Method for predicting prognosis of colorectal cancer using HSPD1 gene mRNA or HSP60 protein encoded by these genes

Abstract

The present invention relates to a biomarker for predicting the prognosis of colorectal cancer by using changes in the expression level of HSPD1 gene mRNA or HSP60 protein encoded by these genes, and a method for predicting prognosis using the same. By analyzing the expression level of HSPD1 gene or HSP60 protein, the prognosis of colorectal cancer patients can be predicted in clinical practice, and by performing the analysis in combination with TNM classification, more advanced prediction is possible and personalized strategies can be designed.

Description

[Technical Field]

[0001] The present invention relates to a method for predicting the prognosis of colorectal cancer using the mRNA of the HSPD1 gene or the HSP60 protein encoded by this gene. [Background technology]

[0002] The digestive system is divided into the esophagus, stomach, small intestine, and large intestine. The large intestine is the final part of the digestive system and is where water and electrolyte absorption primarily occurs. The large intestine is divided into the colon, cecum, and rectum, which is further divided into the ascending colon, transverse colon, descending colon, and sigmoid colon. Depending on the location of the cancer, cancer occurring in the colon is called colon cancer, and cancer occurring in the rectum is called rectal cancer, collectively referred to as colorectal cancer. The approximate incidence of cancer in each region of the large intestine is known to be 25% in the cecum and ascending colon, 15% in the transverse colon, 5% in the descending colon, 25% in the sigmoid colon, 10% in the rectosigmoid junction, and 20% in the rectum.

[0003] The large intestine is a pipe-like tube divided into four layers from the inside out: the mucosa, submucosa, muscularis, and serosal layer. Most colorectal cancers are adenocarcinomas that originate in the mucosa of the colon, but others include lymphomas, sarcomas, squamous cell carcinomas, and metastatic lesions from other cancers.

[0004] The causes of colorectal cancer can be broadly divided into environmental and genetic factors. Although the cause of colorectal cancer remains unknown, it is believed that environmental factors play a greater role in the development of colorectal cancer than genetic factors, and the rapid Westernization of the diet, particularly excessive intake of animal fats and proteins, is recognized as a contributing factor. However, approximately 5% of colorectal cancers are thought to be caused by genetic predisposition.

[0005] The relationship between diet and colorectal cancer is one of the most studied areas, and changes in where people live (e.g., due to migration) may alter the incidence of colorectal cancer based on regional characteristics, regardless of genetic differences. In particular, high calorie intake, excessive animal fat intake, high-fat diet, obesity, low fiber intake, weight gain, inflammatory bowel disease, and colorectal polyps are known to increase the risk of colorectal cancer.

[0006] Biomarkers are becoming a major tool for advancing personalized medicine, and can be divided into nucleic acid-based biomarkers (based on DNA and RNA) and protein-based biomarkers (based on proteins and their moieties). These biomarkers have recently been applied to the early diagnosis of various intractable diseases, such as cancer, infectious diseases, cardiovascular diseases, stroke, and dementia, as well as to the diagnosis and treatment of drug response.

[0007] Despite the use of various existing treatment methods (surgery, chemotherapy, and radiation therapy), most patients with cancer, including colorectal cancer, die primarily as a result of cancer metastasis. While most patients with a primary tumor present before cancer metastasis have a high chance of recovery, detecting such patients is difficult, and in most patients, cancer metastasis is already discovered by the time the primary tumor is present. Most cancer metastases are multiple and systemic, making their presence difficult to detect, which explains why current cancer treatments do not provide satisfactory therapeutic effects. However, cancer metastasis is an inefficient process, with only a small proportion of cancer cells constituting the primary tumor successfully completing the various stages of the metastatic process and becoming metastatic. Therefore, by better understanding the metastatic process, discovering clinically and biologically useful therapeutic targets, and developing methods to effectively inhibit them, it will be possible to develop useful therapies that can effectively control death from cancer metastasis. Furthermore, early prognosis prediction and early diagnosis of high-risk groups for cancer metastasis could be useful for future treatment planning and individualized treatment for each patient based on the prognosis.

