Marker composition for predicting prognosis of cancer, method for predicting prognosis of cancer and method for providing information for determining strategy of cancer treatment

Abstract

To provide a marker composition for predicting the prognosis of cancer and a method for predicting the prognosis of cancer using the same.SOLUTION: Provided is a composition for predicting the prognosis of gastric cancer, comprising a preparation for measuring the expression level of mRNA of a gene in a first gene group including ACTA2, or a protein thereof, wherein the preparation is a primer, probe, or antisense oligonucleotide that specifically binds to the mRNA of the gene.SELECTED DRAWING: Figure 1

Description

Technical Field

[0001] The present invention relates to a marker composition for predicting the prognosis of cancer, a method for predicting the prognosis of cancer using the same, and a method for providing information for determining the treatment direction of cancer. More specifically, the present invention provides a marker capable of predicting survival rate, chemo-sensitivity, chemo-resistance, immunotherapy sensitivity, immunotherapy resistance, or any combination thereof, a method for predicting the prognosis of cancer using the same, and a method for providing information for determining the treatment direction of cancer. According to the present invention, not only the prediction of the survival rate of a patient, but also the establishment of an effective treatment strategy is possible by classifying patient groups for which the administration of chemotherapeutic agents and immunotherapeutic agents is effective or unfavorable.

Background Art

[0002] Numerous studies have been conducted to overcome cancer, but cancer remains an intractable disease that has not been overcome yet. As treatment methods for diagnosed cancer, there are generally surgery, chemotherapy, radiation therapy, etc., but each method has many limitations. In addition, the possibility of recurrence is quite high even after the treatment of cancer is completed, and the sensitivity to chemotherapeutic agents and immunotherapeutic agents also varies greatly among individuals. Therefore, predicting the prognosis of cancer and the sensitivity to chemotherapeutic agents and immunotherapeutic agents is essential for determining the treatment direction of cancer patients.

[0003] On the one hand, many anticancer drugs are used as effective therapeutic agents, but a newly emerging problem is the resistance of cancer cells to anticancer drugs. Resistance to anticancer drugs occurs through various mechanisms such as long-term use of anticancer drugs causing cells exposed to the drug to reduce drug accumulation within the cell, activate detoxification or excretion, or deform the target protein. Such a process is not only the greatest obstacle factor for cancer treatment but also deeply related to treatment failure. In fact, when attempting chemotherapy for cancer patients, when a specific anticancer drug fails to exert its efficacy, there are frequent cases where resistance is also shown to other anticancer drugs subsequently. Even when attempting combination chemotherapy by simultaneously administering various types of anticancer drugs with different mechanisms of action during initial treatment, the phenomenon of no treatment effect can often be observed. As a result, the fact that the range of available anticancer drugs is very limited has been pointed out as an important issue in cancer chemotherapy.

[0004] Currently, as prognostic prediction criteria at the molecular level used in clinical practice, microsatellite instability (MSI), CpG island methylation phenotype (CIMP), chromosomal instability (CIN), BRAF / KRAS mutations, etc. are used, but there is a complete lack of a methodology for predicting the sensitivity of anticancer treatment according to the characteristics of each patient. Therefore, the development of markers that can accurately predict the prognosis of cancer patients and at the same time predict the sensitivity of anticancer treatment is an urgent situation.

[0005] If the prognosis of patients for anticancer drug treatment after cancer surgery can be predicted, it will serve as a basis for establishing a treatment strategy suitable for each prognosis. Since 2010, in the case of current stage II and III advanced gastric cancer, it has been found that adjuvant anticancer therapy after standardized gastrectomy can improve the survival rate of gastric cancer patients, and currently, this corresponds to the standard treatment method. Traditionally, gastric cancer has been classified according to its anatomical and pathological phenotype, and in cases of stage II or above according to the TNM staging method, anticancer treatment is carried out However, there is no method other than the TNM stage that can predict the prognosis of anticancer treatment.

[0006] On the other hand, anticancer chemotherapy is essential in the treatment of most cancer patients, but it is associated with severe side effects. Many patients cannot benefit from this treatment due to such side effects, or in some cases, the side effects may even lead to adverse outcomes for survival rates. Therefore, if a biomarker that can predict a patient's response to chemotherapy is provided, it is expected to improve the accuracy of treatment and provide the possibility of predicting survival rates and responses.

Summary of the Invention

Problems to be Solved by the Invention

[0007] Therefore, one aspect of the present invention is to provide a marker composition for predicting the prognosis of cancer.

[0008] Another aspect of the present invention is to provide a method for predicting the prognosis of gastric cancer using the marker composition of the present invention.

[0009] Still another aspect of the present invention is to provide a method for providing information for determining the treatment direction of cancer using the marker composition of the present invention.

Means for Solving the Problems

[0010] According to one aspect of the present invention, there is provided a marker composition for predicting the prognosis of cancer, which comprises a preparation for measuring the expression level of mRNA or its protein of at least one gene selected from the group consisting of ESR1, BEST1, ACTA2, HIPK2, IGSF9, ASCC2, JUN, PPP2R5A, SMAD3, CREBBP, EP300, and DDX5.

[0011] According to another aspect of the present invention, there is provided a method for predicting the prognosis of cancer, including the steps of measuring the expression level of mRNA or its protein of each gene in the marker composition for predicting the prognosis of cancer of the present invention, and comparing the measured expression level of mRNA or its protein of the gene.

