Method for determining prognosis of colorectal cancer patient using colorectal cancer microbial marker

Abstract

According to the present invention, intestinal microbiota of patients diagnosed with colorectal cancer were analyzed, and intestinal microbiota following surgery and chemotherapy were compared and analyzed for the same patient. Through this, microorganisms that exhibited changes in enrichment before and after colorectal cancer treatment were selected, and intestinal microbial markers were selected by determining whether the selected microorganisms could be used to distinguish between a state in which colorectal cancer is present and a state in which colorectal cancer is absent. Therefore, the intestinal microbial marker according to the present invention can be used to determine the prognosis state of a colorectal cancer patient following surgery and chemotherapy.

Description

A method for assessing the prognosis of colorectal cancer patients using colorectal cancer microbial markers

[0001] The present invention relates to a method for determining the prognosis of a colon cancer patient using a colon cancer microbial marker.

[0002]

[0003] Colorectal cancer is the third most common cancer worldwide, with 1.9 million new cases and approximately 935,000 deaths annually. In Korea, it is the fourth most commonly diagnosed cancer and has the third highest mortality rate. Notably, 60-65% of colorectal cancer cases occur in individuals without a clear genetic predisposition or family history, suggesting that the onset of colorectal cancer is driven by extrinsic factors such as lifestyle and dietary intake. Recent studies have revealed that an imbalance in the gut microbiome plays a crucial role in the development of colorectal cancer. Interest in the microbiome, which studies this phenomenon, is gaining traction as a new paradigm for regulating the pathogenesis and outcomes of diseases such as colorectal cancer. For example, Fusobacterium nucleatum is known to promote cancer cell growth through the Wnt / β-catenin pathway and Annexin A1, inhibit T-cell and NK-cell activity to interfere with antitumor immunity, and increase chemotherapy resistance through the TLR4 / NF-κB pathway. In addition, the microome is known to be involved in the induction of inflammation, mutation generation, production of reactive oxygen species, and production of carcinogenic metabolites.

[0004] Despite the clear link between the gut microbiome and colorectal cancer, as described above, research on the gut microbiome of colorectal cancer patients is lacking. Microbiomes have been shown to vary based on geography, ethnicity, and dietary patterns. For example, the microbiome compositions of Westerners and Asians differ, and even within the same region but with different dietary habits, these differences can be significant. These results highlight the need for individualized gut microbiome studies in Asians.

[0005] The patent documents and references mentioned in this specification are incorporated herein by reference to the same extent as if each document were individually and specifically identified by reference.

[0006]

[0007] The present invention monitors and compares the composition of intestinal microorganisms in a large number of identical colon cancer patients from diagnosis to post-operative and chemotherapy treatment, thereby selecting colon cancer microbial markers capable of determining the prevalence and disease-free state of colon cancer. Furthermore, it experimentally demonstrates that colon cancer treatment outcomes can be monitored based on changes in their abundance. Therefore, the purpose of the present invention is to provide colon cancer microbial markers capable of determining the prevalence and disease-free state of colon cancer, and to provide a method for determining the prognosis of colon cancer patients using these markers.

[0008] Other objects and technical features of the present invention are presented more specifically in the detailed description of the invention, the claims and the drawings below.

[0009]

[0010] The present invention provides a colon cancer microbial marker capable of determining the colon cancer prevalence and disease-free state, and to provide a method for determining the prognosis of a colon cancer patient, the first abundance (%) of one or more microorganisms selected from the microbial group of Fusobacterium, Parvimonas, Prevotella 9, and Holdemanella is analyzed from a fecal sample of a colon cancer patient before colon cancer treatment, and the second abundance (%) of one or more microorganisms selected from the microbial group of Fusobacterium, Parvimonas, Prevotella 9, and Holdemanella is analyzed from a fecal sample of the colon cancer patient after colon cancer treatment, and then the Fusobacterium, Parvimonas, Prevotella 9, and If the second abundance of one or more microorganisms selected from the Holdemanella microbial group is reduced by 3 to 120 times compared to the first abundance, it is determined to be a disease-free state.

[0011]

[0012] The present invention analyzed the intestinal microbiota of patients diagnosed with colorectal cancer and compared the intestinal microbiota of the same patients after surgery and chemotherapy. Through this analysis, microorganisms whose abundance changed before and after colorectal cancer treatment were identified, and whether these microorganisms could distinguish between colorectal cancer-prevalent and colorectal cancer-free states was determined, thereby selecting intestinal microbial markers. Therefore, the intestinal microbial markers of the present invention have the advantage of being able to determine the prognosis of colorectal cancer patients after surgery and chemotherapy.