[0008] As prior art, Korean Patent Publication No. 1020170089316 discloses a method for diagnosing cancer by reacting HSP60 protein present in a sample isolated from a patient suspected of having cancer with hydroxylamine and confirming degradation of the HSP60 protein. Korean Patent Registration No. 101307132 discloses that inhibiting HSP60 has a therapeutic effect on abnormal cell proliferation diseases such as cancer or hyperproliferative vascular disorders by blocking the interaction between HSP60 and the IKK complex, thereby inactivating the NF-kB pathway and inducing apoptosis. Meanwhile, a non-patent document by Ce'line Hamelin et al. [FEBS Journal 278 (2011) 4845-4859] measured the expression level of HSP60 protein in the colorectal tissues of healthy subjects and colorectal cancer patients and reported that HSP60 protein expression was significantly increased in the tissues of colorectal cancer patients.

[0009] Therefore, in order to find biomarkers that can predict the prognosis of colorectal cancer, the inventors identified HSPD1 gene or HSP60 protein that has differential expression in colorectal cancer tissues obtained from colorectal cancer patients and analyzed them in conjunction with survival analysis. As a result, it was confirmed that the prognosis of colorectal cancer patients can be predicted using HSPD1 gene or HSP60 protein. Furthermore, the present invention was completed by confirming that the prognosis of colorectal cancer patients can be more accurately predicted by linking the expression of HSPD1 gene or HSP60 protein with TNM stage (tumor, node, and metastasis stage). Summary of the Invention

[0010] An object of the present invention is to provide a biomarker for predicting the prognosis of colorectal cancer patients and a method for predicting the prognosis using the biomarker.

[0011] To achieve the above object, the present invention provides a composition for predicting the prognosis of colorectal cancer patients, the composition comprising an agent for measuring the level of HSPD1 gene mRNA or the HSP60 protein encoded by this gene.

[0012] The present invention also provides a kit for predicting the prognosis of a colorectal cancer patient, the kit comprising a composition containing an agent for measuring the level of HSPD1 gene mRNA or the HSP60 protein encoded by this gene.

[0013] The present invention also provides a method for predicting the prognosis of a colorectal cancer patient, the method comprising: (a) measuring the level of HSPD1 gene mRNA or the HSP60 protein encoded by these genes in a sample isolated from a colorectal cancer patient; and (b) comparing the measured mRNA level or its protein level with the mRNA level or its protein level in a control sample; Includes:

[0014] The present invention also provides a method for predicting the prognosis of a colorectal cancer patient, the method comprising: (a) measuring the level of HSPD1 gene mRNA or the HSP60 protein encoded by these genes in a sample isolated from a colorectal cancer patient; (b) comparing the measured mRNA level or its protein level with the mRNA level or its protein level of a control sample; and (c) Combining and analyzing the information classified according to TNM stages Includes: [Effects of the Invention]

[0015] The present invention relates to a biomarker for predicting the prognosis of colorectal cancer by using changes in the expression level of HSPD1 gene mRNA or HSP60 protein encoded by these genes, and a method for predicting prognosis using the same. By analyzing the expression level of the HSPD1 gene or HSP60 protein, the prognosis of colorectal cancer patients can be predicted in clinical practice, and by performing the analysis in combination with the TNM classification, more advanced predictions can be made and personalized strategies can be designed. [Brief explanation of the drawings]

