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Background: Microsatellite instability (MSI) caused by DNA mismatch repair (MMR) deficiency is of great significance in the occurrence, diagnosis and treatment of colorectal cancer (CRC)., Aim: This study aimed to analyze the relationship between mismatch repair status and clinical characteristics of CRC., Methods: The histopathological results and clinical characteristics of 2029 patients who suffered from CRC and underwent surgery at two centers from 2018 to 2020 were determined. After screening the importance of clinical characteristics through machine learning algorithms, the patients were divided into deficient mismatch repair (dMMR) and proficient mismatch repair (pMMR) groups based on the immunohistochemistry results and the clinical feature data between the two groups were observed by statistical methods., Results: The dMMR and pMMR groups had significant differences in histologic type, TNM stage, maximum tumor diameter, lymph node metastasis, differentiation grade, gross appearance, and vascular invasion. There were significant differences between the MLH1 groups in age, histologic type, TNM stage, lymph node metastasis, tumor location, and depth of invasion. The MSH2 groups were significantly different in age. The MSH6 groups had significant differences in age, histologic type, and TNM stage. There were significant differences between the PMS2 groups in lymph node metastasis and tumor location. CRC was dominated by MLH1 and PMS2 combined expression loss (41.77%). There was a positive correlation between MLH1 and MSH2 and between MSH6 and PMS2 as well., Conclusions: The proportion of mucinous adenocarcinoma, protruding type, and poor differentiation is relatively high in dMMR CRCs, but lymph node metastasis is rare. It is worth noting that the expression of MMR protein has different prognostic significance in different stages of CRC disease., (© 2024. The Author(s).)

Background: Gut bacteria have an important influence on colorectal cancer (CRC). The differences of gut bacteria between genders have been the hot spots., Objective: To analyze the relationship between gut bacteria and gender differences in patients with CRC., Methods: A total of 212 patients with CRC and 212 healthy volunteers were recruited. The subjects' fecal samples were obtained, and the fecal microorganisms were analyzed by the third-generation sequencing PacBio. The composition of gut bacteria was analyzed. Linear discriminant analysis Effect Size (LEfSe) was used to analyze the differences in gut bacteria. Pearson coefficient was used to calculate the correlation between differential bacteria. CRC risk prediction models were used to rank the importance of effective differential bacteria., Results: Escherichia flexneri and Phocaeicola vulgatus were the most frequent bacteria in both male and female CRC patients. Bacteroides, Verrucomicrobia and Akkermansiaceae were highly enriched in male CRC group, while Bacteroidetes, Phocaeicola and Tissierellales were highly enriched in female CRC group. Peptostreptococcus anaerobius and Phocaeicola vulgatus were important CRC related bacteria in males and females, respectively. Peptostreptococcus anaerobius was the most important characteristic bacterium of males (AUC = 0.951), and the sensitivity and specificity of the discovery set were 78.74 % and 93.98 %, respectively. Blautia stercoris was the most important characteristic bacterium of females (AUC = 0.966), and the sensitivity and specificity of the discovery set were 90.63 % and 90.63 %, respectively., Conclusion: Gut bacteria varied in different genders. Therefore, gender should be considered when gut bacteria are applied in the diagnose and prevention of CRC., Competing Interests: Declaration of competing interest The authors declared that no potential conflicts of interest exist., (Copyright © 2024. Published by Elsevier Ltd.)