[0013]

[0014] Figure 1 shows the results of a comparative analysis of microbial diversity and microbiota of colon cancer patient samples analyzed according to the present invention.

[0015] Figure 2 shows the results of linear discriminant analysis effect size analysis for a sample before colon cancer surgery (S1 sample) and a sample after surgery and chemotherapy (S2 sample) of the present invention.

[0016] Figure 3 shows the results of a Wilcoxon rank sum test for changes in the abundance of specific microbial taxa between a stool sample before colorectal cancer surgery (S1 sample) and a stool sample after colorectal cancer surgery and chemotherapy (S2 sample) of a colorectal cancer patient being analyzed according to the present invention.

[0017] Figure 4 shows the results of receiver operating characteristic analysis for a stool sample (S1 sample) before colon cancer surgery and a stool sample (S2 sample) after colon cancer surgery and chemotherapy of a colon cancer patient subject to analysis of the present invention.

[0018]

[0019] The present invention comprises a first step of analyzing a first abundance (%) of one or more microorganisms selected from a microbial group of Fusobacterium, Parvimonas, Prevotella 9, and Holdemanella from a stool sample of a colon cancer patient before colon cancer treatment; a second step of analyzing a second abundance (%) of one or more microorganisms selected from a microbial group of Fusobacterium, Parvimonas, Prevotella 9, and Holdemanella from a stool sample of the colon cancer patient after colon cancer treatment; And a third step of determining that the patient is in a disease-free state when the second abundance of one or more microorganisms selected from the microbial group of Fusobacterium, Parvimonas, Prevotella 9, and Holdemanella decreases by 3 to 120 times compared to the first abundance; a method for determining the prognosis of a colon cancer patient using a colon cancer microbial marker is provided.

[0020] The above colon cancer treatment is characterized by colon cancer surgery or chemotherapy, and the chemotherapy is characterized by being performed for 6 to 12 months after colon cancer surgery.

[0021] The above colon cancer patients are characterized by TNM stage I to IV.

[0022] The above abundance (%) is characterized by performing sequence analysis on genomic DNA obtained from the above fecal sample, comparing it with a microbial genome database to identify microbial species, and calculating it using the Chao 1 index.

[0023] The present invention is characterized in that, when one or more microorganisms selected from the group of microorganisms Fusobacterium, Parvimonas, Prevotella 9, and Holdemanella are used as colon cancer microorganism markers, a disease-free state is determined when the second abundance of the microorganisms is reduced by 3 to 120 times compared to the first abundance.

[0024] When Fusobacterium is used as a colon cancer microbial marker, it is characterized in that a disease-free state can be determined when the second abundance of Fusobacterium decreases by 3 to 120 times compared to the first abundance of Fusobacterium; preferably, a disease-free state can be determined when the second abundance decreases by 15 to 60 times; and preferably, a disease-free state can be determined when the second abundance decreases by 19.7 times.

[0025] When Parvimonas is used as a colon cancer microbial marker, it is characterized in that a disease-free state can be determined when the second abundance of Parvimonas is reduced by 3 to 120 times compared to the first abundance of Parvimonas; preferably, a disease-free state can be determined when the second abundance of Parvimonas is reduced by 80 to 110 times; and preferably, a disease-free state can be determined when the second abundance of Parvimonas is reduced by 103 times.

[0026] When Prevotella 9 is used as a colon cancer microbial marker, if the second abundance of Prevotella 9 decreases by 3 to 120 times compared to the first abundance of Prevotella 9, it can be determined as a disease-free state; preferably, if it decreases by 5 to 40 times, it can be determined as a disease-free state; and preferably, if it decreases by 7.8 times, it can be determined as a disease-free state.

[0027] When the Holdemanella is used as a colon cancer microbial marker, it is characterized in that a disease-free state can be determined when the second abundance of the Holdemanella is reduced by 3 to 120 times compared to the first abundance of the Holdemanella; preferably, a disease-free state can be determined when the second abundance is reduced by 3 to 20 times; and preferably, a disease-free state can be determined when the second abundance is reduced by 3.6 times.

