TPM4-ALK fusion protein and composition for diagnosing cancer

Abstract

Background: Recently, studies on genome and transcritome of gastric cancer have suggested that gastric cancer is a heterogeneous disease caused by various genetic defects combined with environmental risk factors. In the present invention, a fusion protein expressed only in Korean gastric cancer tissues is detected by performing quantitative label-free proteome analysis.

Result: A tropomyosin 4 (TPM4)-anaplastic lymphoma receptor tyrosine kinase (ALK) fusion protein, which is not expressed in a normal gastric tissue, but expressed only in a gastric cancer tissue, is identified. As a result identified by the TPM4 antibody, a high-molecular TPM4 band is present only in a gastric cancer tissue.

Claims

1. A TPM4-ALK fusion protein for diagnosing cancers, wherein a tropomyosin 4 (TPM4) protein or a fragment thereof at an N-terminal and an anaplastic lymphoma receptor tyrosine kinase (ALK) protein or a fragment thereof at a C-terminal are fused.

2. The TPM4-ALK fusion protein of claim 1, wherein the TPM4-ALK fusion protein has an amino acid sequence of SEQ ID NO: 1.

3. A TPM4-ALK fusion gene for diagnosing cancers encoding the fusion protein of claim 1.

4. The TPM4-ALK fusion gene of claim 3, wherein the fusion gene has a nucleotide sequence of SEQ ID NO: 2.

5. The TPM4-ALK fusion protein of claim 1, wherein the cancer is any one selected from lung cancer, liver cancer, colon cancer, pancreatic cancer, gastric cancer, breast cancer, ovarian cancer, kidney cancer, thyroid cancer, esophageal cancer, prostate cancer, and brain cancer.

6. A composition for diagnosing cancers of patients to be tested, wherein the composition includes at least one selected from the group consisting of a molecule specifically binding to the fusion protein of claim 1 and a polynucleotide hybridizable with a fusion gene encoding the fusion protein.

7. The composition for diagnosing cancers of claim 6, wherein the molecule specifically binding to the fusion protein is at least one selected from the group consisting of an antibody and an aptamer.

8. The composition for diagnosing cancers of claim 6, wherein the cancer is any one selected from lung cancer, liver cancer, colon cancer, pancreatic cancer, gastric cancer, breast cancer, ovarian cancer, kidney cancer, thyroid cancer, esophageal cancer, prostate cancer, and brain cancer.

9. A method for providing cancer diagnosis information, comprising: detecting the fusion protein of claim 1, a fusion gene encoding the fusion protein, or an mRNA corresponding to the fusion gene, wherein when the fusion protein, the fusion gene, or the mRNA is detected, the patient is determined as a cancer patient.

10. The method for providing cancer diagnosis information of claim 9, wherein the cancer is any one selected from lung cancer, liver cancer, colon cancer, pancreatic cancer, gastric cancer, breast cancer, ovarian cancer, kidney cancer, thyroid cancer, esophageal cancer, prostate cancer, and brain cancer.

11. The method for providing cancer diagnosis information of claim 9, wherein in the detecting, any one method selected from immunochromatography, immunohistochemical staining, ELISA, radioimmunoassay, enzyme immunoassay, fluorescence immunoassay, luminescence immunoassay, western blotting, and FACS is applied.

12. A composition for preventing or treating cancers comprising: at least one selected from the group consisting of an inhibitor of the fusion protein of claim 1 and a polynucleotide molecule inhibitor encoding the fusion protein as an active ingredient.

13. The composition for preventing or treating cancers of claim 12, wherein the inhibitor of the fusion protein includes at least one substance selected from the group consisting of an antibody, an aptamer, a kinase inhibitor, and a signal transduction inhibitor.

14. The composition for preventing or treating cancers of claim 12, wherein the polynucleotide molecule inhibitor includes at least one substance selected from the group consisting of an siRNA, an shRNA, and an aptamer.