Background: Emergence of novel immuno-therapeutics has shown promising improvement in the clinical outcome of colorectal cancer (CRC)., Objective: To identify robust immune checkpoints based on expression and immune infiltration profiles of clinical CRC samples., Methods: One dataset from The Cancer Genome Atlas database and two from Gene Expression Omnibus were independently employed for the analysis. Genes associated with overall survival were identified, and distribution of each immune checkpoint with respect to different clinical features was determined to explore key immune checkpoints. Multiple staining methods were used to verify the correlation between key immune checkpoint ICOS and clinical pathological features. Differentially expressed mRNA and long non-coding RNA (lncRNA) were then detected for gene set enrichment analysis and gene set variation analysis to investigate the differentially enriched biological processes between low- and high-expression groups. Significant immune-related mRNAs and lncRNA were subjected to competing endogenous RNA (ceRNA) network analysis. Correlation of inducible T-cell costimulator (ICOS) and top 10 genes in ceRNA network were further considered for validation., Results: ICOS was identified from 14 immune checkpoints as the most highly correlated gene with survival and clinical features in CRC. The expression of ICOS protein in the poorly differentiated group was lower than that in the moderately differentiated group, and the expression in different pathological stages was significant. In addition, the expressions of ICOS were negatively correlated with Ki67. A conspicuous number of immune-related pathways were enriched in differentially expressed genes in the ICOS high- and low-expression groups. Integration with immune infiltration data revealed a multitude of differentially expressed immune-related genes enriched for ceRNA network. Furthermore, expression of top 10 genes investigated from ceRNA network showed high correlation with ICOS., Conclusion: ICOS might serve as a robust immune checkpoint for prognosis with several genes being potential targets of ICOS-directed immunotherapy in CRC., (© 2024 The Authors. Cancer Medicine published by John Wiley & Sons Ltd.)

Introduction: Endoplasmic reticulum stress (ERS) is associated with the occurrence and development of colorectal cancer (CRC)., Methods: One thousand nine CRC samples and 3 ERS gene sets from GEO database were used to screen and validate genes related to stage and prognosis of CRC. Twenty thousand five hundred thirty samples from the TCGA database validated the ERS genes related to prognosis. PPI network construction and coexpression analysis were used to investigate the correlation of genes. ConsensusClusterPlus analysis was used to classify CRC subtypes. Cox regression and the LASSO algorithm were used to screen ERS genes related to prognosis. HE staining, immunohistochemical staining, and RT-qPCR of 50 owner-central samples were used to verify the genes. The ERscore model was constructed based on the ERS genes related to prognosis. The nomogram model was used to verify that different subtypes of CRC patients have different prognosis., Results: Fifty ERS differentially expressed genes related to CRC stage and 8 ERS model genes related to prognosis were screened. Three subtypes of CRC were classified based on the former 50 genes. The clinical characteristics were significantly different among the subtypes. The ERscore model was constructed based on the latter 8 genes, and its accuracy was verified by clinical samples. Finally, the nomogram was constructed based on ERscore, age, and CRC stage, and the accuracy of the nomogram prediction was verified., Conclusion: ERS-related genes can be used as classification criteria for CRC, and the related clinical characteristics of different CRC subtypes are different., (© 2023 S. Karger AG, Basel.)

Immunotherapy has transformed treatment for various types of malignancy. However, the benefit of immunotherapy is limited to a minority of patients with mismatch-repair-deficient (dMMR) and microsatellite instability-high (MSI-H) (dMMR-MSI-H) colorectal cancer (CRC). Understanding the complexity and heterogeneity of the tumor immune microenvironment (TIME) and identifying immune-related CRC subtypes will improve antitumor immunotherapy. Here, we review the current status of immunotherapy and typing schemes for CRC. Immune subtypes have been identified based on TIME and prognostic gene signatures that can both partially explain clinical responses to immune checkpoint inhibitors and the prognosis of patients with CRC. Identifying immune subtypes will improve understanding of complex CRC tumor heterogeneity and refine current immunotherapeutic strategies., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2023 Wu, Zhuang, Qu, Yang and Han.)