[0012] According to still another aspect of the present invention, the expression level of mRNA or its protein of at least one gene selected from the first gene group consisting of ESR1, BEST1, ACTA2, HIPK2, IGSF9, ASCC2, JUN, PPP2R5A, SMAD3, CREBBP, EP300 and DDX5; the expression level of mRNA or its protein of at least one gene selected from the second gene group consisting of FHL2, PML, BRCA1, WT1, AREG and TP63; and the expression level of mRNA or its protein of at least one gene selected from the third gene group consisting of TP53, HSF1, NCOA6IP, PAWR, FAM96A, WTAP, PCNA, GNL3, WRN, SMARCA4, NCOA6, RPA1, MSH6 and PARP1 are measured, and the measured expression level of mRNA or its protein of the gene is compared. When the expression level of mRNA or its protein of the third gene group among the three gene groups is relatively high, it is classified into patient group 1. When the expression level of mRNA or its protein of the second gene group is relatively high, it is classified into patient group 3. When the expression level of mRNA or its protein of the first gene group is relatively high, it is classified into patient group 4, and other patients are classified into group 2. There is provided a method for providing information for determining the treatment direction of cancer, including the above steps.

Advantages of the Invention

[0013] According to the marker composition for predicting the prognosis of cancer of the present invention, the method for predicting the prognosis of gastric cancer using the same, and the method for providing information for determining the treatment direction of cancer, it is possible to predict the prognosis of cancer, that is, the survival rate, chemo-sensitivity and resistance, and immunotherapy sensitivity and resistance. Therefore, a more effective treatment strategy can be provided. That is, for patients in the group with a good prognosis, over-treatment related to anti-cancer therapy can be prevented, and for those with a poor prognosis but good anti-cancer therapy sensitivity, it is possible to establish an individualized patient-customized treatment strategy such as actively attempting to apply anti-cancer therapy agents.

Brief Description of the Drawings

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Mode for Carrying Out the Invention

[0015] Hereinafter, preferred embodiments of the present invention will be described with reference to the accompanying drawings. However, the embodiments of the present invention can be modified into various other forms, and the scope of the present invention is not limited to the embodiments described below.

[0016] The inventors of the present application have found that based on the expression levels of 32 genes included in a modified pathway specific to gastric cancer, the prognosis of cancer, that is, the survival rate and the suitability for applying anti-cancer therapy can be predicted. At this time, the above survival rate includes the overall survival rate, for example, the 5-year overall survival rate. The 32-gene test of the present invention may have the potential to improve the accuracy of cancer treatment.

[0017] In the present specification, "gene expression" is intended to include the expression level of the mRNA of the gene or its protein.

[0018] In the present invention, "prognosis" means predicting various states of a patient due to cancer, such as the possibility of complete cure of cancer after diagnosis, the possibility of recurrence after treatment, and the survival possibility of the patient. In the present invention, for example, it means including the survival rate, chemo-sensitivity, chemo-resistance, immunotherapy sensitivity, immunotherapy resistance, or the treatment prognosis of anti-cancer therapy which is any combination of these. For the purpose of the present invention, the prognosis can mean the prognosis of survival and the prognosis for treatment after the diagnosis of cancer. By using the marker provided by the present invention, the survival prognosis of cancer patients and the prognosis for anti-cancer therapy treatment can be more easily predicted, and it can be utilized for classifying patients in the high-risk group or further determining the presence or absence of the use of necessary treatment methods, thereby contributing to the improvement of the survival rate after the onset of cancer.

[0019] Also, the above-mentioned "prediction" is related to whether a patient responds preferentially or non-preferentially to a treatment method, and whether the patient will survive after treatment and / or the possibility thereof. The marker composition of the present invention can be clinically used for making treatment decisions by selecting an optimal treatment method for a patient with cancer. Furthermore, the prediction method of the present invention can be used, for example, for confirming whether a patient responds preferentially to a treatment prescription, or for predicting whether long-term survival of the patient is possible after the treatment prescription.

[0020] The "anticancer therapy" used in the present invention is intended to include treatment using (chemical) anticancer agents and / or immune anticancer agents.

[0021] More specifically, the marker composition for predicting the prognosis of cancer of the present invention includes a preparation for measuring the expression level of mRNA or its protein of at least one gene selected from the group consisting of ESR1, BEST1, ACTA2, HIPK2, IGSF9, ASCC2, JUN, PPP2R5A, SMAD3, CREBBP, EP300, and DDX5.

[0022] More preferably, the above composition includes a preparation for measuring the expression level of mRNA or its protein of the ACTA2 gene, and may include a preparation for measuring the expression level of mRNA or its protein of at least one, or at least two, or all of the above genes selected from the group consisting of the ACTA2 gene and ESR1, BEST1, HIPK2, IGSF9, ASCC2, JUN, PPP2R5A, SMAD3, CREBBP, EP300, and DDX5. For example, it may include a preparation for measuring the expression level of mRNA or its protein of at least one gene selected from the group consisting of BEST1, ACTA2, ESR1, CREBBP, and EP300.

[0023] For example, it may include a preparation for measuring the expression level of mRNA or its protein of at least one gene selected from the group consisting of BEST1, ACTA2, ESR1, CREBBP, and EP300.

[0024] Furthermore, the marker composition for predicting the prognosis of cancer of the present invention may further include at least one selected from the group consisting of FHL2, PML, BRCA1, WT1, AREG, and TP63, or at least two, or a preparation for measuring the expression level of the mRNA or its protein of all of the above genes.

[0025] In addition, the marker composition for predicting the prognosis of cancer of the present invention may further include at least one selected from the group consisting of TP53, HSF1, NCOA6IP, PAWR, FAM96A, WTAP, PCNA, GNL3, WRN, SMARCA4, NCOA6, RPA1, MSH6, and PARP1, or at least two, or a preparation for measuring the expression level of the mRNA or its protein of all of the above genes.