15. The composition for preventing or treating cancers of claim 12, wherein the cancer is any one selected from lung cancer, liver cancer, colon cancer, pancreatic cancer, gastric cancer, breast cancer, ovarian cancer, kidney cancer, thyroid cancer, esophageal cancer, prostate cancer, and brain cancer.

Description

DESCRIPTION OF DRAWINGS

[0027] FIG. 1 shows a result of analyzing gene ontology, that is, up-regulated or down-regulated genes in gastric cancer. Up-regulated proteins A or down-regulated proteins B identified in gastric cancer are associated with a variety of molecular functions and biological processes.

[0028] FIG. 2 shows a result of search tool for recurring instances of neighboring genes (STRING) analysis of up-regulated (red) or down-regulated (blue) proteins identified in gastric cancer tissues as compared with normal gastric tissues. The up-regulated or down-regulated genes are classified according to main functional characteristics thereof. Six closely related clusters are identified. Depending on the reported or predicted biological and molecular functions, five additional groups are further classified.

[0029] FIG. 3 shows a predicted three-dimensional structure of the TPM4-ALK fusion protein, in which a three-dimensional homology modeling of the TPM4-ALK fusion protein shows possible dimerization through a tropomyosin domain in the fusion protein.

[0030] FIG. 4 shows that a monoclonal TPM4 antibody recognizes a large fusion protein in a gastric cancer tissue-derived protein extract, but does not recognize the large fusion protein in a normal gastric tissue-derived protein extract.

[0031] A: Using a monoclonal anti-TPM4 antibody, two TPM4 bands are detected in a gastric cancer tissue, but not detected in a normal control gastric tissue. The upper band is expected as a fusion protein.

[0032] B: A monoclonal -actin antibody is used as a loading control.

[0033] C: A monoclonal TMP3 antibody detects only one band in gastric cancer tissue.

[0034] D: An amount of protein loaded on each lane is identified as the monoclonal -actin antibody. The monoclonal -actin antibody is used as a loading control.

[0035] FIGS. 5a to 5n show 27 fusion protein candidates identified through label-free proteomics. FIGS. 5a to 5n are separately shown for convenience, but show one drawing vertically connected to each other in actual. Coverage maps are indicated by colors described in <Materials and Methods> of the following Example.

MODES OF THE INVENTION

[0036] Hereinafter, configurations of the present invention will be described in more detail with reference to detailed Examples. However, it will be apparent to those skilled in the art that the scope of the present invention is not limited to only the disclosure of Examples.

[0037] <Materials and Methods>

[0038] Clinical Tissue Samples

[0039] A total of 9 pairs of gastric cancer tissues and adjacent normal tissues were collected from patients with gastric cancer who provided information and agreed on the gastrectomy received in the Hallym University Sungsim Hospital in 2011. Detailed patient clinical data were summarized in Table 1. As determined by pathologists, a central region of the tumor avoiding a necrotic tissue and adjacent normal tissues were used in Examples of the present invention. This study was approved by the Clinical Trials Committee of the Hallym University Sungsim Hospital (Approval No.: 2011-1057).

[0040] Protein Extraction

[0041] Proteins were extracted from gastric cancer tissues and adjacent normal tissues for label-free proteomic analysis using a T-PER tissue protein extraction kit (Pierce Biotechnology, Rockford, Ill., USA). Briefly, 20 to 30 mg of the tissue was grinded together with glass beads in 200 L of a T-PER reagent (containing protease) (Roche Diagnostics, Basel, Switzerland) and then sonicated six times for 30 seconds. The protein extract was centrifuged at 15,000 g for 10 minutes to obtain water-soluble fractions. All steps were performed on ice. The total protein in the water soluble fractions was quantified using BCA analysis. A supernatant was mixed with a loading buffer (Tris 40 mM pH 7.5, 2% SDS, 10% glycerol, and 25 mM DTT) and the mixture was heated at 95 C. for 5 minutes, and then 30 g of the proteins were loaded for each lane of a 12% SDS-PAGE gel. Thereafter, the gel was cut to separate respective sample lanes, and each lane was divided into five pieces. Finally, each piece was treated with trypsin-gold and then peptides were extracted and completely dried.