Background: Aging is one of the factors leading to cancer. Gut microbiota is related to aging and colorectal cancer (CRC)., Methods: A total of 11 metagenomic data sets related to CRC were collected from the R package curated Metagenomic Data. After batch effect correction, healthy individuals and CRC samples were divided into three age groups. Ggplot2 and Microbiota Process packages were used for visual description of species composition and PCA in healthy individuals and CRC samples. LEfSe analysis was performed for species relative abundance data in healthy/CRC groups according to age. Spearman correlation coefficient of age-differentiated bacteria in healthy individuals and CRC samples was calculated separately. Finally, the age prediction model and CRC risk prediction model were constructed based on the age-differentiated bacteria., Results: The structure and composition of the gut microbiota were significantly different among the three groups. For example, the abundance of Bacteroides vulgatus in the old group was lower than that in the other two groups, the abundance of Bacteroides fragilis increased with aging. In addition, seven species of bacteria whose abundance increases with aging were screened out. Furthermore, the abundance of pathogenic bacteria (Escherichia_coli, Butyricimonas_virosa, Ruminococcus_bicirculans, Bacteroides_fragilis and Streptococcus_vestibularis) increased with aging in CRCs. The abundance of probiotics (Eubacterium_eligens) decreased with aging in CRCs. The age prediction model for healthy individuals based on the 80 age-related differential bacteria and model of CRC patients based on the 58 age-related differential bacteria performed well, with AUC of 0.79 and 0.71, respectively. The AUC of CRC risk prediction model based on 45 disease differential bacteria was 0.83. After removing the intersection between the disease-differentiated bacteria and the age-differentiated bacteria from the healthy samples, the AUC of CRC risk prediction model based on remaining 31 bacteria was 0.8. CRC risk prediction models for each of the three age groups showed no significant difference in accuracy (young: AUC=0.82, middle: AUC=0.83, old: AUC=0.85)., Conclusion: Age as a factor affecting microbial composition should be considered in the application of gut microbiota to predict the risk of CRC., (© 2023 The Authors. Cancer Medicine published by John Wiley & Sons Ltd.)

The occurrence and development of colorectal cancer (CRC) and advanced adenoma (AA) are closely related to the gut microbiome, and AA has a high cancerization progression rate to CRC. Current studies have revealed that bacteriological analysis cannot identify CRC from AA. The objective was to explore microbial targets that could identify CRC and AA from a microecological perspective and to figure out the best way to identify CRC based on fecal microbes. The metagenomic sequencing data were used to describe the gut microbiome profile and analyze the differences between microbial abundance and microbial single nucleotide polymorphism (SNP) characteristics in AA and CRC patients. It was found that there were no significant differences in the diversity between the two groups. The abundance of bacteria (e.g., Firmicutes , Clostridia , and Blautia ), fungi ( Hypocreales ), archaea ( Methanosarcina , Methanoculleus , and Methanolacinia ), and viruses ( Alphacoronavirus , Sinsheimervirus , and Gammaretrovirus ) differed between AA and CRC patients. Multiple machine-learning algorithms were used to establish prediction models, aiming to identify CRC and AA. The accuracy of the random forest (RF) model based on the gut microbiome was 86.54%. Nevertheless, the accuracy of SNP was 92.31% in identifying CRC from AA. In conclusion, using microbial SNP was the best method to identify CRC, it was superior to using the gut microbiome, and it could provide new targets for CRC screening. IMPORTANCE There are differences in characteristic microorganisms between AA and CRC. However, current studies have indicated that bacteriological analysis cannot identify CC from AA, and thus, we wondered if there were some other targets that could be used to identify CRC from AA in the gut microbiome. The differences of SNPs in the gut microbiota of intraindividuals were significantly smaller than those of interindividuals. In addition, compared with intestinal microbes, SNP was less affected by time with certain stability. It was discovered that microbial SNP was better than the gut microbiome for identifying CRC from AA. Therefore, screening characteristic microbial SNP could provide a new research direction for identifying CRC from AA.