[0026] In the present invention, for convenience, the gene group consisting of ESR1, BEST1, ACTA2, HIPK2, IGSF9, ASCC2, JUN, PPP2R5A, SMAD3, CREBBP, EP300, and DDX5 can be referred to as the first gene group; the gene group consisting of FHL2, PML, BRCA1, WT1, AREG, and TP63 can be referred to as the second gene group; and the gene group consisting of TP53, HSF1, NCOA6IP, PAWR, FAM96A, WTAP, PCNA, GNL3, WRN, SMARCA4, NCOA6, RPA1, MSH6, and PARP1 can be referred to as the third gene group.

[0027] The above cancer for which the prognosis can be predicted using the marker composition of the present invention can be selected from the group consisting of gastric cancer, bladder cancer, kidney cancer, brain tumor, uterine cancer, skin cancer, pancreatic cancer, lung cancer, colorectal cancer, liver cancer, and breast cancer, and is preferably gastric cancer.

[0028] In this specification, "measurement of mRNA expression level" means a process of confirming the degree of mRNA expression of a gene in a biological sample, which means measuring the amount of mRNA. Analytical methods therefor include reverse transcription polymerase reaction (RT-PCR), competitive reverse transcription polymerase reaction (Competitive RT-PCR), real-time reverse transcription polymerase reaction (Real-time RT-PCR), RNase protection assay (RPA), Northern blotting, DNA chip, etc., but are not limited thereto.

[0029] In the composition according to the present invention, a preparation for measuring the expression level of mRNA of a gene contains a primer, a probe, or an antisense nucleotide that specifically binds to the mRNA of each gene. Since the information on each gene according to the present invention is known in GenBank, UniProt, etc., a person skilled in the art can easily design a primer, a probe, or an antisense nucleotide that specifically binds to the mRNA of each gene based on this.

[0030] In the present invention, the above "primer" means that under suitable conditions (i.e., four other nucleoside triphosphates and a polymerization reaction enzyme) in a suitable temperature and a suitable buffer solution, the template "Primer" means a single-stranded oligonucleotide that can act as a starting point for DNA synthesis. The appropriate length of the primer can vary depending on various factors, such as temperature and the use of the primer. Also, the sequence of the primer does not necessarily have to have a sequence that is completely complementary to a part of the template sequence, and it suffices to have sufficient complementarity within the range that can hybridize with the template and perform the specific function of the primer. Therefore, the primer in the present invention does not necessarily have to have a sequence that is perfectly complementary to the nucleotide sequence of each gene serving as a template, and it suffices to have sufficient complementarity within the range that can hybridize with this gene sequence and perform the primer function. The above-mentioned primer includes forward and reverse primer pairs, and preferably, it is a primer pair that provides analytical results having specificity and sensitivity. Since the nucleic acid sequence of the primer is a sequence that does not match the non-target sequence present in the sample, high specificity can be imparted when it is a primer that only amplifies the target gene sequence containing the complementary primer binding site and does not induce non-specific amplification.

[0031] The above-mentioned "amplification reaction" refers to a reaction for amplifying nucleic acid molecules, and such gene amplification reactions are well known in the art and can include, for example, polymerase chain reaction (PCR), reverse transcription polymerase chain reaction (RT-PCR), ligase chain reaction (LCR), transcription-mediated amplification (TMA), nucleic acid sequence-based amplification (NASBA), and the like.

[0032] In the present invention, the above-mentioned "probe" means a linear oligomer of natural or modified monomers or linkages, including deoxyribonucleotides and ribonucleotides, which can specifically hybridize to a target nucleotide sequence, and refers to those that exist naturally or are artificially synthesized. The probe according to the present invention may be single-stranded, and preferably, it may be an oligodeoxyribonucleotide. The probe of the present invention can include natural dNMPs (i.e., dAMP, dGMP, dCMP, and dTMP), nucleotide analogs, or derivatives. Also, the probe of the present invention can include ribonucleotides.

[0033] In the present invention, the expression level of the above protein preferably means a polypeptide generated through the translation process from the mRNA in which each gene is expressed. As substances capable of measuring the level of each of the above proteins, "antibodies" such as polyclonal antibodies, monoclonal antibodies, and recombinant antibodies that can specifically bind to each protein can be included.

[0034] The prognostic prediction marker composition for cancer of the present invention may further contain a pharmaceutically acceptable carrier. The above pharmaceutically acceptable carrier includes carriers and vehicles commonly used in the pharmaceutical field. Specifically, ion exchange resins, alumina, aluminum stearate, lecithin, serum proteins (for example, human serum albumin), buffering substances (for example, various phosphates, glycine, sorbic acid, potassium sorbate, partial glyceride mixtures of saturated vegetable fatty acids), water, salts or electrolytes (for example, protamine sulfate, disodium hydrogen phosphate, potassium hydrogen phosphate, sodium chloride, and zinc salts), colloidal silica, magnesium trisilicate, polyvinylpyrrolidone, cellulose-based substrates, polyethylene glycol, sodium carboxymethyl cellulose, polyarylate, wax, polyethylene glycol, or lanolin, etc., are included, but not limited thereto.

[0035] In addition to the above components, lubricants, wetting agents, emulsifying agents, suspending agents, or preservatives, etc., can be further included.

[0036] According to another aspect of the present invention, a method for predicting the prognosis of cancer using the marker composition of the present invention is provided.

