered with spectra from tumor, whereas those from research subject #14 in FIG. 10b the tumor edge spectra were clustered between normal and cancerous sample. A combine analysis of both cases shows an overlap between tumor and tumor edge of both cases, and a clustering of 2 cm away, 5 cm away, and contralateral.

(39) Abnormal Observation of Oleic Acid:

(40) An interesting phenomenon was observed in research subject #5 that oleic acid signals (m/z 281.2) in normal tissues were increased dramatically (FIGS. 11c and 11d) compared with the tumor center and the tumor edge (FIGS. 11a and 11b), while the ions with m/z 391.375 and m/z 655.625 remained with low intensity. The dominance of oleic acid in the profiled spectrum of normal tissue is obviously visualized in FIG. 11e. Serial sections were analyzed repeatedly using DESI-MSI and similar results were obtained.

(41) Lipid Analysis of Breast Cancer Tissues in Positive Ion Mode:

(42) The tissue sections from normal and tumor samples were also analyzed using DESI-MSI in positive mode. The representative spectra are shown in FIGS. 12(a-c) . The same lipid species were observed in both tumor and normal tissues, mostly PC and SM lipids. Similar to the negative ion mode, the healthy tissue with mammary glands gave more abundant signals compared to the normal fatty tissue (FIGS. 12a and 12b). However, in the profiled spectrum from the tumor tissue, the relative abundance of m/z 782.6 to other ions was dramatically changed (FIG. 12c). The ion images obtained by DESI-MSI failed to exhibit the discrimination between tumor and mammary glands in normal tissues with similar cell density. However, the incorporation of unique lipid relative abundance in the tumor is able to improve the confidence of detecting cancer tissue based on MS analysis.

(43) Discussion:

(44) A mass spectrometry based methodology is demonstrated here to distinguish breast cancerous and noncancerous tissue in order to potentially facilitate breast surgeon's decision making intra-operatively. Samples from 14 research subjects acquired at various locations of breast with tumor were investigated. The application of DESI-MSI enables the differentiation of the tumor from normal tissues and determination of a tumor boundary based on molecular images.

(45) Compared with positive ion mode, the lipid spectra obtained from negative ion mode gives more unique information. In the profiled spectrum from negative ion mode, distinctive fatty acids and lipids were identified in breast cancer tissues. About 85% of the samples showed a significant increase of ion abundance in the low mass region (<m/z 700) in tumor samples, while most ions in high mass range (e.g. m/z 885.7) exist in normal cells as well. A “tumor” spectrum can be obtained by subtracting the ions coming from normal tissue, which represents the unique ions from cancer and facilitates tumor tissue diagnosis using mass spectrometry. In 2D images from DESI-MSI, the distinction of cancer and healthy tissue can be directly visualized. The tumor margin was able to be delineated even based on single molecular image validating the DESI-MS based diagnosis of breast cancer. Statistical analysis was performed to confirm the classification of tumor and normal tissues.

(46) It is known that the lipids in breast samples degrade quickly during defrosting. In the exemplary experiments discussed above, although the samples were transferred carefully from −80° C. freezer to −20° C. crystat for sectioning, the dramatic decrease of lipid signals were observed in DESI-MSI when the tissues were resectioned. The comparison of the tissues from the same sample but sectioned and analyzed at different days is shown in FIG. 13. Obviously, the lipid ions were much less abundant on Feb. 6, 2013. Therefore, in order to obtain reliable lipid information, it is important to retain the samples fresh before analysis.

(47) FIGS. 2-5 show details of a number of bio-markers that may be useful for identifying tumor margins or boundaries. These bio-markers were uncovered during Applicants' study of DESI-MSI analysis. Further, the following bio-markers were uncovered in the negative ion mode:

(48) TABLE-US-00001 MARKER CHEMICAL FORMULA m/z 89.1 TBD m/z 281.3 C18H34O2 m/z 303.3 C20H32O2 m/z 365.4 C24H46O2 m/z 391.4 C26H48O2 m/z 413.4 . . . m/z 445.4 . . . m/z 572.6 . . . m/z 626.8 . . . m/z 656.8 . . . m/z 682.8 . . .

(49) The markers represented above and in FIGS. 2-5 are examples only. Other markers may exist and would be detected by the inventive system and method. In addition, all chemical formulas, names, identifications, and classifications are exemplary and form no boundary about the invention.

(50) Specifically, turning to FIG. 14, a system 900 is provided in accordance with the present invention that is designed to analyze a sample 902 acquired from a subject 904, particularly during an operative procedure. The system 900 may be configured for use with a tool or probe 906 to assist or work in conjunction with other systems for providing the sample 902 to a sample receptacle 908 of the system 900. For example, it is contemplated that the system may be compatible with systems or method or include systems disclosed in co-pending U.S. patent application Ser. No. 13/059,524, which is incorporated herein by reference in its entirety. Once a sample is provided to the sample receptacle 908, the sample is processed by a mass-spectrometry system 910. The mass-spectrometry system 910 analyzes the tissue to determine a presence of a bio-marker indicating a presence of cancer in the tissue sample. The mass-spectrometry system 910 may be a desorption electrospray ionization apparatus. In any case, the mass-spectrometry system 910 is coupled to a report generator 912 that is configured to deliver a report indicating a likelihood of cancer remaining in the subject based on the analysis and, more particularly, the above-described bio-markers. The report generator 912 may include a printing system to print a physical report or may include a display to display a report, including figures and user-interface components, for example, such as described with respect to FIGS. 6-13 and those derived therefrom.

(51) The invention has been described in connection with what are presently considered to be the most practical and preferred embodiments. However, the present invention has been presented by way of illustration and is not intended to be limited to the disclosed embodiments. Specifically, the above specific methods used are exemplary of the inventive concept and may be altered while still falling within the scope and spirit of the invention. Accordingly, those skilled in the art will realize that the invention is intended to encompass all modifications and alternative arrangements within the spirit and scope of the invention as set forth in the appended claims.