[0042] Label-Free Quantitative Proteomics

[0043] The peptides obtained by trypsin treatment were analyzed three times using a nanoAcquity UPLC (Waters, Milford, Mass.) coupled to a Synapt G1 HDMS mass spectrometer (Waters). The peptides were isolated using a BEH 130 C18 75 m250 mm column (Waters) with a particle size of 1.7 m and concentrated with a Symmetry C18 RP (180 m20 mm, particle size of 5 m). In each experiment, 2 L of the trypsin-treated peptides were loaded onto a concentration column with a mobile phase A (water containing 0.1% formic acid), respectively. The step concentration gradient was applied at a rate of 280 nL/min, contained 5 to 45% of a mobile phase B (acetonitrile containing 0.1% formic acid) for 55 minutes, and thereafter, the concentration steeply increased to 90% of the mobile phase B for 10 minutes. The eluted peptides were analyzed in a positive ionization mode using a data-independent MSE mode. MS/MS peaks of [Glu1]-fibrinopeptide (400 fmol/L) were applied for calculating a time-of-flight analyzer (TOF) in a range of m/z 50 to 1990, and double charge [Glu1]-fibrinopeptide ions (m/z 785.8426) were applied for lock mass correction. While the data was obtained, a capillary voltage was set to 3.2 kV and a power supply temperature was set to 100 C. The disintegration energy in a low energy MS mode (complete peptide ions) and a rising energy mode was set to 6 eV and 15 to 40 eV, respectively. A scan time was set to 1.0 second.

[0044] A LC-MSE raw data file was processed, and protein identification and relative quantitative analysis were performed using a ProteinLynx Global Server (PLGS 2.5.1, Waters).

[0045] Processing parameters included auto-resistance to precursors and resultant ions, at least three fragment ion matches per peptide, at least seven fragment ion matches per protein, at least two peptide matches per protein with up to 4% false positive rate (FRP), carbamidomethylation (+57 Da) of cysteine as a fixed variation, oxidation (+16 Da) of methionine as various variations, and one allowed missed cleavage. The proteins were identified by searching the Homo sapiens database (70,718 entries) on the Unitprot website (http://www.uniprot.org) as a PLGS software ion counting algorithm.

[0046] Quantitative analysis was performed using Waters Expression, which was a part of PLGS 2.5.1, based on the measurement of peptide ion peak intensities measured and observed repetitively three times in a low collision energy mode. A data set was standardized using an automatic standardization function. All proteins were identified with reliability of >95%, and in three repeated experiments for each sample, the same peptides were clustered using clustering software included in PLGS 2.5.1 based on mass accuracy and a retention time tolerance of <0.25 min Only proteins identified by repeating at least technology device with a protein probability score of 80 or higher were selected for quantitative and qualitative analysis.

[0047] In order to identify fusion proteins in gastric cancer, the present inventors used a fusion protein database from the Catalog of Somatic Mutations in Cancer (COSMICv77: http://cancer.sanger.ac.uk/cosmic). Amino acid sequence portions of the fusion proteins matched with the peptides were colored as follows.

[0048] Matched with one peptide: blue,

[0049] Matched with some of peptides: red,

[0050] Matched with modified peptides: green, and

[0051] Matched with partially modified peptides: yellow.

[0052] 26 fusion protein candidates were identified according to a manual and whether the peptide binds a junction of two proteins was tested (Additional file 3).

[0053] Prediction of Three-Dimensional Structure of Fusion Protein

[0054] A three-dimensional similarity model of the TPM4-ALK fusion protein was generated using MArkovian TRAnsition of Structure evolution: Protein 3-D Structure Comparison (http://strcomp.protein.osaka-u.ac.jp/matras/). Swiss PDB viewer 4.0.1 (Swiss Institute of Bioinformatics) was used for visualization and modification of the 3D fusion protein model.