[0037] More specifically, the method for predicting the prognosis of cancer of the present invention includes a step of measuring the expression level of the mRNA or its protein of each gene of the prognostic prediction marker composition for cancer, and a step of comparing the measured expression level of the mRNA or its protein of the above gene.

[0038] The above comparison relatively compares the expression levels of the mRNA of the measured gene or its protein. At this time, various known methods in the art can be used to compare the expression levels of the mRNA or its protein, and known data analysis methods can be used for processing. As an example, methods such as the nearest neighbor classifier, partial-least squares, SVM, AdaBoost, and clustering-based classification can be used. In addition, various statistical processing methods can be used to confirm significance. As a statistical processing method, in one implementation example, a logistic regression analysis method can be used.

[0039] The cancer prognosis prediction method of the present invention may further include a step of determining a poor prognosis of chemotherapy with a chemical anticancer agent and / or a poor prognosis of immunotherapy with an anticancer agent when the expression level of at least one gene selected from the first gene group consisting of ESR1, BEST1, ACTA2, HIPK2, IGSF9, ASCC2, JUN, PPP2R5A, SMAD3, CREBBP, EP300, and DDX5, for example, at least one of ACTA2, ESR1, BEST1, HIPK2, ASCC2, JUN, EP300, CREBBP, and DDX5, is relatively high at the mRNA or protein level, preferably when the expression level of the mRNA or protein of ACTA2 is relatively high.

[0040] In addition, when using the marker composition of the third gene group, if the expression level of at least one gene selected from the group consisting of TP53, HSF1, NCOA6IP, PAWR, FAM96A, WTAP, PCNA, GNL3, WRN, SMARCA4, NCOA6, RPA1, MSH6, and PARP1, for example, at least one of the mRNAs or proteins of TP53, HSF1, NCOA61P, PAWR, FAM96A, WTAP, PCNA, GLN3, WRN, SMARCA4, NCOA6, RPA1, MSH6, and PARP1 is relatively high, more preferably, at the same time, if the expression level of the mRNA or protein of ACTA2 is relatively low, it may further include the step of determining that the prognosis of chemotherapy with a chemical anticancer agent is poor and the prognosis of immunotherapy with an immunological anticancer agent is good.

[0041] Furthermore, when using the marker composition of the second gene group, if the expression level of at least one gene selected from the group consisting of FHL2, PML, BRCA1, WT1, AREG, and TP63, for example, at least one of the mRNAs or proteins of FHL2, PML, BRCA1, WT1, AREG, and TP63 is relatively high, more preferably, at the same time, if the expression level of the mRNA or protein of ACTA2 is relatively low, it may further include the step of determining that the prognosis of chemotherapy with a chemical anticancer agent and / or immunotherapy with an immunological anticancer agent is good.

[0042] At this time, the above prognosis may be survival rate, chemo-sensitivity, chemo-resistance, immunotherapy sensitivity, immunotherapy resistance, or any combination thereof.

[0043] Also, referring to FIG. 2, a significant difference in overall survival rate was confirmed among the groups. Patients in Group 1 with a high expression level of the genes in the III gene group showed the best results, while it was confirmed that patients in Group 4 with a high expression level of the genes in the I gene group showed the worst results. This was the case.

[0044] In the present invention, whether the expression level of a gene's mRNA or its protein is high is determined relatively by comparing the measured expression level of the gene's mRNA or its protein. For example, when it exceeds the total average expression level of the measured gene's mRNA or its protein, it can be determined that the expression level is high. For example, by converting the mRNA expression level into a Z-score and showing a heat map, it can be determined that the expression level of the gene corresponding to the positive region is high. For example, in the case of ACTA2, when the mRNA expression level measured by bulk mRNA sequencing, log2(Fragments Per Kilobase of transcript per Million mapped reads (FPKM)+1) is relatively the same as or greater than the measured expression level of the gene's mRNA or its protein, and / or in the case of immunohistochemistry, when the score calculated by multiplying the staining intensity and the number of points in the staining area is greater than 3, it can be determined that the ACTA2 expression level is high. Also, when the Log2(FPKM+1) value is relatively smaller than the measured expression level of the gene's mRNA or its protein and / or in the case of immunohistochemistry, when the score calculated by multiplying the staining intensity and the number of points in the staining area is the same as or less than 3, it can be classified that the ACTA2 expression level is low. For example, referring to FIG. 9, when the Log2(FPKM+1) value is 5 or more, the ACTA2 expression level is high, and when it is less than 5, it can be regarded as low. The expression levels of other genes can also be classified as high or low in the same or similar manner as described above.

[0045] That is, since the marker composition of the present invention can independently confirm the association with the risk of death, it can be seen that it can serve as a prognostic criterion independently of conventionally known clinical and pathological variables.

[0046] According to still another aspect of the present invention, there is provided a method for providing information for determining the treatment direction of cancer.

[0047] More specifically, the method for providing information for determining the treatment direction of cancer of the present invention includes measuring the expression level of mRNA or its protein of at least one gene selected from the first gene group consisting of ESR1, BEST1, ACTA2, HIPK2, IGSF9, ASCC2, JUN, PPP2R5A, SMAD3, CREBBP, EP300, and DDX5; the expression level of mRNA or its protein of at least one gene selected from the second gene group consisting of FHL2, PML, BRCA1, WT1, AREG, and TP63; and the expression level of mRNA or its protein of at least one gene selected from the third gene group consisting of TP53, HSF1, NCOA6IP, PAWR, FAM96A, WTAP, PCNA, GNL3, WRN, SMARCA4, NCOA6, RPA1, MSH6, and PARP1, and comparing the measured expression levels of mRNA or its protein of the above genes. When the expression level of mRNA or its protein of the third gene group among the three gene groups is relatively high, it is classified into patient group 1. When the expression level of mRNA or its protein of the second gene group is relatively high, it is classified into patient group 3. When the mRNA expression level of the first gene group is relatively high, it is classified into patient group 4, and other patients are classified into group 2.