[0016] [Figure 1A] 1 is a graph showing overall survival analysis according to HSPD1 expression levels in the TCGA COAD dataset. [Figure 1B] FIG. 1B shows a hazard ratio analysis of FIG. 1A. [Figure 1C] 1 is a graph showing recurrence-free survival analysis according to HSPD1 expression levels in the TCGA COAD dataset. [Figure 1D] FIG. 1C shows a hazard ratio analysis of FIG. 1C. [Figure 2A] 1 is a graph showing the results of an overall survival analysis combining HSPD1 expression levels and TNM classification in the TCGA COAD dataset. [Figure 2B] FIG. 1 shows the results of an overall survival analysis combining HSPD1 expression levels and TNM classification in the TCGA COAD dataset. [Figure 2C] FIG. 1 shows overall survival analysis according to HSPD1 expression levels at late TNM stages (stages 3 and 4) in the TCGA COAD dataset. [Figure 3A] 1 is a graph showing the results of a recurrence-free survival analysis combining HSPD1 expression levels and TNM classification in the TCGA COAD dataset. [Figure 3B] FIG. 1 shows the results of a recurrence-free survival analysis combining HSPD1 expression levels and TNM classification in the TCGA COAD dataset. [Figure 3C] FIG. 1 shows recurrence-free survival analysis according to HSPD1 expression levels at late TNM stages (stages 3 and 4) in the TCGA COAD dataset. [Figure 4] A series of photographs showing the results of immunochemical staining of HSP60 in tumor cells (A: unstained normal colon epithelial cells, B: unstained tumor cells, C: tumor cells showing weak cytoplasmic staining, D: tumor cells showing moderate cytoplasmic staining, E: tumor cells showing strong cytoplasmic staining) (magnification: 400x). [Figure 5A] 1 is a graph showing event-free survival analysis according to protein expression levels of HSP60 in the GMC (Gachon University Gil Medical Center) colorectal cancer cohort. [Figure 5B] FIG. 5B shows a hazard ratio analysis of FIG. 5A. [Figure 5C] 1 is a graph showing disease-specific survival analysis according to protein expression levels of HSP60 in the GMC (Gachon University Gil Medical Center) colorectal cancer cohort. [Figure 5D] FIG. 5B shows a hazard ratio analysis of FIG. 5C. [Figure 6A] 1 is a graph showing event-free survival analysis by combining protein expression levels of HSP60 and TNM stage. [Figure 6B] FIG. 1 shows event-free survival analysis by combining protein expression levels of HSP60 and TNM stage. [Figure 6C] FIG. 1 shows event-free survival analysis according to expression levels of HSP60 at late TNM stages (stages 3 and 4) in the GMC colorectal cancer cohort. [Figure 7A] 1 is a graph showing disease-specific survival analysis by combining protein expression levels of HSP60 and TNM stage in the GMC colorectal cancer cohort. [Figure 7B]FIG. 1 shows disease-specific survival analysis by combining protein expression levels of HSP60 and TNM stage in the GMC colorectal cancer cohort. [Figure 7C] FIG. 1 shows disease-specific survival analysis according to HSP60 expression levels at late TNM stages (stages 3 and 4) in the GMC colorectal cancer cohort. DETAILED DESCRIPTION OF THE INVENTION

[0017] DESCRIPTION OF THE PREFERRED EMBODIMENT The present invention will be described in detail below.

[0018] The present invention provides a composition for predicting the prognosis of a colorectal cancer patient, the composition comprising an agent for measuring the level of HSPD1 gene mRNA or the HSP60 protein encoded by this gene.

[0019] HSPD1 (heat shock protein family D (Hsp60) member 1) encodes a protein commonly known as HSP60 (also known as Cpn60). This protein is a mitochondrial protein and a type of heat shock protein that suppresses cell damage in response to high temperatures (heat). Heat shock proteins act as chaperones, binding to proteins that do not display a complete three-dimensional structure, preventing intermolecular association and promoting renaturation. Heat shock proteins also bind to immature proteins immediately after synthesis, playing important roles in their higher-order refolding, intracellular transport, and organelle membrane permeabilization, and are known to covalently bind to denatured proteins and mediate their degradation by the proteasome.

[0020] Agents that measure the level of mRNA may include, but are not necessarily limited to, primers or probes.

[0021] The primer is a nucleic acid sequence with a short free 3' hydroxyl group that can form complementary base pairs with a template and serve as a starting point for replicating the template strand. A primer can initiate DNA synthesis in the presence of a polymerization reagent (i.e., DNA polymerase or reverse transcriptase) and four different nucleoside triphosphates in an appropriate buffer at an appropriate temperature.

[0022] The probe may be any probe capable of binding complementarily to the target gene, and the nucleotide sequence of the probe is not limited as long as it is capable of binding complementarily to each gene.

[0023] Methods for measuring mRNA expression levels include, but are not limited to, RT-PCR (reverse transcription polymerase chain reaction), competitive RT-PCR, real-time RT-PCR, RNase protection assay (RPA), Northern blotting, and methods using DNA chips.

[0024] The agent for measuring the level of a protein can be an antibody, a peptide, an aptamer or a compound specific for the protein.

[0025] The antibody refers to a protein molecule capable of specifically binding to an antigenic site on a protein or peptide molecule. Such antibodies can be produced by conventional methods, such as cloning each gene into an expression vector to obtain a protein encoded by a marker gene. The antibody may be in any form, including polyclonal antibodies, monoclonal antibodies, or portions thereof that have antigen-binding activity, including any immunoglobulin antibody. The antibody may also include specialized antibodies such as humanized antibodies. Furthermore, antibodies include functional fragments of antibody molecules, as well as intact forms comprising two full-length light chains and two full-length heavy chains. A functional fragment of an antibody molecule refers to a fragment that retains at least the antigen-binding function, and may be Fab, F(ab'), F(ab')2, Fv, or the like.