[0055] Western Blot Analysis

[0056] Protein extracts derived from normal tissues and cancer tissues were isolated through 12% SDS-PAGE and then transferred to a nitrocellulose membrane. The protein extracts were blocked with a TBST containing 5% defatted milk powder and then proteins were detected from five pairs of gastric cancer samples and a normal control using mouse anti-TPM3 and anti-TPM4 antibodies (Developmental Study Hybridism Bank, University of Iowa, Ames, 10, USA). A monoclonal anti--actin antibody (Sigma-Aldrich, St. Louis, Mo., USA) was used as a loading control.

[0057] Proteins Differentially Expressed in Korean Gastric Cancer Patients

[0058] To identify proteins expressed differently in gastric cancer tissues, label-free proteomics was performed using nine pairs of cancers and normal gastric tissues matched thereto. The present inventors found 72 up-regulated proteins or 29 down-regulated proteins in at least five gastric cancer tissues, as compared with a normal control tissue, respectively (FIG. 1).

[0059] To study a gene ontology category of the differentially expressed proteins, up-regulated proteins or down-regulated proteins were uploaded in the Panther database (www.pantherdb.org) to be categorized according to biological processes. Among the 72 up-regulated proteins in gastric cancer tissues, 42, 34, 23 and 21 proteins were assigned to categories of a metabolic process, a cellular process, a location and a cellular component organization or biosynthesis, respectively. In contrast, among the 29 down-regulated proteins, 13, 11, 10 and 9 proteins were assigned to categories of a multicellular tissue process, a metabolic process, a developmental process and a cell process, respectively (FIG. 1).

[0060] In order to further study molecular and cellular causes of Korean gastric cancer pathogenesis, a relationship between proteins differentially expressed (DEPs) in Korean gastric cancer tissues was studied using a search tool for recurring instances of neighboring genes (STRING) database (www.STRING-db.org). FIG. 2 shows a STRING analysis result. Red dots indicate up-regulated proteins in cancer tissues, and blue dots indicate down-regulated proteins. Lines indicated by colors between the dots indicate various types of relationships. The differentially expressed proteins (DEPs) were divided into six clusters including most of highly related DEPs and five groups having known or predicted similar functions without relationships between the groups.

[0061] Changes in Protein Expression Regulating Actin Cytoskeleton and Motor Activity

[0062] Cluster I included two major pathways, that is, components for actin cytoskeleton and motor activity regulation. Interestingly, actin-binding proteins such as actinin -4 (ACTN4), actinin -1, actinin -1 skeletal muscle, Moesin (MSN), Vinculin and Transgelin and cross-linkers were consistently down-regulated in gastric cancer. Expression levels of ACTN4 in cancers of pancreas, ovary, lung, and salivary gland and a MSN level in breast cancer were changed. In contrast, levels of actin polymerized regulatory proteins such as an actin-related protein 3 homolog, an IQ motif-containing GTPase activating protein 1 (IQGAP1), an adenylate cyclase-associated protein 1, a GDP dissociation inhibitor 2 and a Rho GTPase activating protein 1 were significantly increased in gastric cancer. The up-regulation of the IQGAP1 among these proteins is known to be associated with carcinogenesis of lung, ovary, gastric, and colon cancers.

[0063] Motor activity regulatory factors such as myosin light chain 9 (MYL9, regulatory), myosin light chain 6, alkali, smooth muscle and non-muscle, tropomyosin 1- (TPM1), tropomyosin 2- and tropomyosin 3 (TPM3) were down-regulated in gastric cancer. However, myosin heavy chain 9 (MYH9, non-muscle) was up-regulated. Among these proteins, MYL9, TPM1 and MYH9 are known to be associated with the carcinogenesis of various tumors. Other down-regulation factors include intermediate filament factors such as Vimentin and Desmin (FIG. 1I), which are very closely related to hepatocellular carcinoma and colon cancer, respectively.