[0048] The above patient group 2 can be patients in whom the mRNA expression levels of the first to third gene groups are not classified among the first to third gene groups, that is, it means a case where there is no tendency such as an increase in the gene expression level in a specific gene group across the first to third gene groups.

[0049] The method for providing information for determining the cancer treatment direction of the present invention further includes at least one of the steps of predicting that anti-cancer therapy using a chemical anti-cancer agent is incompatible for patient group 1, predicting that anti-cancer therapy using a chemical anti-cancer agent is compatible for patient group 3, and predicting that anti-cancer therapy using a chemical anti-cancer agent is incompatible for patient group 4.

[0050] At this time, the anti-cancer agent can be a combined anti-cancer therapy in which at least one chemical anti-cancer agent selected from fluorouracil (5-FU), bleomycin, and epirubicin is combined based on platinum, and preferably, it is a combined anti-cancer therapy of platinum or platinum and fluorouracil (5-FU).

[0051] In the present invention, it was confirmed that patients in group 3 showed improved survival rates in relation to anti-cancer therapy using chemical anti-cancer agents based on 5-FU and platinum, and patients in group 2 showed improved survival rates in relation to treatment therapy using 5-FU alone chemical anti-cancer agents.

[0052] Furthermore, interestingly, patients in group 3 showed good responses to both 5-FU and platinum doublet chemotherapy and anti-PD-1 therapy, so clinical attempts at combinations of chemical anti-cancer agents and immune anti-cancer agents could be considered in this patient population.

[0053] On the other hand, although patients in group 1 showed the best prognosis, it was confirmed that applying anti-cancer therapy using chemical anti-cancer agents, for example, 5-FU and platinum treatment therapy, would worsen the prognosis. Therefore, a strategy of excluding anti-cancer therapy using chemical anti-cancer agents can be considered for patients in group 1.

[0054] Furthermore, the method for providing information for determining the cancer treatment direction of the present invention may include at least one step of predicting that immunotherapy using an immune anticancer agent is suitable for at least one of patient group 1 and patient group 3, and predicting that immunotherapy using an immune anticancer agent is unsuitable for at least one of patient group 2 and patient group 4.

[0055] In this case, the immune anticancer agent may be at least one immune anticancer agent selected from an anti-PD1 immune anticancer agent (Anti PD1 inhibitor), an anti-CTLA4 (Anti CTLA4) immune anticancer agent, and an anti-PDL1 (Anti PDL1) immune anticancer agent.

[0056] Furthermore, in the method for providing information for determining the cancer treatment direction of the present invention, it may further include a step of diagnosing microsatellite instability (MSI, microsatellite instability) for determining the cancer treatment direction.

[0057] For example, when diagnosing microsatellite instability (MSI, microsatellite instability) and confirming a patient with high-frequency microsatellite instability (microsatellite instability high, MSI-H), as can be confirmed in FIG. 10, it can be confirmed that the biomarkers of the present invention, for example, at least one of the first gene group, preferably the survival probabilities are significantly different when the expression of the ACTA2 gene is high and low.

[0058] Therefore, by combining the diagnosis of microsatellite instability (MSI, microsatelite instability) widely used in the art with the marker composition for predicting the prognosis of cancer of the present invention, more detailed information that was not previously classified can be obtained. It is expected that patients can be classified into groups and the prognosis can be predicted to determine the most effective treatment direction suitable for the patients. Thus, according to the prognostic marker composition for cancer of the present invention, the method for predicting the prognosis of gastric cancer using the same, and the method for providing information for determining the treatment direction of cancer, the prognosis of cancer and the sensitivity to immune anticancer agents and / or chemotherapeutic agents (chemo-sensitivity) can be predicted, so that a more effective treatment strategy can be provided.

[0059] That is, for patients in the group with a good prognosis, over-treatment related to anticancer therapy can be prevented. For the group with a poor prognosis but good sensitivity to anticancer therapy, it is possible to establish an individualized patient-customized treatment strategy such as actively attempting to apply anticancer therapy.

[0060] Hereinafter, the present invention will be described more specifically with specific examples. The following examples are merely illustrative for helping the understanding of the present invention, and the scope of the present invention is not limited thereto.

Example

[0061] Example 1. Identification of gene signature and molecular subtype To identify biomarkers for predicting prognosis in gastric cancer, the somatic mutation profiles of 6,681 patients from 19 different cancer types published by The Cancer Genome Atlas (TCGA) were input into NTriPath to identify pathways specifically altered in gastric cancer.

[0062] To examine the usefulness of these pathways related to prognosis prediction, the inventors of the present application generated microarray-based mRNA expression profiles from pretreatment tumor samples of 567 patients surgically resected at Yonsei University. 89% of the patients had stage II or III disease, and the median duration of the follow-up period was 61 months.

[0063] It was confirmed that the following 32 genes in Table 1, including TP53, BRCA1, MSH6, PARP1, and ACTA2, in which DNA damage response, TGF-β signaling, and cell proliferation pathways were integrated, were included in the gastric cancer-specific pathways useful for prognosis prediction.