[0026] The above peptides have the advantage of being highly avid for target substances and not denatured even when treated with heat or chemicals. Furthermore, due to their small molecular size, they can be attached to other proteins to form fusion proteins. Specifically, they can be attached to polymer protein chains that can be used as diagnostic kits and drug delivery materials.

[0027] The term "aptamer" refers to a single-stranded oligonucleotide, a nucleic acid molecule that has binding activity to a specific target molecule. Aptamers can have various three-dimensional structures depending on their nucleotide sequence and can have high affinity for specific substances, such as antigen-antibody reactions. By binding to a target molecule, aptamers can inhibit the activity of a specific target molecule. Similar to antibodies, aptamers can specifically bind to antigenic substances. However, aptamers are more stable than proteins, have a simpler structure, and are composed of polynucleotides that are easier to synthesize, making them suitable as an alternative to antibodies.

[0028] Methods for measuring protein levels include, but are not limited to, Western blot, enzyme-linked immunosorbent assay (ELISA), radioimmunoassay (RIA), radioimmunodiffusion, Ouchterlony immunodiffusion, rocket immunoelectrophoresis, tissue immunostaining, immunoprecipitation assay, complement fixation assay, FACS, and DNA chip-based methods.

[0029] The present invention also provides a kit for predicting the prognosis of a colorectal cancer patient, the kit comprising a composition containing an agent for measuring the level of HSPD1 gene mRNA or the HSP60 protein encoded by this gene.

[0030] The kit may include, but is not necessarily limited to, an RT-PCR kit, a DNA chip kit, an ELISA kit, a protein chip kit, a rapid kit, or an MRM (multiple reaction monitoring) kit.

[0031] The present invention also provides a method for predicting the prognosis of a colorectal cancer patient, the method comprising: (a) measuring the level of HSPD1 gene mRNA or the HSP60 protein encoded by these genes in a sample isolated from a colorectal cancer patient; and (b) comparing the measured mRNA level or its protein level with the mRNA level or its protein level in a control sample; Includes:

[0032] If the expression level of HSPD1 gene mRNA or the HSP60 protein encoded by these genes is higher than that of the control group, it can be determined that the prognosis is likely to be good.

[0033] The above determination of good prognosis may mean that overall survival, recurrence-free survival, event-free survival, and disease-specific survival are higher than in a poor prognosis group.

[0034] The sample in step (a) above may be colon tissue.

[0035] The present invention also provides a method for predicting the prognosis of a colorectal cancer patient, the method comprising: (a) measuring the level of HSPD1 gene mRNA or the HSP60 protein encoded by these genes in a sample isolated from a colorectal cancer patient; (b) comparing the measured mRNA level or its protein level with the mRNA level or its protein level of a control sample; and (c) Combining and analyzing the information classified according to TNM stages Includes:

[0036] TNM stage is one method of determining the stage of a tumor. T stands for tumor, and is divided into T0 (no primary tumor), Tis (carcinoma in situ), and T1-T4 (the higher the number, the more extensive the surrounding area is). N stands for node (lymph node), and is divided into N0 (no lymph node metastasis), N1-N3, and other stages depending on the number, size, and location of the invaded lymph nodes. M stands for metastasis, and is divided into M0 (no metastasis), M1 (metastasis), and other stages depending on the presence or absence of distant metastasis. Once T, N, and M are determined using the above methods, they are combined to determine the final stage of the disease. This stage is crucial for determining treatment plans and prognosis.

[0037] Information categorized according to the above TNM stage is the most common method of providing cancer prognosis information, and can be divided into stages 1 to 4. However, in order to simplify the staging, the TNM stage does not include all important variables that affect prognosis, so there is a problem that it is incomplete in predicting the prognosis of individual patients.

[0038] In our event-free survival analysis, events were defined as cancer progression, cancer recurrence, and death from colorectal cancer.

[0039] In our disease-specific survival analysis, deaths due to colorectal cancer were categorized as deaths (events) and censored deaths due to causes other than colorectal cancer were categorized as survival.

[0040] The present invention will now be described in detail with reference to the following experimental examples.

[0041] However, the following experimental examples are merely for the purpose of illustrating the present invention, and the contents of the present invention are not limited thereto.

[0042] Experimental Example 1: Predicting survival of colorectal cancer patients using the HSPD1 gene <1-1> Confirmation of the correlation between colorectal cancer and HSPD1 gene expression To confirm the correlation between colorectal cancer and HSPD1 gene expression, we performed an analysis using genome databases.

