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Background: Gut bacteria are related to colorectal cancer (CRC) and its clinicopathologic characteristics. Objective: To develop gut bacterial subtypes and explore potential microbial targets for CRC. Methods: Stool samples from 914 volunteers (376 CRCs, 363 advanced adenomas, and 175 normal controls) were included for 16S rRNA sequencing. Unsupervised learning was used to generate gut microbial subtypes. Gut bacterial community composition and clustering effects were plotted. Differences of gut bacterial abundance were analyzed. Then, the association of CRC‐associated bacteria with subtypes and the association of gut bacteria with clinical information were assessed. The CatBoost models based on gut differential bacteria were constructed to identify the diseases including CRC and advanced adenoma (AA). Results: Four gut microbial subtypes (A, B, C, D) were finally obtained via unsupervised learning. The characteristic bacteria of each subtype were Escherichia‐Shigella in subtype A, Streptococcus in subtype B, Blautia in subtype C, and Bacteroides in subtype D. Clinical information (e.g., free fatty acids and total cholesterol) and CRC pathological information (e.g., tumor depth) varied among gut microbial subtypes. Bacilli, Lactobacillales, etc., were positively correlated with subtype B. Positive correlation of Blautia, Lachnospiraceae, etc., with subtype C and negative correlation of Coriobacteriia, Coriobacteriales, etc., with subtype D were found. Finally, the predictive ability of CatBoost models for CRC identification was improved based on gut microbial subtypes. Conclusion: Gut microbial subtypes provide characteristic gut bacteria and are expected to contribute to the diagnosis of CRC. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

Background: Bile acids (BAs) are closely related to the occurrence and development of colorectal cancer (CRC), but the specific mechanism is still unclear. Aims: To identify potential targets related to BAs in CRC and analyze the correlation with immunity. Methods: The expression of BAs and CRC-related genes in TCGA was studied and screened using KEGG. GSE71187 was used for external validation of differentially expressed genes. Immunofluorescence, immunohistochemistry, and enzymatic cycling assays were used to detect the expression levels of the differentially expressed genes ki67 and BAs. Weighted gene coexpression network analysis (WGCNA) was used to identify genes associated with differential gene expression and immunity. The Cibersort algorithm was used to detect the infiltration of 22 kinds of immune cells in cancer tissues. The PPI network and ceRNA network were constructed to reveal the possible molecular mechanisms behind tumorigenesis. Results: The BA-related gene UGT2A3 is positively correlated with good prognoses in CRC. The expression level of UGT2A3 was negatively related to the BA level and positively related to the Ki67 proliferation index. The expression level of UGT2A3 was higher in the moderately differentiation and advanced stage (stage IV) of CRC. In addition, the expression level of UGT2A3 is correlated with CD8+ T cells. A PPI network related to UGT2A3 and T-cell immune-related genes was constructed. A ceRNA network containing 32 miRNA‒mRNA and 40 miRNA‒lncRNA regulatory pairs was constructed. Conclusion: UGT2A3 is a potential molecular target of bile acids in the regulation of CRC and is related to T-cell immunity. [ABSTRACT FROM AUTHOR]

Background: Gut microbiome is a complex community of microbes present in the human gut and plays an important role in the occurrence and progression of colorectal cancer (CRC). However, the relationship between virus and CRC has not been fully understood. Objective: To explore the hot spots and research trends in the field of CRC and virus. Methods: By using the bibliometric analysis tool CiteSpace and based on the articles of the Web of Science Core Collection (WoSCC) database, the country, institution, highly cited literature, keywords and so on were visually analyzed. Results: A total of 356 research articles on CRC from 2001 to 2023 were thoroughly analyzed. The USA and China have made the largest contribution in the field of virus and CRC. The Helmholtz Association published the most papers. There were relatively few cooperations among institutions from different countries. The results of keyword cluster analysis proved that the literature on the relationship between human cytomegalovirus (CMV) and CRC was the most widely studied aspect in this field. "Gut microbiota," "inflammatory bowel disease," "hepatitis b virus," and "human papillomavirus infection" are the current research hotspots; "oncolytic virus," "apoptosis," and "gut microbiome" are the recent research frontiers and should be paid closer attention. Conclusion: By using CiteSpace bibliometric software, the visual analysis reflected the research trends and hot topics of virus and CRC. In addition, the prevalence and mechanism of specific virus on CRC were also reviewed, which provides valuable references for future CRC research. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