[0028] When the microbial group including Fusobacterium, Parvimonas, Prevotella 9, and Holdemanella is used as a colon cancer microbial marker, it is characterized in that when the second abundance of the microbial group decreases by 3 to 120 times compared to the first abundance of the microbial group, it can be determined as a disease-free state; preferably, when it decreases by 4 to 20 times, it can be determined as a disease-free state; and preferably, when it decreases by 6.6 times, it can be determined as a disease-free state.

[0029]

[0030] The present invention is described in detail through examples.

[0031]

[0032] Example

[0033]

[0034] 1. Experimental method

[0035] 1) Selection of colorectal cancer patients for analysis

[0036] In the present invention, samples were obtained and analyzed from patients diagnosed with primary colorectal cancer between July 1, 2021, and March 2, 2023. The colorectal cancer patients analyzed were selected according to the following criteria to ensure homogeneity and relevance of the analysis group.

[0037] The patients with colorectal cancer analyzed above were 60 to 80 years of age and visited the hospital for treatment of primary colorectal cancer; patients with primary colorectal cancer who had been prescribed steroids or immunosuppressants within 6 months before colorectal cancer surgery; patients with primary colorectal cancer without severe communication disorders such as dementia or intellectual disability; patients with primary colorectal cancer with an American Society of Anesthesiologists (ASA) score of III or higher; patients with primary colorectal cancer with an Eastern Cooperative Oncology Group (ECOG) performance status >3; patients with primary colorectal cancer who were not pregnant; and patients with primary colorectal cancer without underlying diseases that may affect the immune status, such as rheumatoid arthritis, Behcet's disease, or inflammatory bowel disease.

[0038] In this invention, variability was minimized and the reliability of the study results increased through a rigorous screening process for colorectal cancer patients. This study was conducted with ethics approval from the Myongji Hospital Institutional Review Board (IRB 2021-05-005 and 2020-01-016).

[0039]

[0040] 2) Preparation and analysis of samples to be analyzed

[0041] (1) Sample to be analyzed

[0042] In the present invention, the stool (feces) of the colorectal cancer patients and the mucosal tissue around the site of colorectal cancer were used as the analysis target samples. The stool samples of the colorectal cancer patients were collected 30 times each before colorectal cancer surgery or after 6 to 12 months of chemotherapy after surgery. They were obtained before PEG intestinal treatment, treated with a DNA / RNA protection reagent (New England Biolabs), and then stored at -80℃. The stool sample collected before colorectal cancer surgery of the colorectal cancer patients was designated as S1 sample; and the stool sample collected after 6 to 12 months of chemotherapy after colorectal cancer surgery of the colorectal cancer patients was designated as S2 sample. The colorectal cancer patients analyzed who underwent chemotherapy for 6 to 12 months after the above colorectal cancer surgery performed blood tests and the average Carcino-Embryonic Antigen (CEA) level was 3.6 ng / ㎖ (±72.2), which was confirmed to be in a disease-free state or normal healthy state. Thirty mucosal tissue samples around the site of colorectal cancer in the colorectal cancer patients analyzed were collected during the colorectal cancer surgery, stored at -80℃, and designated as T1 samples.

[0043]

[0044] (2) Extraction of genomic DNA

[0045] Genomic DNA was extracted from the S1, S2, and T1 samples of the present invention. Genomic DNA was extracted from the S1 and S2 samples using the QIAamp Power Fecal Pro DNA Kit (Qiagen); genomic DNA was extracted from the T1 sample using the QIAamp Fast DNA Tissue Kit (Qiagen). The purity of the extracted genomic DNA was assessed using a NanoDrop 2000 spectrophotometer (Thermo Fisher Scientific), and the integrity was confirmed using a 2% (w / v) agarose gel.

[0046]

[0047] (3) Analysis of genomic DNA

[0048] The genomic DNA of the extracted samples was sequenced and subjected to bioinformatics and statistical analysis. The genomic DNA sequence was analyzed by paired-end sequencing on the Illumina MiSeq platform. The sequencing data obtained through the analysis were processed with QIIME2 and DADA2, and then taxonomic groups were determined using the Silva 138.1 database. Microbiome profiling of the microorganisms contained in the samples was performed using the taxonomic groups.

[0049] Statistical analysis was performed using Qiime2, R (version 4.0.2), and Python (version 3.8). Non-parametric tests were used to compare the microbial diversity and composition across the analysis subjects. Alpha diversity was assessed using non-parametric tests; beta diversity was assessed using unweighted UniFrac; and visualization was performed using PERMANOVA and PCoA. Microbial markers were identified using LEfSe analysis (LDA score ≥ 3.0 and p ≤ 0.05 threshold).