[0043] Specifically, for survival analysis of HSP60 expression in colorectal cancer patients, we downloaded gene expression and clinical information datasets from the Colon Adenocarcinoma (COAD) dataset of The Cancer Genome Atlas (TCGA) project from the UCSC Cancer Genomics Browser1 (last accessed December 3, 2017). Survival analysis was performed on 272 samples with 5-year overall survival (OS) and recurrence-free survival (RFS) data among primary tumor samples with expression of HSPD1, the gene encoding HSP60.

[0044] The optimal cut point for gene expression levels of HSPD1 was determined using MaxStat function 2 in R software. For overall survival (OS) analysis, patients were categorized as follows: 高 group (HSPD1 expression level > 14.1791) or HSPD1 (HSP60) 低 For recurrence-free survival (RFS) analysis, patients were categorized into HSPD1 (HSP60) and HSPD1 (HSPD1 expression level ≤ 14.1791) groups. 高 group (HSPD1 expression level > 14.1211) or HSPD1 (HSP60) 低 Patients were classified into groups (HSPD1 expression level ≤ 14.1211). Survival analysis by HSPD1 expression level was performed using the log-rank test, a univariate analysis. Results of multivariate analysis were adjusted for sex and age using the Cox proportional hazards (CPH) model. The log-rank test for survival analysis and CPH modeling were performed using the survival package in R version 4.0. Hazard ratios for each variable obtained from CPH modeling were visualized using the forest model package and used in R version 4.0.

[0045] As shown in Figures 1A and 1B, the overall survival hazard ratio for the low HSPD1 gene expression group was 1.87 (95% confidence interval [CI]: 0.95-3.69), indicating a trend toward a worse prognosis than the high HSPD1 gene expression group. As shown in Figures 1C and 1D, the recurrence-free survival hazard ratio for the low HSPD1 gene expression group was 1.87 (95% confidence interval [CI]: 0.94-3.73), indicating a statistically significantly worse prognosis than the high HSPD1 gene expression group.

[0046] The above results suggest that patients with high HSPD1 expression have a survival advantage compared with patients with low HSPD1 expression.

[0047] <1-2> Prediction of survival in colorectal cancer patients by combining TNM stage and HSPD1 gene expression level Survival prediction was analyzed by combining TNM stage (tumor, node, metastasis stage) and gene expression levels of HSPD1, which are recognized as the best-performing biomarkers for predicting survival in colorectal cancer patients.

[0048] Specifically, high HSPD1 gene expression (hereinafter referred to as HSPD1 (HSP60) 高 Patients with low HSPD1 gene expression (hereafter referred to as HSPD1 (HSP60)) and TNM stage 1 / 2 were grouped into group 1 and group 2, respectively. 低 Patients with TNM stage 1 / 2 were grouped into group 2, and patients with HSPD1 (HSP60) 高 Patients with TNM stage 3 / 4 were grouped into group 3, and HSPD1 (HSP60) 低 Patients with TNM stage 3 / 4 were divided into group 4, and 5-year overall survival and recurrence-free survival analyses were performed.

[0049] As shown in Figures 2A and 2B, when overall survival was analyzed by combining HSPD1 expression and TNM stage, the overall survival hazard ratio (OSR) for Group 2 was 1.04 times (95% CI: 0.35-3.10) higher than that for Group 1, the OSR for Group 3 was 2.02 times (95% CI: 0.61-9.69), and the OSR for Group 4 was 5.00 times (95% CI: 1.85-13.52; log-rank test p-value: 0.002) higher than that for Group 1. As shown in Figure 2C, in patients with the same stage (TNM stage 3 / 4), the OSR for the group with low HSPD1 expression (Group 4) was 2.21, indicating a trend toward a worse prognosis than the group with high HSPD1 expression (Group 3).

[0050] Furthermore, as shown in Figures 3A and 3B, when recurrence-free survival was analyzed by combining HSPD1 expression and TNM stage, the recurrence-free survival hazard ratio for Group 2 was 1.10 times higher (95% CI: 0.40-3.04) than that for Group 1, the recurrence-free survival hazard ratio for Group 3 was 1.45 times higher (95% CI: 0.44-4.75), and the recurrence-free survival hazard ratio for Group 4 was 3.76 times higher (95% CI: 1.49-9.53, log-rank test p-value: 0.005) than that for Group 1. As shown in Figure 3C, in patients with the same stage (TNM stage 3 / 4), the recurrence-free survival hazard ratio for the group with low HSPD1 expression (Group 4) was 2.48, indicating a trend toward a worse prognosis than the group with high HSPD1 expression (Group 3).