[0064] Main Components of Significantly Up-Regulated Microtubule

[0065] Among various tubulins present in humans, six -tubulins [tubulin (TUBA)-1A, TUBA-1B, TUBA-1C, TUBA-3E, TUBA-4A and TUBA-8], seven -tublines [tubulin (TUBB), TUBB-2A, TUBB-2B, TUBB-3, TUBB-4A, TUBB-4B, TUBB-6 and TUBB-8], and two regulators [Filamin A (FLNA), and chaperone containing TCP1 subunit 6A] were significantly up-regulated in gastric cancer (FIG. 2II). It is reported that the -tubulin is an established target for anticancer agents, and the FLNA is up-regulated in breast cancer tissues.

[0066] Ion Binding Proteins with Change in Expression in Gastric Cancer

[0067] Among proteins DEPs with changes in expression, iron- and oxygen-binding proteins such as hemoglobin (HB) subunit-, HB subunit-2, HB subunit-, HB subunit-1, and HB subunit-1 were significantly down-regulated in gastric cancer. In addition, the binding of albumin to Ca.sup.2+, Na.sup.+, and K.sup.+ was down-regulated in gastric cancer. On the other hand, other iron-binding proteins, transferrin and zinc-containing carbonic anhydrase were significantly up-regulated in gastric cancer (FIG. 2III).

[0068] Up-Regulated Glycolytic Metabolism-Related Proteins in Gastric Cancer

[0069] Proteins in Cluster IV are involved in various metabolic processes. Among these proteins, glyceraldehyde-3-phosphate dehydrogenase, enolase 1 (ENO1), enolase 2 (ENO2), glucose-6-phosphate isomerase (GPI), pyruvate kinase muscle (PKM), and phosphoglycerate kinase 1 (PGK1) are highly related to glycolysis. These genes are up-regulated and closely related to each other. This cluster also contains down-regulated malate dehydrogenase 1, ATP synthase H.sup.+ metastatic mitochondrial F1 complex -subunit, and citrate synthases found in myocardia and up-regulated mitochondria (FIG. 2IV).

[0070] Most of molecular chaperone-related proteins were up-regulated in gastric cancer.

[0071] Cluster V (FIG. 2V) includes two central molecular chaperones and corresponds to heat shock protein (HSP) 90 kDa cytoplasm- class A member 1 and HSP90 -family class b member 1, and strongly reacts with HSP family A member 1 analogue, HSP family A member 2, HSP family A member 5, HSP family A member 6, HSP family A member 8, HSP family A member 9, HSP family D member 1, hypoxia up-regulated 1 and HSP B member 1 (HSPB1). Except for the HSPB1, all heat shock proteins were up-regulated in gastric cancer.

[0072] Up-Regulated Proteins with Protein Folding and Trafficking Activities

[0073] Cluster VI (FIG. 2VI) includes up-regulated proteins located in the Golgi body (GA) or the endoplasmic reticulum (ER) and regulates protein folding and trafficking. Valosin-containing protein, major histocompatibility complex class 1 (HLA)-B, HLA-C, ribophorin II (RPN2), protein disulfide isomerase family A (PDIA) member-3, PDIA member-6, prolyl 4-hydroxylase subunit-, calnexin (CANX), calreticulin (CALR), thioredoxin domain containing 5, and glucosidase II -subunit are significantly up-regulated proteins.

[0074] Up-Regulated Proteins Involved in Protein Synthesis

[0075] Three proteins involved in protein synthesis, that is, eukaryotic translation elongation factor (EEF)-2, EEF-1A1 and EEF-1A2 were up-regulated and interacted with factors of other clusters. Among these proteins, the EEF1A2 is associated with carcinogenesis of ovarian cancer.

[0076] Down-Regulated Proto-Oncogene and Up-Regulated Protease Inhibitors in Gastric Cancer

[0077] Proto-oncogenes such as anterior gradient 2, anterior gradient 3, Ras inhibitor-1, SET nuclear proto-oncogene, tryptophanyl-tRNA synthethase, and ubiquitin-like modifier activating enzyme 1 were significantly down-regulated in gastric cancer (FIG. 2B). In addition, it was found that serpin peptidase inhibitor clade (SERPIN)-A member 1 (SPERPINA1) associated with tumor progression in gastric cancer and colon cancer and SERPIN-H member 1 identified as a strong biomarker of early-stage hepatocellular tumor were significantly increased in gastric cancer in the present invention.