[0050] The diagnostic potential of colorectal cancer using microbial markers was analyzed using the ROC curve and the Random Forest algorithm; pairwise comparisons of the Kruskal-Wallis test and the Wilcoxon rank-sum test were used to analyze differences between groups.

[0051] The associations between microbial taxa and clinical parameters, adjusted for multiple comparisons, were analyzed using stepwise regression analysis, fine-tuned by AIC and adjusted for multiple comparisons using the FDR method. The significance level was set at p<0.05.

[0052]

[0053] 2. Experimental results

[0054] 1) Characteristics of the colorectal cancer patient population analyzed

[0055] The target population of colorectal cancer patients for analysis in the present invention consisted of 30 Koreans diagnosed with colorectal cancer, with an average age of 68.8 years (±8.7) and an average body mass index of 24.0 (±3.0). The target population of colorectal cancer patients for analysis in the present invention included 36.7% of women who had comorbidities including diabetes (46.7%), hypertension (56.7%), and hyperlipidemia (43.3%). The cancer stage of the target population of colorectal cancer patients for analysis in the present invention was mainly stage 2 (36.7%) or stage 3 (46.7%), and the carcinoembryonic antigen (CEA) level significantly decreased from an average of 22.8 ng / ㎖ (±72.2) before surgery to an average of 3.6 ng / ㎖ (±2.7) after surgery.

[0056] Clinical variables: Colorectal cancer, Age (mean ± standard deviation), Body mass index (mean ± standard deviation), 24.0 ± 3.0, Sex (persons, (%)), Female, 11 (36.7), Comorbidities: Diabetes (persons, (%)), 14 (46.7), Hypertension (persons, (%)), 17 (56.7), Hyperlipidemia (persons, (%)), 13 (43.3), Smoking (persons, (%)), 13 (43.3), Drinking (persons, (%)), 10 (33.3), Tumor location (persons, (%)), Right side, 15 (50.0), Left side, 15 (50.0), TNM stage (persons, (%)), I4 (13.3), II, 11 (36.7), III, 14 (46.7), IV, 1 (3.3), Metastatic lymph nodes (persons, (%)), 0.14 (46.7), 1 ≥ 0.16 (53.3) Perineural invasion (persons, (%))9 (30.0) K-RAS (persons, (%))12 (40.0) CEA (mean ± standard deviation)22.8±72.2 Adjuvant chemotherapy (persons, (%))16 (53.3)

[0057] In the present invention, for the intestinal microome analysis of a group of colorectal cancer patients, a mucosal tissue sample (T1) was obtained from an area adjacent to a tumor during colorectal cancer surgery; a stool sample (S1 sample) was obtained before surgery; and a stool sample (S2 sample) was obtained after chemotherapy for 6 to 12 months after surgery.

[0058]

[0059] 2) Analysis of microbial abundance and diversity

[0060] In the present invention, the microbial richness and diversity were analyzed through alpha diversity indices (Shannon index, Chao1 index, and Simpson index) analysis for the colon cancer patient samples to be analyzed, and the differences between them at the phylum level or genus level were analyzed through beta diversity analysis using NMDS (Non-metric MultiDimensional Scaling) and the unweighted UniFrac method.

[0061] Figure 1 shows the results of comparative analysis of microbial diversity and microbiota of colorectal cancer patient samples analyzed according to the present invention. Panel a shows the results of alpha diversity evaluation using the Shannon index for the colorectal cancer patient samples analyzed according to the present invention; Panel b shows the results of microbial species-specific abundance evaluation using the Chao1 index for the colorectal cancer patient samples analyzed according to the present invention; Panel c shows the results of evaluating the probability of the presence of identical microorganisms using the Simpson index for the colorectal cancer patient samples analyzed according to the present invention; Panel d shows the results of confirming a significant difference in the composition of microbial species between fecal samples and mucosal tissue samples (p=0.001) through beta diversity analysis using NMDS (Non-metric MultiDimensional Scaling) and the unweighted UniFrac method for the colorectal cancer patient samples analyzed according to the present invention; Panel d shows the results of comparative analysis of the significant relative abundance differences in the composition of microbial communities between the fecal samples and mucosal tissue samples at the phylum level; Panel e shows the results of a comparative analysis of the significant differences in relative abundance in the microbial community composition between the fecal samples and mucosal tissue samples at the genus level.