[0051] Experimental Example 2: Predicting survival of colorectal cancer patients using HSP60 protein <2-1> Survival analysis by HSP60 protein expression To perform survival analysis based on the expression level of HSP60 protein encoded by the HSPD1 gene, tissue microarrays were constructed from tumor tissues derived from colorectal cancer patients, and the expression level of HSP60 protein was quantified by immunohistochemical staining.

[0052] Specifically, the study was conducted on patients who underwent surgery for colorectal cancer at Gachon University Gil Medical Center (GMC) between April 2010 and January 2013. Patients who underwent surgery for primary colorectal cancer and patients whose tumors were preserved in paraffin blocks were included in the study, resulting in a total of 456 patients analyzed. Patients with recurrent colorectal cancer, patients whose normal colonic architecture had been altered by previous surgery, patients who received chemotherapy or abdominal radiation therapy before colorectal cancer surgery, and patients who had received treatment for other cancers before colorectal cancer surgery were excluded. After microdissecting the paraffin blocks, hematoxylin and eosin (H&E) staining was performed. The pathological findings were reviewed, and two tumor cores were marked on the corresponding paraffin blocks. Cylindrical tumor tissues with a diameter of 2 mm were extracted using a tissue microarray device and transferred to new paraffin blocks. New tissue microarray (TMA) blocks were created by inserting each tissue cylinder from 69 patients into a single paraffin block. The TMA blocks were cut into 4 μm-thick sections using a microtome, flattened by smoothing, and attached to slides in a fixed orientation and allowed to dry. Immunohistochemical staining was then performed using the dried slides. The slides were treated at 60°C for 10 minutes, deparaffinized with xylene, rehydrated using different concentrations of alcohol (100%, 95%, 80%, and 70% alcohol), and then washed with distilled water. For antigen retrieval, 10 mM citrate buffer (2.1 g citric acid in 1 L H2O, pH 6.0) was heated, and once boiling began, the slides were placed in the solution and boiled for another 10 minutes. The slides were then washed in cold water for 10 minutes, removed, and washed in PBS buffer (8 g NaCl, 200 mg KCl, 1.44 g Na2HPO4, 24 mg KH2PO4 in 1 L H2O). Endogenous peroxidase activity was then inhibited by treatment with 3% hydrogen peroxide for 10 minutes, and the antigens were retrieved in 0.01 M sodium citrate buffer (pH 6.0) using a microwave oven.To prevent nonspecific reactions, slides were incubated with a blocking antibody (DAKO #X0909; Glostrup, Denmark) for 10 minutes at room temperature, and samples were incubated with anti-HSP60 (rabbit monoclonal, 1:200, D6F1, Cell signaling technology, USA) in a humidified container at 4°C. Tissue slides were treated with a non-biotinylated horseradish peroxidase (HRP) detection system according to the manufacturer's instructions (Gene Tech).

[0053] Statistical analysis was performed as follows. In this study, survival-related factors and survival rates 5 years after surgery for colorectal cancer were the focus of event-free survival and disease-specific survival analyses. In event-free survival analysis, events were defined as cancer progression, cancer recurrence, and death from colorectal cancer. Disease-specific survival was defined as the time from surgery to death from colorectal cancer, excluding death from diseases other than colorectal cancer. Log-rank tests and Cox proportional hazards (CPH) modeling for survival analysis were performed using the survival package in R version 4.0. Hazard ratios for each variable obtained from CPH modeling were visualized using the forest model package and used in R version 4.0.

[0054] The results of immunochemical staining of HSP60 in normal colon epithelial cells and tumor cells are shown in Figure 4. Figure 4A is a photograph showing unstained tumor cells, Figure 4B is a photograph showing tumor cells with weak cytoplasmic staining, Figure 4C is a photograph showing tumor cells with moderate cytoplasmic staining, and Figure 4D is a photograph showing tumor cells with strong cytoplasmic staining.

[0055] Statistical analysis confirmed that the event-free survival of colorectal cancer patients differed significantly depending on their HSP60 protein expression level, as shown in Figures 5A and 5B. The event-free survival hazard rate for patients with low HSP60 protein expression was 1.42-fold higher (95% CI: 1.01-2.00) than for patients with high HSP60 protein expression. The CPH model adjusted for gender and age showed a statistically significant p-value of 0.04. Furthermore, as shown in Figures 5C and 5D, the disease-specific survival of colorectal cancer patients differed significantly depending on their HSP60 protein expression level. The disease-specific survival hazard rate for patients with low HSP60 protein expression was 1.69-fold higher (95% CI: 1.17-2.44) than for patients with high HSP60 protein expression. The CPH model adjusted for gender and age showed a statistically significant p-value of 0.005.