[0064] [Table 1]

[0065] Among the above genes, FHL2, PML, BRCA1, WT1, AREG, and TP63 are genes in the apoptosis signaling and cell proliferation pathways and are called the first gene group; ESR1, BEST1, ACTA2, HIPK2, IGSF9, ASCC2, JUN, PPP2R5A, SMAD3, CREBBP, EP300, and DDX5 are genes found in the TGF-β, SMAD, and estrogen receptor signaling and mesenchymal morphology development pathways and are called the second gene group; TP53, HSF1, NCOA-6IP, PAWR, FAM96A, WTAP, PCNA, GNL3, WRN, SMARCA4, NCOA6, RPA1, MSH6, and PARP1 are genes related to the cell cycle, DNA damage response and repair, and mismatch repair and are called the third gene group.

[0066] The present inventors performed consensus clustering based on the expression levels of the above 32 genes, and found molecular subtypes divided into four groups, groups 1 to 4, based not only on manual examination of the consensus matrix but also on the consensus cumulative distribution function (CDF) plot and the delta area plot (Figure 1).

[0067] Tumors from patients in Group 1 expressed genes related to the cell cycle, DNA damage response and repair, and mismatch repair. Cancers from patients in Group 4 overexpressed genes found in the TGF-β, SMAD, and estrogen receptor signaling and mesenchymal morphogenesis pathways. Tumors from patients in Group 3 overexpressed genes in the apoptosis signaling and cell proliferation pathways. Tumors from Group 2 did not show a unique pattern of overexpressed genes. At this time, the presence or absence of overexpression was determined by relatively comparing the expression levels of 32 genes.

[0068] In univariate analysis, the molecular subtypes were significantly correlated with differences in age (P = 0.003), stage (P = 0.021), Lauren type (P < 0.001), and perineural invasion (P < 0.001). Finally, significant differences in overall survival were observed between the groups. Patients in Group 1 showed the best results, with a survival probability reaching approximately 70%, compared to less than 50% for all other groups of patients after 150 months. On the other hand, patients in Group 4 showed the worst results, with a median overall survival of 65 months (Figure 2; P < 0.001).

[0069] Multivariate Cox proportional-hazards analysis using significant variables for univariate analysis showed that age, stage, etc., and the molecular subtypes of the present invention were independently associated with the risk of death (Table 2). That is, this indicates that the 32-gene signature of the present invention can serve as a prognostic criterion that acts independently of known important clinical and pathological variables.

[0070]

Table 2

[0071] 2. Verification of the 32-Gene Prognostic Signature To examine the robustness and reproducibility of the 32-gene prognostic signature, the inventors of the present application analyzed the gene expression profiles of gastric cancer patients published by the Asian Cancer Research Group (ACRG; n = 300; Gene Expression Omnibus: GSE62254) and Sohn et al. (n = 267; Gene Expression Omnibus: GSE13861 and GSE26942) as independent data sets. Using the 32-gene signature, four molecular subtypes were identified again according to the present invention by unsupervised consensus clustering. The subtypes of the ACRG cohort were associated with age (P = 0.001), sex (P = 0.016), stage (P = 0.001), tumor location (P = 0.004), Lauren type (P < 0.001), perineural invasion (P < 0.001), EBV status (P = 0.03), and ACRG molecular subtype classification (P < 0.001; Table S5). The subtypes of the Sohn et al. cohort were significantly correlated with differences in sex (P = 0.032), Lauren type (P = 0.04), and TCGA molecular grouping (P < 0.001; Table S6).

[0072]

[0073] On the other hand, in both cohorts, it was confirmed that the molecular subtypes of the present invention were significantly associated with survival rates (Figures 3A and 3B). Multivariate Cox proportional-hazards analysis of cancer stage, Lauren type, tumor location, and molecular subtype associated with the risk of death in both the ACRG and Sohn et al. cohorts showed that in the molecular subtypes, there was a significant association with survival rates, especially between groups 1 and 4. Based on such analysis results, it was confirmed that the 32-gene signature could be an important prognostic biomarker.

[0074] Machine learning to identify a risk score for predicting 3.5-year overall survival <000G0281>Using the Yonsei cohort as a training set, the inventors of the present application constructed a support vector machine (SVM) with a linear kernel that uses the expression levels of 32 genes to evaluate the 5-year overall survival rate.

[0075] The inventors of the present application administered a negative label to group 1 with the best prognosis and a positive label to group 4 with the worst prognosis. The inventors of the present application tested the SVM model using data published by ACRG, Sohn, etc., and The Cancer Genome Atlas, and confirmed that the risk score, as a continuous variable, prognosticates the 5-year overall survival rate (Figure 4).

[0076] The inventors of the present application divided the cohort into quartiles based on the risk score. Patients in the lower quartile were classified as the low-risk group, patients within the interquartile range were classified as the intermediate-risk group, and patients in the upper quartile were classified as the high-risk group. The 5-year overall survival rates for the low-, intermediate-, and high-risk groups were 61% (95% CI, 55% - 69%), 50% (45% - 56%), and 35% (28% - 42%), respectively (B in Figure 3; P < 0.0001). Importantly, the risk score was associated with poor outcomes across all datasets and was prognostic independent of known clinical and pathological characteristics (Tables 3 and S13 - 15). These results demonstrated that the risk score derived from machine learning based on the 32-gene signature predicts the 5-year survival rate in gastric cancer patients.