Objective: This study aimed to characterize the tumor-infiltrating T cells in moderately differentiated colorectal cancer. Methods: Using single-cell RNA sequencing data of isolated 1632 T cells from tumor tissue and 1252 T cells from the peripheral blood of CRC patients, unsupervised clustering analysis was performed to identify functionally distinct T cell populations, followed by correlations and ligand-receptor interactions across cell types. Finally, differential analysis of the tumor-infiltrating T cells between colon cancer and rectal cancer were carried out. Results: A total of eight distinct T cell populations were identified from tumor tissue. Tumor-Treg showed a strong correlation with Th17 cells. CD8+TRM was positively correlated with CD8+IEL. Seven distinct T cell populations were identified from peripheral blood. There was a strong correlation between CD4+TN and CD4+blood-TCM. Colon cancer and rectal cancer showed differences in the composition of tumor-infiltrating T cell populations. Tumor-infiltrating CD8+IEL cells were found in rectal cancer but not in colon cancer, while CD8+ TN cells were found in the peripheral blood of colon cancer but not in that of rectal cancer. A larger number of tumor-infiltrating CD8+ Tex (88.94%) cells were found in the colon cancer than in the rectal cancer (11.06%). The T cells of the colon and rectal cancers showed changes in gene expression pattern. Conclusions: We characterized the T cell populations in the CRC tumor tissue and peripheral blood. [ABSTRACT FROM AUTHOR]

Long non-coding RNAs (lncRNAs) are tumor-related regulators and have been found to be involved in the underlying molecular mechanisms of colorectal cancer (CRC). However, the role of lncRNA LINC00115 during CRC progression is not entirely elucidated. In this study, we discovered that LINC00115 was significantly overexpressed in CRC, and its overexpression predicted poor patient outcomes. Downregulation of LINC00115 markedly inhibited CRC cell proliferation, increased cell apoptosis, and suppressed cell migration and invasion. Moreover, downregulation of LINC00115 led to the inactivation of PI3K/AKT/mTOR signaling. Bioinformatics analysis identified miR-489-3p as a candidate target of LINC00115. Furthermore, we revealed an inverse correlation between LINC00115 and miR-489-3p in CRC tissues. Importantly, by luciferase reporter assay, we found that miR-489-3p might directly target LINC00115, and downregulation of miR-489-3p could rescue the biological effects induced by the absence of LINC0015. In conclusion, our findings demonstrated that LINC00115 serves as an oncogene in CRC metastasis. Deeper understanding of the LINC00115/miR-489-3p axis might provide potential therapeutic targets against CRC metastasis. [ABSTRACT FROM AUTHOR]

Intestinal flora is an important component in the human body, which have been reported to be involved in the occurrence and development of colorectal cancer (CRC). Indeed, changes in the intestinal flora in CRC patients compared to those in control subjects have been reported. Several bacterial species have been shown to exhibit the pro-inflammatory and pro-carcinogenic properties, which could consequently have an impact on colorectal carcinogenesis. In this review, we summarize the current knowledge on the potential links between the intestinal microbiota and CRC. We illustrated the mechanisms by which intestinal flora imbalance affects CRC, mainly focusing on inflammation, microbial metabolites, and specific bacteria species. In addition, we discuss how a diet exhibits a strong impact on microbial composition and provides risks for developing CRC. Finally, we describe the potential future directions that are based on intestinal microbiota manipulation for CRC diagnosis and treatment. [ABSTRACT FROM AUTHOR]

Purpose: To analyze the lymph node metastasis status and prognosis in CRCs and to investigate the gut microorganisms and microbial metabolites at different lymph node stages. Methods: The Surveillance, Epidemiology, and End Results (SEER) database and STAT software were used to analyze the clinical features and lymph node metastasis. Bacterial 16S V3-V4 and fungal ITS V3-V4 ribosomal RNA genes were sequenced in 53 stool samples and gas chromatography/mass spectrometry (GS/MS) was performed to detect the microbial metabolites in 48 stool samples from CRC patients. Results: A higher number of lymph node metastases predicted a poor prognosis. Inadequate evaluation of lymph nodes affects the accuracy of prognostic assessments. We constructed a nomogram model for the assessment of prognostic factors. There were multiple characteristic bacteria identified, including Akkermansia, Megamonas, Dialister, etc., and fungi, including Penicillium, Filobasidium, Debaryomyces, etc. A total of 27 characteristic microbial metabolites in different lymph node metastasis status were also identified. Conclusion: Gut microorganisms and microbial metabolites may provide reference and guidance for the adequate lymph node assessments (ALNA) in CRC. [ABSTRACT FROM AUTHOR]