[0056] The above results suggest that patients with high HSP60 expression have a survival advantage compared with patients with low HSP60 expression.

[0057] <2-2> Prediction of survival in colorectal cancer patients by combining TNM stage and HSP60 protein expression level Survival prediction was analyzed by combining TNM stage and protein expression level of HSP60.

[0058] Specifically, high HSP60 protein expression (hereinafter referred to as HSP60 高 Patients with low HSP60 protein expression (hereafter referred to as HSP60) and TNM stage 1 / 2 were grouped into group 1. 低 Patients with TNM stage 1 / 2 were grouped into group 2, and HSP60 高 Patients with TNM stage 3 / 4 were grouped into group 3, and HSP60 低Patients with TNM stage 3 / 4 were divided into group 4, and 5-year event-free survival and disease-specific survival analyses were performed. Survival analysis was performed using the log-rank test, univariate analysis, and CPH modeling and multivariate analysis. The log-rank test and CPH modeling for survival analysis were performed using the survival package in R version 4.0. Hazard ratios for each variable obtained from CPH modeling were visualized using the forest model package and used in R version 4.0.

[0059] As shown in Figures 6A and 6B, when event-free survival was analyzed by combining HSP60 and TNM stage, the event-free survival hazard ratio for Group 3 was 4.18 times higher than that for Group 1 (95% CI: 2.33–7.49, p < 0.001), and the event-free survival hazard ratio for Group 4 was 7.21 times higher than that for Group 1 (95% CI: 4.05–12.83, p < 0.001). As shown in Figure 6C, in patients with the same stage (TNM stage 3 / 4), the event-free survival hazard ratio for the group with low HSP60 expression was 1.70, showing a trend toward a significantly worse prognosis than the group with high HSP60 expression (p = 0.009). This suggests that combining HSP60 expression with TNM stage may provide better performance in predicting survival. The above results suggest that combining HSP60 expression and TNM stage may provide better survival prediction performance than using TNM stage alone to predict survival.

[0060] Furthermore, as shown in Figures 7A and 7B, when disease-specific survival was analyzed by combining HSP60 and TNM stage, the disease-specific survival hazard ratio for Group 3 was 4.52-fold higher (95% CI: 2.31–8.83, p<0.001) than that for Group 1, and the disease-specific survival hazard ratio for Group 4 was 9.40-fold higher (95% CI: 4.89–18.07, p<0.001) than that for Group 1. As shown in Figure 7C, in patients with the same stage (TNM stage 3 / 4), the disease-specific survival hazard ratio for the group with low HSP60 expression was 2.02, indicating a trend toward a significantly worse prognosis than the group with high HSP60 expression (p=0.001).

[0061] These results confirmed that a combination of HSP60 expression level and TNM stage could predict survival better than TNM stage alone, suggesting that the combination of HSP60 expression level and TNM stage as a biomarker could provide better performance in survival prediction. The present disclosure includes, for example, the embodiments described in the following sections. [Section 1] A composition for predicting the prognosis of a colorectal cancer patient, comprising an agent for measuring the level of HSPD1 gene mRNA or the HSP60 protein encoded by this gene. [Section 2] Item 2. The composition for predicting the prognosis of a colorectal cancer patient according to Item 1, wherein the agent for measuring the mRNA level is a primer or probe that specifically binds to the gene. [Section 3] Item 1. A composition for predicting the prognosis of a colorectal cancer patient according to Item 1, wherein the agent for measuring the protein level comprises an antibody, peptide, aptamer, or compound specific to the protein. [Section 4] Item 1. A kit for predicting the prognosis of a colorectal cancer patient, comprising the composition according to Item 1. [Section 5] 1. A method for predicting the prognosis of a patient with colorectal cancer, comprising: (a) measuring the level of HSPD1 gene mRNA or the HSP60 protein encoded by these genes in a sample isolated from a colorectal cancer patient; and (b) comparing the measured mRNA level or its protein level with the mRNA level or its protein level in a control sample; A method comprising: [Section 6] Item 6. The method for predicting the prognosis of a colorectal cancer patient according to Item 5, wherein the prognosis is determined to be good when the level of HSPD1 gene mRNA or the HSP60 protein encoded by these genes is higher than that of a control group. [Section 7] Item 6. The method for predicting the prognosis of a colorectal cancer patient according to Item 5, wherein the prognosis is determined to be poor when the level of HSPD1 gene mRNA or the HSP60 protein encoded by these genes is lower than that of a control group. [Section 8] Item 6. The method for predicting the prognosis of a colorectal cancer patient according to Item 5, wherein the sample in step (a) is colon tissue. [Section 9] 1. A method for predicting the prognosis of a patient with colorectal cancer, comprising: (a) measuring the level of HSPD1 gene mRNA or the HSP60 protein encoded by these genes in a sample isolated from a colorectal cancer patient; (b) comparing the measured mRNA level or its protein level with the mRNA level or its protein level of a control sample; and (c) Combining and analyzing the information classified according to TNM stage (tumor, node, metastasis stage). A method comprising: [Section 10] Item 10. The method for predicting the prognosis of a colorectal cancer patient according to Item 9, wherein the prognosis is determined to be good when the level of HSPD1 gene mRNA or the HSP60 protein encoded by these genes is higher than that of a control group of the same TNM stage. [Section 11] Item 10. The method for predicting the prognosis of a colorectal cancer patient according to Item 9, wherein the prognosis is determined to be poor when the level of HSPD1 gene mRNA or the HSP60 protein encoded by these genes is lower than that of a control group of the same TNM stage.