[0077] 4. Molecular subtype prediction response to systemic treatment therapies It was examined whether the molecular subtype of the present invention can predict the response to systemic treatment therapies. The Yonsei cohort includes patients who were treated before the establishment of adjuvant chemotherapy as a standard treatment. Therefore, it was possible to compare patients treated by one of the following three adjuvant chemotherapy regimens with patients who underwent only surgery: - 5-fluorouracil (5-FU) monotherapy - 5-FU and platinum doublet - In addition to 5-FU, other classes of systemic treatment therapies

[0078] The inventors of the present application performed a multivariate Cox proportional analysis of overall survival, adjuvant chemotherapy regimens, cancer stage, age, lymphovascular invasion, and perineural invasion as covariates within each genetic group. The inventors of the present application revealed that patients treated with 5-FU and platinum in Group 3 showed significantly better overall survival compared to patients in Group 3 who did not receive adjuvant chemotherapy (hazard ratio (HR), 0.28 (95% CI, 0.08 - 0.96), p = 0.043). However, in contrast, patients in Group 1 treated with 5-FU and platinum showed a worse survival rate than patients in Group 1 who did not receive adjuvant treatment (HR, 6.80 (95% CI, 1.46 - 31.6), P = 0.015), (Figure 5). On the other hand, patients in Group 2 showed improved survival rates associated with 5-FU monotherapy (HR, 0.37 (95% CI, 0.14 - 0.99)), and the addition of other formulations was not correlated with improved outcomes. Such data suggest that the molecular subtypes of the present invention are predictive biomarkers for adjuvant treatment.

[0079] Next, it was examined whether the subtypes of the present invention could further predict the response to immune anti-cancer agents, such as immune checkpoint inhibitors. As a result of analyzing a cohort of patients with refractory, metastatic, and / or recurrent gastric cancer who received treatment with an anti-PD1 immune anti-cancer agent (Anti PD1 inhibitor), an anti-CTLA4 (Anti CTLA4) immune anti-cancer agent, or an anti-PDL1 (Anti PDL1) immune anti-cancer agent as immunotherapy, it was confirmed that the molecular subtypes of the present invention were also associated with both immunotherapy response and resistance (Figure 7).

[0080] Looking at the results of recent randomized control trials, the overall response rate (ORR) of refractory, metastatic, and / or recurrent gastric cancer patients treated with immune anti-cancer agents was less than 20% (12% in KEYNOTE-059 (Fuchs et al, JAMA ONC, 2018), 16%, KEYNOTE-061 (Shitara et al, Lancet, 2018), 11% in ATTRACTION-2 (Kang et al, Lancet, 2017)).

[0081] On the other hand, referring to the results in Figure 7, in the case of the molecular subtypes of the present invention, that is, the classification of patient groups using the first to third gene groups and the cancer prognosis prediction method based thereon, patient group 1 showed an overall response rate (ORR) of 50% (N = 10), and patient group 3 showed an overall response rate (ORR) of 67% for immune anti-cancer agent treatment. Therefore, according to the prognosis prediction method of the present invention, it can be seen that it is significantly more effective than the method of selecting patients who respond to currently used immune anti-cancer agents. In addition, according to the present invention, it was confirmed that the response to immune checkpoint inhibitors can also be predicted.

[0082]

Table 3

[0083] In Table 3 above, the hazard ratio (HR) was calculated with age, cancer stage, Lauren type, perineural invasion status, and chemotherapy treatment as adjustment factors.

[0084] 5. ACTA2 as a prognostic and predictive biomarker Among the 32 genes of the present invention, it was further investigated whether the expression of ACTA2 mRNA and protein can be used to predict the overall survival rate of patients, the response to chemotherapy and immunotherapy.

[0085] Therefore, first, patients from the Yonsei cohort were divided based on the mean value of ACTA mRNA expression. Patients with higher ACTA2 mRNA expression showed poorer overall survival compared to patients with lower ACTA2 mRNA expression (A in Figure 6).

[0086] Multivariate Cox proportional analysis of age, tumor stage, tumor location, Lauren type, and ACTA2 mRNA expression related to the risk of 5-year death in the ACRG and Sohn et al. cohorts also showed that a 1-unit increase in ACTA2 mRNA expression was significantly and independently associated with a higher risk regarding overall survival. The TCGA gastric cancer mRNA expression data further represented that there were statistically significant and different overall survival results in the high and low patient subgroups of ACTA2. survival results.

[0087] To demonstrate the prognostic utility of ACTA2 protein expression, the inventors of the present application performed immunohistochemical analysis using an anti-ACTCA2 monoclonal antibody. Analysis of stained formalin-fixed paraffin-embedded tissue sections from Seoul St. Mary Hospital (n = 396) confirmed the existence of a subgroup of gastric cancer patients who overexpressed ACTA2 protein in malignant epithelial and stromal cells. The patient subgroup with low ACTA2 protein expression showed a better prognosis compared to the patient subgroup with high ACTA2 protein expression (B in Figure 6).

[0088] The reading of ACTA2 immunohistochemistry was performed according to the reading criteria in Table 4 below. The reading was performed on the stromal cells around the tumor in the tissue microarray (TMA) of gastric cancer tissue. Based on the scores calculated by multiplying the staining intensity and the number of points in the staining area respectively, the patients were divided into two groups: Group 1 (ACTA2 low subgroup, score 0 - 3) and Group 2 (ACTA2 high subgroup, score 4 - 6), and the correlation with clinicopathologic factors and the difference in survival rates between the two groups were analyzed.

[0089]

Table 4

[0090] In addition, the ACTA2 mRNA expression levels in the response groups of patients who received immunotherapy at Samsung Medical Center (n = 45) were measured and analyzed. As a result, in the subgroup of patients resistant to immunotherapy agents, higher ACTA2 mRNA expression was confirmed compared to the subgroup of patients who responded to immunotherapy agents (Figure 8). In particular, among MSI-H patients, it was confirmed that patients who did not respond to immunotherapy agents showed high ACTA2 mRNA expression. Also, among MSS patients, it was confirmed that patients who responded to immunotherapy agents showed low ACTA2 mRNA expression.