[0062] Analysis of the alpha diversity index showed that the Shannon index was p=0.152; the Chao1 index was p=0.333; and the Simpson index was p=0.073. This indicates that the microbial diversity between the fecal samples and the mucosal tissue samples was statistically different (see panels a, b, and c in Figure 1). In addition, significant differences were found when the beta diversity index was used to evaluate the changes in the microbial community composition between the samples. Analysis of the beta diversity index using Non-metric MultiDimensional Scaling (NMDS) with the unweighted UniFrac method confirmed that there was a significant difference (p=0.001) in the microbial composition between the fecal samples and the mucosal tissue samples. This indicates that the fecal samples and the mucosal tissue samples each have unique microbial profiles (see panels d and e in Figure 1).

[0063]

[0064] 3) Results of comparative microbiota analysis of colon cancer samples

[0065] As a result of comparative analysis of colon cancer patient samples analyzed by the present invention, it was confirmed that the composition of microorganisms differed depending on the type of sample.

[0066] As a result of analyzing the microorganisms at the phylum level, the microorganisms present in the S1 sample were confirmed to be composed of 73.3% Firmicutes; 13.4% Bacteroidota; and 3.95% Proteobacteria, in that order. The microorganisms present in the S2 sample were confirmed to be composed of 65.9% Firmicutes; 8.3% Bacteroidota; and 5.91% Proteobacteria, in that order. In addition, the microorganisms present in the T1 sample were confirmed to be Bacteroidota 24.5%; Proteobacteria 26.7%; and Fusobacteriota 6.13%.

[0067] Comparative analysis of microorganisms at the genus level revealed that, similar to the phylum level analysis, the composition of microorganisms varied depending on the type of sample. As a result of the analysis, Fusobacterium was found to be present at 14.75% in the T1 sample, which was higher than that of the S1 sample (0.79%) and the S2 sample (0.04%); Prevotella 9 was found to be present at 9.05% in the T1 sample, while it was present at 6.13% in the S1 sample and 0.78% in the S2 sample. In contrast, Blautia was found to be present at relatively high levels, at 6.3% in the T1 sample, 23.9% in the S1 sample, and 22.3% in the S2 sample.

[0068]

[0069] 4) Screening of colon cancer microbial markers

[0070] In order to select the colon cancer microbial marker of the present invention, linear discriminant analysis effect size (LEfSe) analysis was performed on the colon cancer pre-surgery sample (S1 sample) and the post-surgery chemotherapy-administered sample (S2 sample).

[0071] Figure 2 shows the results of linear discriminant analysis effect size analysis for a pre-operative colon cancer sample (S1 sample) of the present invention; and a post-operative chemotherapy-administered sample (S2 sample). Panel a shows the results of analysis at the phylum level for the T1 sample of the present invention; panel b shows the results of analysis at the phylum level for the S1 sample of the present invention; panel c shows the results of analysis at the genus level for the T1 sample of the present invention; panel d shows the results of analysis at the genus level for the S1 sample of the present invention; panel e shows a Venn diagram analyzing colon cancer microbial markers at the phylum level between the T1 sample and the S1 sample; and panel f shows a Venn diagram analyzing colon cancer microbial markers at the genus level between the T1 sample and the S1 sample.

[0072] The analysis results showed that Proteobacteria and Fusobacteriota were enriched at the phylum level in the T1 sample; and that Escherichia-Shigella, Fusobacterium, Pseudomonas, Prevotella 9, Parvimonas, Peptostreptococcus, Sutterella, Selemonas, and Holdemanella were enriched at the genus level (see Fig. 2a). In contrast, in the case of the S1 sample, Firmicutes and Fusobacteriota were found to be particularly enriched at the Phylum level, and at the Genus level, Prevotella 9, Dorea, Peptostreptococcus, Holdemanella, Fusobacterium, and Parvimonas were found to be more enriched in the S1 sample than in the S2 sample.

[0073] Venn diagram analysis results showed that Fusobacteriota was enriched at the phylum level in both S1 and T1 samples. This suggests that Fusobacteriota plays an important role in colorectal cancer. In addition, at the genus level, Fusobacterium, Parvimonas, Prevotella 9, and Holdemanella were found to be the most enriched genera in both S1 and T1 samples (Table 2). Therefore, in the present invention, Fusobacterium, Parvimonas, Prevotella 9, and Holdemanella were selected as colorectal cancer microbial markers.