Claims

1. A composition for predicting the prognosis of a colorectal cancer patient, comprising an agent for measuring the level of HSPD1 gene mRNA or HSP60 protein encoded by the HSPD1 gene in colon tissue isolated from a colorectal cancer patient; where: The prognosis is determined to be good when the level of mRNA or protein measured by the drug is higher than that of a control group of colorectal cancer patients at the same TNM stage; If the level of mRNA or protein measured by the agent is lower than that of a control group of colorectal cancer patients at the same TNM stage, the prognosis is determined to be poor.

2. The composition for predicting the prognosis of a colorectal cancer patient according to claim 1 , wherein the agent for measuring the mRNA level is a primer or probe that specifically binds to the gene.

3. The composition for predicting the prognosis of a colorectal cancer patient according to claim 1 , wherein the agent for measuring the protein level comprises an antibody, peptide, aptamer or compound specific to the protein.

4. A kit for predicting the prognosis of a colorectal cancer patient, comprising the composition of claim 1, determining the prognosis as good if the level of mRNA or protein measured by the agent is higher than that of a control group of colorectal cancer patients at the same TNM stage; If the level of mRNA or protein measured by the agent is lower than that of a control group of colorectal cancer patients at the same TNM stage, the prognosis is determined to be poor. A kit for predicting the prognosis of colorectal cancer patients.

5. 1. A method for predicting the prognosis of a patient with colorectal cancer, comprising: (a) measuring the level of HSPD1 gene mRNA or HSP60 protein encoded by the HSPD1 gene in colon tissue isolated from a colorectal cancer patient; and (b) comparing the measured mRNA level or its protein level with the mRNA level or its protein level in a control sample; A method comprising: where: When the level of the mRNA of the HSPD1 gene or the HSP60 protein encoded by the HSPD1 gene is higher than that of a control group of colorectal cancer patients at the same TNM stage, the prognosis is determined to be good; When the level of the mRNA of the HSPD1 gene or the HSP60 protein encoded by the HSPD1 gene is lower than that of a control group of colorectal cancer patients at the same TNM stage, the prognosis is determined to be poor.

6. 1. A method for predicting the prognosis of a patient with colorectal cancer, comprising: (a) measuring the level of HSPD1 gene mRNA or HSP60 protein encoded by the HSPD1 gene in colon tissue isolated from a colorectal cancer patient, thereby obtaining information about the level of the HSPD1 gene mRNA or the level of the HSP60 protein; (b) comparing the information obtained by step (a) with the mRNA level of the HSPD1 gene or the protein level of HSP60 encoded by the HSPD1 gene in a control group of colorectal cancer patients at the same TNM stage; and (c) the prognosis is judged to be good when the level of the mRNA of the HSPD1 gene or the HSP60 protein encoded by the HSPD1 gene is higher than that of a control group of colorectal cancer patients at the same TNM stage; determining that the prognosis is poor when the level of the mRNA of the HSPD1 gene or the HSP60 protein encoded by the HSPD1 gene is lower than that of a control group of colorectal cancer patients at the same TNM stage; A method comprising:

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