Colorectal cancer (CRC) is one of the common human malignancies. Discovery and identification of novel therapeutic target is imperative to improve the prognosis of CRC patients. As a member of the PIM family, PIM3 has been found to be overexpressed in a variety of cancerous tumors. In this study, we evaluated the expression of PIM3 in CRC tissues and analyzed the role of PIM3 in CRC. Our results showed that PIM3 expression was significantly higher in CRC tissues compared with adjacent noncancerous tissues. The PIM3 expression level was found to be correlated with advanced disease stage and lymph node metastasis. Moreover, PIM3 was found to be able to predict poor prognosis in CRC patients as an independent factor. In vitro studies also showed that knockdown of PIM3 exhibited inhibitory effect on cell growth, promoted cell apoptosis and dampened invasive capability of HCT116 and SW620 cells. Moreover, PIM3 knockdown was able to delay tumor growth and suppress lung metastasis in xenograft model. Our results indicated that PIM3 is a potential therapeutic target for CRC. Anat Rec, 302:1552-1560, 2019. © 2018 American Association for Anatomy., (© 2018 American Association for Anatomy.)

Background: Abnormal lipid metabolism is considered to be one of main promoters of colorectal cancer (CRC), and intestinal microorganisms may be involved in CRC in patients with abnormal lipid metabolism., Objective: To investigate lipid metabolism in CRC patients and explore the role of intestinal microorganisms in CRC complicated with abnormal lipid metabolism., Methods: Overall, 150 CRC patients in Huzhou Central Hospital from January 2016 to September 2017 were recruited in the present study. Basic patient information and clinical serological indicators were investigated and analyzed. Twenty-one stool samples were collected from patients after receiving informed consent. Next-generation sequencing technology was used to sequence bacterial 16S ribosomal RNA. Bioinformatics analysis was used to profile the microbial composition and screen distinctive bacteria in patients with CRC complicated with abnormal lipid metabolism., Results: Apo B and FFA levels were higher in patients with stage I disease than in patients with other stages. HDL, LDL, Apo B and FFA levels were higher in female patients than in male patients. FFA level was higher in rectal cancer patients than in colon cancer patients. These differences were statistically significant (p < 0.05). The proportion of Escherichia/Shigella was increased in CRC patients with hyperlipoidaemia and hypercholesteremia; the abundance of Streptococcus was increased in CRC patients with hyperlipoidaemia; the abundance of Clostridium XIVa was reduced in CRC patients with hyperlipoidaemia and hypercholesteremia; and the abundance of Ruminococcaceae was reduced in CRC patients with hypercholesteremia. Bilophila and Butyricicoccus were closely related to CRC patients without hyperlipoidaemia or hypercholesteremia, and Selenomonas, Clostridium, Bacteroidetes Slackia, Burkholderiales and Veillonellaceae were closely related to CRC patients with hyperlipoidaemia. Some pathways, including secretion system, chaperones and folding catalysts, amino sugar and nucleotide sugar metabolism, arginine and proline metabolism, glycine, serine and threonine metabolism, histidine metabolism, pores and ion channels, nitrogen metabolism and sporulation, may be involved in lipid metabolism abnormality in CRC patients., Conclusions: Many CRC patients have abnormal lipid metabolism, and the intestinal microbiota is altered in these CRC patients.

Background: Tongue diagnosis, as a unique method of traditional Chinese medicine (TCM), discriminates physiological functions and pathological conditions by observing the changes of the tongue coating., Aims: To evaluate the differences of tongue images and tongue coating microbiome between patients with colorectal cancer and healthy people., Methods: The tongue diagnostic information acquisition system was used to photograph the tongue images and analyze the thickness of the tongue coatings in patients with colorectal cancer and healthy people. The next-generation sequencing technology was used to determine the V2-V4 hypervariable region of 16S rDNA to investigate the microbial community structure and diversity on the tongue coating., Results: The tongue coatings in patients with colorectal cancer were obvious thickening compared with tongue images in healthy people. The microbial community structure on the tongue coating was different between patients with colorectal cancer and healthy people., Conclusion: Tongue diagnosis may provide important leads towards novel microbiome-related diagnostic tools and tongue coating microbiome may be a novel biomarker for characterizing patient with colorectal cancer., (Copyright © 2014 Elsevier Ltd. All rights reserved.)