[0074] Colon cancer microbial markers Microbial abundance (%) T1 sample S1 sample S2 sample Fusobacterium 14.75% 0.79% 0.04% Prevotella 9 9.05% 6.13% 0.78% Parvimonas 1.91% 0.31% 0.003% Holdemanella 1.07% 2.09% 0.58%

[0075]

[0076] 5) Changes in the abundance of colon cancer microbial markers

[0077] In the present invention, we analyzed changes in the abundance of specific microbial taxa between stool samples taken before colorectal cancer surgery (S1 sample) and stool samples taken after colorectal cancer surgery and chemotherapy (S2 sample) of colorectal cancer patients. The analysis was performed using the Wilcoxon rank-sum test.

[0078] Figure 3 shows the results of a Wilcoxon rank sum test for changes in the abundance of specific microbial taxa between a stool sample before colorectal cancer surgery (S1 sample) and a stool sample after colorectal cancer surgery and chemotherapy (S2 sample) of a colorectal cancer patient being analyzed according to the present invention. Panel a shows the sample-dependent change in abundance of Fusobacterium; panel b shows the sample-dependent change in abundance of Parvimonas; panel c shows the sample-dependent change in abundance of Prevotella 9; panel d shows the sample-dependent change in abundance of Holdemanella; and panel e shows the sample-dependent change in abundance of the entire microbiome, including Fusobacterium, Parvimonas, Prevotella 9, and Holdemanella.

[0079] Analysis results showed that Fusobacterium (p=1.47x10 -3 ), Parvimonas (p=2.24x10 -5 ), Prevotella 9 (Prevotella 9, p=4.43x10 -3 ), and Holdemanella (p=3.45x10 -4 ) was confirmed to have a significantly reduced microbial enrichment in the S2 sample compared to the S1 sample. In particular, when the abundance changes were evaluated by combining the above Fusobacterium; Parvimonas; Prevotella 9; and Holdemanella, the abundance levels in the sample before colorectal cancer surgery (S1 sample) and the sample that underwent chemotherapy after colorectal cancer surgery (S2 sample) were significantly reduced (p=6.98x10 -6) was confirmed (see Table 3 and panels a to e of Fig. 3). The above results indicate that analyzing the four microorganisms in an integrated manner provides clearer results than analyzing each microorganism individually.

[0080] Colon cancer microbial markers Microbial abundance (%) p-value S1 S2 Fusobacterium 0.79% 0.04% 1.47 x 10 -3 Prevotella 9 6.13% 0.78% 4.43x10 -3 Parvimonas 0.31% 0.003% 2.24x10 -5 Holdemanella 2.09% 0.58% 3.45x10 -4 Fusobacterium + Prevotella 9 + Fabimonas + Holdemanella 9.32% 1.4% 6.98 x 10 -6

[0081]

[0082] 5) Use of colon cancer microbial markers

[0083] In the present invention, the diagnostic potential of Fusobacterium, Prevotella 9, Parvimonas, and Holdemanella for colorectal cancer was analyzed. The analysis was conducted using receiver operating characteristic (ROC) analysis of the microorganisms present in the stool samples of colorectal cancer patients before colorectal cancer surgery (S1 sample) and after colorectal cancer surgery and chemotherapy (S2 sample).

[0084] Figure 4 shows the results of receiver operating characteristic analysis for stool samples (S1 sample) taken before colorectal cancer surgery and stool samples taken after colorectal cancer surgery and chemotherapy (S2 sample) of a colorectal cancer patient analyzed according to the present invention. The analysis results confirmed that Fusobacterium had an AUC value of 0.599; Prevotella 9 had an AUC value of 0.688; Parvimonas had an AUC value of 0.680; and Holdemanella had an AUC value of 0.594. The above results indicate that the colon cancer microbial markers of the present invention, Fusobacterium, Prevotella 9, Parvimonas, and Holdemanella, can discriminate between a stool sample (S1 sample) taken before colon cancer surgery and a stool sample taken after colon cancer surgery and chemical therapy (S2 sample) taken by a colon cancer patient under analysis.

[0085] In particular, when the four colon cancer microbial markers (Fusobacterium, Prevotella 9, Parvimonas, and Holdemanella) were comprehensively analyzed, it was confirmed that they showed an AUC value of 0.841, which was higher than the AUC value of each marker. This means that it is more desirable to use the four colon cancer microbial markers in an integrated manner than to use them individually (see Fig. 4).