[0078] Expression-Change Proteins Associated with Energy Metabolism and Cell Structural Factors

[0079] Creatine kinase B regulates energy homeostasis in tissues, and is decreased in cervical cancer and down-regulated in gastric cancer. In contrast, an ATPase Na.sup.+/K.sup.+-transfer subunit -1 which maintains energy homeostasis, mitochondrial aldehyde dehydrogenase 2 family which generates carboxylic acid by oxidizing aldehyde, and gastric type lipase F which is an enzyme involved in the digestion of triglycerides in foods were significantly up-regulated in gastric cancer.

[0080] Other proteins with multiple domains important for cellular structural organization also exhibited changes in expression. For example, POTE ankyrin domain family members (POTE)-J and POTE-I were down-regulated and up-regulated in gastric cancer, respectively. Lumican, which belongs to a leucine-rich small proteoglycan family regulating collagen fibril organization and involved in prostate cancer, was significantly down-regulated in gastric cancer. Major vault proteins are highly overexpressed in drug-resistant cancers. Caroferrin subunit -1, junction plakoglobin, lamin A/C, multiple PDZ domain crumbs cell polarity complex component, clathrin heavy chain, and leucine-rich pentatricopeptide repeat-containing were up-regulated.

[0081] The TPM4-ALK fusion protein was identified by label-free proteome analysis.

[0082] The present inventors studied MS data obtained from nine pairs of gastric cancer tissues and normal tissues using a COSMIC fusion gene database to obtain 27 fusion protein candidates (FIGS. 5a to 5n). The present inventors tested whether a peptide binds to a junction of two proteins by a mass spectrometer according to a manual. Only the TPM4-ALK fusion protein was identified to have the corresponding peptide binding the two proteins.

[0083] In order to further study a possible role of the TPM4-ALK fusion protein in the carcinogenesis process, a three-dimensional structure of the TPM4-ALK fusion protein was predicted by performing a homology modeling. The three-dimensional structure of the TPM4-ALK fusion protein indicated that one ALK kinase domain and one TPM first form one alpha helix and may be assembled as parallel dimeric coiled-coils with normal TPM4 or other TPM4-ALK fusion proteins (FIG. 3). The dimerization ability of the fusion protein suggests that the location of the fusion protein may be different from that of the normal protein, thereby changing cellular and molecular processes.

[0084] A larger sized band in gastric cancer tissue was recognized as a monoclonal TPM4 antibody.

[0085] To confirm the presence of the TPM4-ALK fusion protein, the present inventors performed Western blot analysis using a specific monoclonal antibody to TPM3 or TPM4. The anti-TPM4 antibody recognized a larger-sized band that was not detected in the normal gastric tissue. However, the anti-TPM3 antibody did not detect an added band. Only one band from the gastric cancer tissue showed the same migration pattern as observed in the normal gastric tissue (FIG. 4).

[0086] Table 1 shows clinical and pathological data of nine gastric cancer patients.

TABLE-US-00001 TABLE 1 Tumor Lauren No. Sex Age Stage location Differentiation classification 1 F 82 IIB Antrum Poorly differentiated Intestinal 2 M 57 IIA Antrum Moderately differentiated Intestinal 3 M 56 IIIB Antrum Poorly differentiated Mixed 4 M 79 IIIB Antrum Poorly differentiated Mixed 5 M 78 IIIB Antrum Signet ring cell Diffuse 6 M 78 IIA Body Moderately differentiated Intestinal 7 F 74 IIIC Body Signet ring cell Diffuse 8 F 78 IIIC Body Poorly differentiated Diffuse 9 M 59 IIIA Body Poorly differentiated Mixed