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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.
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Neoplasias Colorretais , Microbioma Gastrointestinal , RNA Ribossômico 16S , Humanos , Neoplasias Colorretais/microbiologia , Neoplasias Colorretais/patologia , Masculino , Feminino , RNA Ribossômico 16S/genética , Pessoa de Meia-Idade , Fezes/microbiologia , Adenoma/microbiologia , Adenoma/patologia , Idoso , Bactérias/classificação , Bactérias/isolamento & purificação , Bactérias/genética , Estudos de Casos e ControlesRESUMO
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.
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Bactérias , Neoplasias Colorretais , Fezes , Microbioma Gastrointestinal , Humanos , Neoplasias Colorretais/microbiologia , Masculino , Feminino , Microbioma Gastrointestinal/genética , Bactérias/classificação , Bactérias/genética , Bactérias/isolamento & purificação , Fezes/microbiologia , Pessoa de Meia-Idade , Fatores Sexuais , Idoso , Sequenciamento de Nucleotídeos em Larga Escala , Adulto , RNA Ribossômico 16S/genéticaRESUMO
The characteristics of human aging manifest in tissue and organ function decline, heightening susceptibility to age-related ailments, thereby presenting novel challenges to fostering and sustaining healthy longevity. In recent years, an abundance of research on human aging has surfaced. Intriguingly, evidence suggests a pervasive correlation among gut microbiota, bodily functions, and chronic diseases. From infancy to later stages of adulthood, healthy individuals witness dynamic shifts in gut microbiota composition. This microbial community is associated with tissue and organ function deterioration (e.g., brain, bones, muscles, immune system, vascular system) and heightened risk of age-related diseases. Thus, we present a narrative review of the aging gut microbiome in both healthy and unhealthy aging contexts. Additionally, we explore the potential for adjustments to physical health based on gut microbiome analysis and how targeting the gut microbiome can potentially slow down the aging process.
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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.
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Neoplasias Colorretais , MicroRNAs , RNA Longo não Codificante , Humanos , Proteínas de Checkpoint Imunológico/genética , RNA Longo não Codificante/genética , Diferenciação Celular , Neoplasias Colorretais/genética , Linfócitos TRESUMO
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 miRNAâmRNA and 40 miRNAâlncRNA 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.
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Neoplasias Colorretais , MicroRNAs , Humanos , Ácidos e Sais Biliares , Antígeno Ki-67 , Algoritmos , Neoplasias Colorretais/genéticaRESUMO
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.
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Neoplasias Colorretais , Nomogramas , Humanos , Bases de Dados Factuais , Estresse do Retículo Endoplasmático/genética , Neoplasias Colorretais/genética , PrognósticoRESUMO
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.
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Neoplasias Colorretais , Imunoterapia , Humanos , Prognóstico , Neoplasias Colorretais/genética , Neoplasias Colorretais/terapia , Instabilidade de Microssatélites , Microambiente TumoralRESUMO
Cell mediated immune escape, a microenvironment factor, induces tumorigenesis and metastasis. The purpose of this study was to display the characteristics of T cell populations in immune microenvironments for colorectal cancer (CRC) metastasis. Unsupervised cluster analysis was conducted to identify functionally distinct T cell clusters from 3,003 cells in peripheral blood and 4,656 cells in tissues. Subsequently, a total of 8 and 4 distinct T cell population clusters were identified from tumor tissue and peripheral blood, respectively. High levels of CD8+TEX, CD4+TRM, TH1-like T cells, CD8+TEM, tumor-Treg from tissues, and CD4+TN from peripheral blood are essential components of immune microenvironment for the prediction of CRC metastasis. Moreover, exhausted T cells are characterized by higher expression of multiple inhibitory receptors, including PDCD1 and LAG3. Some genes such as PFKFB3, GNLY, circDCUN1D4, TXNIP and NR4A2 in T cells of cluster were statistically different between CRC metastasis and non-metastasis. The ligand-receptor interactions identified between different cluster cells and metastases-related DEGs identified from each cluster revealed that the communications of cells, alterations of functions, and numbers of T subsets may contribute to the metastasis of CRC. The mutation frequency of KiAA1551, ATP8B4 and LNPEP in T cells from tissues and SOR1 from peripheral blood were higher in metastatic CRC than that in non-metastatic CRC. In conclusion, the discovery of differential genes in T cells may provide potential targets for immunotherapy of CRC metastasis and relevant insights into the clinical prediction and prognosis of CRC metastasis.
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Introduction. Differences in gut bacteria that are associated with the occurrence and development of colorectal cancer (CRC) exist between sexes, and males have a higher morbidity of CRC.Gap Statement. Clinical data for the relationship between gut bacteria and sexes in patients with CRC are not available and are needed to support individualized screening and treatment programmes.Aim. To analyse the relationship between gut bacteria and sexes in patients with CRC.Methodology. A total of 6 077 samples recruited by Fudan University's Academy of Brain Artificial Intelligence Science and Technology were included, and the gut bacteria composition mainly shows the top 30 genera. Linear discriminant analysis Effect Size (LEfSe) was used to analyse the differences in gut bacteria. Pearson correlation coefficients were calculated to demonstrate the relationship of discrepant bacteria. CRC risk prediction models were used to rank the importance of valid discrepant bacteria.Results. Bacteroides, Eubacterium and Faecalibacterium were the top three bacteria in males with CRC, while Bacteroides, Subdoligranulum and Eubacterium were the top three bacteria in females with CRC. The abundance of gut bacteria (Escherichia, Eubacteriales, Clostridia, etc.) was higher in males with CRC compared with that in females with CRC. In addition, Dorea and Bacteroides were important CRC-related bacteria (P<0.001). Finally, the importance of discrepant bacteria was ranked based on CRC risk prediction models. Blautia, Barnesiella and Anaerostipes were the top three important discrepant bacteria between males with CRC and females with CRC. The value of AUC was 1.0, the sensitivity was 92.0â%, the specificity was 68.4â%, and the accuracy was 83.3â% in the discovery set.Conclusion. Gut bacteria were correlated with sexes and CRC. It is necessary to consider gender when gut bacteria are used to treat and predict CRC.