[0086]

[0087] 6) Relationship between the abundance of colon cancer microbial markers and clinical variables

[0088] The relationship between the abundance of four colon cancer microbial markers, Fusobacterium, Prevotella 9, Parvimonas, and Holdemanella, and clinical parameters was analyzed. To this end, multiple comparison analysis was performed on the abundance of the above microorganisms and clinical parameters. The multiple comparison analysis was performed using stepwise regression analysis fine-tuned with the Akaike Information Criterion (AIC) and adjusted with the False Discovery Rate (FDR) method.

[0089] The analysis results for the T1 sample of the present invention showed that the abundance of Prevotella 9 decreased with age (β=-0.653, 95% CI: -1.025 to -0.281, p=6.1x10 -3 ) was confirmed. This means that the abundance of Prevotella 9 and age have a significant inverse relationship. In addition, the abundance of Holdemanella was significantly correlated with high blood lipid levels (β=-5.747, 95% CI: -10.923 to -0.571, p=2.72x10 -2 ) was confirmed to show a marginal association with blood CEA levels (β=7.034, 95% CI: -0.736 to 14.804, p=6.39x10 -2 ) was confirmed to have.

[0090] The analysis results for the S1 sample of the present invention showed that the abundance of Fusobacterium was highly correlated with the TNM (Tumor, Node, Metastasis) stage (β=0.610, 95% CI: 0.066 to 1.154, p= 2.80x10 -2) was found to have a high correlation with CEA levels; the abundance of Holdemanella was highly correlated with CEA levels (β=-3.977, 95% CI: -8.161 to 0.207, p=5.76x10 -2 ) was found to be present. The abundance of Parvimonas was found to have no significant correlation with clinical variables.

[0091]

[0092] 3. Discussion

[0093] In this study, we analyzed the microbiota present in stool and mucosal tissue samples from Korean patients with colorectal cancer. As a result, we identified important colorectal cancer-associated microorganisms, including the phylum Fusobacteriota; the genus Fusobacterium; Prevotella 9; Parvimonas; and Holdemanella. These colorectal cancer-associated microorganisms were found in the mucosal tissue surrounding colorectal cancer lesions; in stool before colorectal cancer surgery; and in stool after colorectal cancer surgery and chemotherapy, indicating a deep association between these microorganisms and colorectal cancer.

[0094] According to the results of the present invention, it was confirmed that the abundance of Fusobacterium increased in the mucosal tissue sample (T1 sample) and the stool sample (S1 sample) before the colorectal cancer surgery of patients. This is believed to be because Fusobacterium is involved in the pathogenesis of colorectal cancer. According to known results, Fusobacterium colonies formed in cancer tissues induce DNA modification, and among them, species such as ATM and PIK3CA were confirmed to be involved in the modification of the cell cycle system. The ATM species belongs to the PI3 / PI4-kinase family and acts as a cell cycle regulatory kinase that regulates the activity of various proteins that control cell cycle regulation.

[0095] The intratumoral microbiota present in the mucosal tissue of colorectal cancer patients is known to differ significantly from the microbiota of normal mucosa. Our analysis revealed that Fusobacterium was enriched in the mucosal tissue of colorectal cancer patients (see panel f in Figure 1). Because Fusobacterium is conserved across diverse populations, it is believed to have potential as a diagnostic and prognostic indicator in colorectal cancer research.

[0096] According to known results, intratumoral tissue samples are known to provide more information than stool samples, and the Fusobacterium is known to be associated with metastatic lesions of cancer cells. The Fusobacterium is known to stimulate the growth of colon cancer cells through the FadA adhesin in carcinogenic and inflammatory responses, and a study using a colon cancer transplant mouse model has shown that Fusobacterium-targeted antibiotics alleviate cancer cell proliferation and tumor growth. In addition, it has been reported that the multivariate hazard ratio for colon cancer-specific mortality in Fusobacterium nucleatum-positive cases was 1.25 (95% CI: 0.82 to 1.92) or 1.58 (95% CI: 1.04 to 2.39) times higher than in Fusobacterium nucleatum-negative cases.

[0097] In the present invention, the correlation between microbial abundance and clinical parameters was confirmed through regression analysis.