[0091] That is, it was confirmed that ACTA2 is overexpressed in high-risk subgroups showing resistance to chemotherapy and immunotherapy.

[0092] 6. Combined evaluation of the biomarker of the present invention and high-frequency microsatellite instability (MSI-H, microsatellite instability high) diagnosis To examine the possibility of combining MSI diagnosis in conjunction with prognosis prediction using the biomarkers of the present invention, patients in the stomach cancer cohort of TCGA (The Cancer Genome Atlas) were divided into four subgroups based on MSI-H and MSS information, as well as the mRNA expression level of ACTA2, as follows (Figure 9).

[0093] 1) High subgroup with MSI-H and high ACTA2 2) Low subgroup with MSI-H and low ACTA2 3) High subgroup with MSS and high ACTA2 4) Low subgroup with MSS and low ACTA2

[0094] In addition, to analyze that there is a statistically significant difference in survival between such MSI-H / MSS and high / low subgroups of ACTA2, a KM plot was created using the overall survival of patients in each subgroup (Figure 10).

[0095] As a result, it was confirmed that there are subgroups with high and low mRNA expression levels of ACTA2 in gastric cancer patients with MSI-H and MSS (Figure 9), and it was also confirmed that there is a statistically significant difference in survival between such subgroups (Figure 10).

[0096] In particular, among gastric cancer patients with MSI-H or MSS, it was confirmed that patients with low mRNA expression level of ACTA2 (MSI-H or MSS + ACTA2 low) have a better prognosis compared to the patient subgroup with MSI-H or MSS and high ACTA2. Thus, it can be seen that the prognosis prediction of gastric cancer patients using the existing MSI-H can be made more accurately by combining high or low ACTA2 biomarkers.

[0097] In addition, a method for selecting gastric cancer patients who are sensitive to (or have a poor prognosis for) chemotherapeutic anticancer agents or immunotherapeutic anticancer agents via MSI-H biomarkers can, by means of a combination of ACTA2 biomarkers, distinguish between patients sensitive to chemotherapeutic anticancer agents and immunotherapeutic anticancer agents (e.g., MSI-H or MSS&ACTA2 low subgroups) and resistant patients (e.g., MSI-H or MSS&ACTA2 high subgroups).

[0098] As described above, the embodiments of the present invention have been described in detail. However, the scope of the rights of the present invention is not limited thereto, and it is obvious to those with ordinary knowledge in the art that various modifications and variations are possible without departing from the technical idea of the present invention described in the claims.

Claims

1. A preparation for measuring the expression level of mRNA or its protein of a gene in the first gene group containing ACTA2, wherein the preparation is a primer, probe, or antisense nucleotide that specifically binds to the mRNA of the gene, and is a composition for predicting the prognosis of gastric cancer.

2. The composition for predicting the prognosis of gastric cancer according to claim 1, wherein the composition for predicting the prognosis of gastric cancer is used for predicting the treatment prognosis of an anticancer therapy that is survival rate, chemo-sensitivity, chemo-resistance, immunotherapy sensitivity, immunotherapy resistance, or any combination thereof.

3. The composition for predicting the prognosis of gastric cancer according to claim 1, wherein the first gene group further includes at least one gene selected from the group consisting of ESR1, BEST1, HIPK2, IGSF9, ASCC2, JUN, PPP2R5A, SMAD3, CREBBP, EP300, and DDX5.

4. The composition for predicting the prognosis of gastric cancer according to claim 1, further comprising a preparation for measuring the expression level of mRNA or its protein of at least one gene selected from the second gene group consisting of FHL2, PML, BRCA1, WT1, AREG, and TP63.

5. The composition for predicting the prognosis of gastric cancer according to claim 1, further comprising a preparation for measuring the expression level of mRNA or its protein of at least one gene selected from the third gene group consisting of TP53, HSF1, NCOA6IP, PAWR, FAM96A, WTAP, PCNA, GNL3, WRN, SMARCA4, NCOA6, RPA1, MSH6, and PARP1.

6. Measuring the expression level of mRNA or its protein of a gene in the first gene group containing ACTA2 using the composition for predicting the prognosis of gastric cancer according to claim 1 or 3, and the measured expression level of mRNA or its protein of the gene in the first gene group, A method for predicting the prognosis of gastric cancer, comprising: comparing the expression level of mRNA or its protein of at least one gene selected from the second gene group using the composition for predicting the prognosis of gastric cancer according to claims 4 and 5; and comparing the expression level of mRNA or its protein of at least one gene selected from the third gene group.

7. The prognosis according to claim 6, wherein the prognosis is survival rate, chemo-sensitivity, chemo-resistance, immunotherapy sensitivity, immunotherapy resistance, or any combination thereof.

8. The method for predicting the prognosis of gastric cancer according to claim 6, further comprising: when the expression level of mRNA or its protein of at least one gene selected from the group consisting of ESR1, BEST1, HIPK2, IGSF9, ASCC2, JUN, PPP2R5A, SMAD3, CREBBP, EP300, and DDX5 in the first gene group is relatively high, determining that the prognosis of chemotherapy treatment is poor and the prognosis of chemoimmunotherapy treatment is poor.

9. The method for predicting the prognosis of gastric cancer according to claim 6, further comprising: when the expression level of mRNA or its protein of at least one gene in the second gene group selected from the group consisting of FHL2, PML, BRCA1, WT1, AREG, and TP63 is relatively high using the composition according to claim 4, determining that the prognosis of chemotherapy treatment and immunotherapy treatment is good.

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