[0098] The abundance of Fusobacterium of the present invention affects the TNM stage (β=0.610, 95% CI: 0.066 to 1.154, p=2.80x10 -2) was confirmed.

[0099] In the present invention, we confirmed that Parvimonas was significantly prevalent in subjects analyzed before colorectal cancer surgery (see panel c in Figure 2). Parvimonas, an anaerobic microorganism, is known to significantly contribute to the development of colorectal cancer, and colonies of Parvimonas micra are known to reduce the survival rate of colorectal cancer patients. Additionally, Parvimonas is known to induce tumorigenesis through epigenetic reprogramming of human intestinal cells and to increase Th17-mediated immune responses.

[0100] Prevotella, of which there are approximately 50 species, is widely distributed in the healthy gut of people who consume a high-fiber diet and has been considered a commensal bacterium. Recent studies have reported that Prevotella dominance can cause immune dysregulation, suggesting that some species of Prevotella may possess pathogenic properties. Prevotella dominance is associated with systemic inflammatory diseases, including periodontitis, bacterial vaginosis, rheumatoid arthritis, and metabolic disorders. For example, Prevotella copri has been found to be predominant in the feces of patients with autoimmune diseases such as rheumatoid arthritis. Furthermore, Prevotella copri colonies are known to exacerbate inflammation in a dextran sulfate sodium (DSS)-induced colitis model. According to the results of the present invention, the dominance of Prevotella, especially Prevotella 9, was confirmed.

[0101] A high prevalence of Holdemanella was confirmed in patients with colon cancer according to the present invention. Holdemanella is known to have anticancer effects.

[0102] According to the present invention, the colon cancer microbial marker can be used to screen colon cancer patients. The colon cancer microbial marker comprises Fusobacterium, Prevotella 9, Parvimonas, and Holdemanella, and these may be used singly or, preferably, analyzed in an integrated manner.

[0103] The colorectal cancer microbial marker of the present invention is consistently detected in feces before and after colorectal cancer treatment. Therefore, comparing and analyzing its abundance can help determine the extent of colorectal cancer treatment. Therefore, the colorectal cancer microbial marker of the present invention is expected to facilitate the development of non-invasive analytical methods, complementing traditional colorectal cancer screening methods. Furthermore, because the colorectal cancer microbial marker of the present invention reflects the microbial imbalance associated with colorectal cancer, it is expected to be utilized as a biomarker for the detection of early-stage colorectal cancer.

[0104] The specific embodiments described herein are intended to represent preferred embodiments or examples of the present invention and are not intended to limit the scope of the present invention. It will be apparent to those skilled in the art that variations and other uses of the present invention do not depart from the scope of the invention described in the claims of this specification.

[0105]

[0106] The intestinal microbial marker of the present invention can be used as data for determining the prognosis status of colon cancer patients after surgery and chemotherapy.

Claims

1. A first step of analyzing the first abundance (%) of one or more microorganisms selected from the microbial groups of Fusobacterium, Parvimonas, Prevotella 9, and Holdemanella from a stool sample of a colon cancer patient prior to colon cancer treatment; A second step of analyzing the second abundance (%) of one or more microorganisms selected from the microbial groups Fusobacterium, Parvimonas, Prevotella 9, and Holdemanella from a stool sample of a colon cancer patient after colon cancer treatment; and A third step of determining a disease-free state when the second abundance of one or more microorganisms selected from the microbial group of Fusobacterium, Parvimonas, Prevotella 9, and Holdemanella decreases by 3 to 120 times compared to the first abundance; A method for determining the prognosis of a colon cancer patient using a colon cancer microbial marker including .

2. A method for determining the prognosis of a colon cancer patient using a colon cancer microbial marker, characterized in that the colon cancer treatment in paragraph 1 is colon cancer surgery or chemotherapy.

3. A method for determining the prognosis of a colon cancer patient using a colon cancer microbial marker, characterized in that, in the second paragraph, the chemotherapy is performed for 6 to 12 months after colon cancer surgery.

4. A method for determining the prognosis of a colon cancer patient using a colon cancer microbial marker, characterized in that the colon cancer patient in paragraph 1 is in TNM stage I to IV.

5. A method for determining the prognosis of a colon cancer patient using a colon cancer microbial marker, characterized in that in paragraph 1, the abundance (%) is calculated by performing sequence analysis on genomic DNA obtained from the fecal sample, comparing the microbial species with a microbial genome database, and using the Chao 1 index.

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