Action of m6A-related gene signatures on the prognosis and immune microenvironment of colonic adenocarcinoma.

N6-methyladenosine (m6A) modification in human tumor cells exerts considerable influence on crucial processes like tumorigenesis, invasion, metastasis, and immune response. This study aims to comprehensively analyze the impact of m6A-related genes on the prognosis and immune microenvironment (IME) of colonic adenocarcinoma (COAD). Public data sources, predictive algorithms identified m6A-related genes and differential gene expression in COAD. Subtype analysis and assessment of immune cell infiltration patterns were performed using consensus clustering and the CIBERSORT algorithm. The Least Absolute Shrinkage and Selection Operator (LASSO) regression analysis determined gene signatures. Independent prognostic factors were identified using univariate and multivariate Cox proportional hazards models. The findings indicate that 206 prognostic m6A-related DEGs contribute to the m6A regulatory network along with 8 m6A enzymes. Based on the expression levels of these genes, 438 COAD samples from The Cancer Genome Atlas (TCGA) were classified into 3 distinct subtypes, showing marked differences in survival prognosis, clinical characteristics, and immune cell infiltration profiles. Subtype 3 and 2 displayed reduced levels of infiltrating regulatory T cells and M0 macrophages, respectively. A six-gene signature, encompassing KLC3, SLC6A15, AQP7 JMJD7, HOXC6, and CLDN9, was identified and incorporated into a prognostic model. Validation across TCGA and GSE39582 datasets exhibited robust predictive specificity and sensitivity in determining the survival status of COAD patients. Additionally, independent prognostic factors were recognized, and a nomogram model was developed as a prognostic predictor for COAD. In conclusion, the six target genes governed by m6A mechanisms offer substantial potential in predicting COAD outcomes and provide insights into the unique IME profiles associated with various COAD subtypes.

Age and aging process alter the gut microbes.

BACKGROUND: Gut microbes and age are both factors that influence the development of disease. The community structure of gut microbes is affected by age. OBJECTIVE: To plot time-dependent gut microbe profiles in individuals over 45 years old and explore the correlation between age and gut microbes. METHODS: Fecal samples were collected from 510 healthy individuals over 45 years old. Shannon index, Simpson index, Ace index, etc. were used to analyze the diversity of gut microbes. The beta diversity analysis, including non-metric multidimensional scaling (NMDS), was used to analyze community distribution. Linear discriminant analysis (LDA) and random forest (RF) algorithm were used to analyze the differences of gut microbes. Trend analysis was used to plot the abundances of characteristic gut microbes in different ages. RESULTS: The individuals aged 45-49 had the highest richness of gut bacteria. Fifteen characteristic gut microbes, including Siphoviridae and Bifidobacterium breve, were screened by RF algorithm. The abundance of Ligiactobacillus and Microviridae were higher in individuals older than 65 years. Moreover, the abundance of Blautia_A massiliensis, Lubbockvirus and Enterocloster clostridioformis decreased with age and the abundance of Klebsiella variicola and Prevotella increased with age. The functional genes, such as human diseases and aging, were significantly different among different aged individuals. CONCLUSIONS: The individuals in different ages have characteristic gut microbes. The changes in community structure of gut microbes may be related to age-induced diseases.

Identification of enterotype and its predictive value for patients with colorectal cancer.

BACKGROUND: Gut microbiota dysbiosis involved in the pathogenesis of colorectal cancer (CRC). The characteristics of enterotypes in CRC development have not been determined. OBJECTIVE: To characterize the gut microbiota of healthy, adenoma, and CRC subjects based on enterotype. METHODS: The 16 S rRNA sequencing data from 315 newly sequenced individuals and three previously published datasets were collected, providing total data for 367 healthy, 320 adenomas, and 415 CRC subjects. Enterotypes were analyzed for all samples, and differences in microbiota composition across subjects with different disease states in each enterotype were determined. The predictive values of a random forest classifier based on enterotype in distinguishing healthy, adenoma, and CRC subjects were evaluated and validated. RESULTS: Subjects were classified into one of three enterotypes, namely, Bacteroide- (BA_E), Blautia- (BL_E), and Streptococcus- (S_E) dominated clusters. The taxonomic profiles of these three enterotypes differed among the healthy, adenoma, and CRC cohorts. BA_E group was enriched with Bacteroides and Blautia; BL_E group was enriched by Blautia and Coprococcus; S_E was enriched by Streptococcus and Ruminococcus. Relative abundances of these genera varying among the three human cohorts. In training and validation sets, the S_E cluster showed better performance in distinguishing among CRC patients, adenoma patients, and healthy controls, as well as between CRC and non-CRC individuals, than the other two clusters. CONCLUSION: This study provides the first evidence to indicate that changes in the microbial composition of enterotypes are associated with disease status, thereby highlighting the diagnostic potential of enterotypes in the treatment of adenoma and CRC.

Colorectal cancer and gut viruses: a visualized analysis based on CiteSpace knowledge graph.

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.

Cholesterol induction in CD8+ T cell exhaustion in colorectal cancer via the regulation of endoplasmic reticulum-mitochondria contact sites.

BACKGROUND: Hypercholesterolemia is one of the risk factors for colorectal cancer (CRC). Cholesterol can participate in the regulation of human T cell function and affect the occurrence and development of CRC. OBJECTIVE: To elucidate the pathogenesis of CRC immune escape mediated by CD8+ T cell exhaustion induced by cholesterol. METHODS: CRC samples (n = 217) and healthy individuals (n = 98) were recruited to analyze the relationship between peripheral blood cholesterol levels and the clinical features of CRC. An animal model of CRC with hypercholesterolemia was established. Intraperitoneal intervention with endoplasmic reticulum stress (ERS) inhibitors in hypercholesterolemic CRC mice was performed. CD69, PD1, TIM-3, and CTLA-4 on CD8+ T cells of spleens from C57BL/6 J mice were detected by flow cytometry. CD8+ T cells were cocultured with MC38 cells (mouse colon cancer cell line). The proliferation, apoptosis, migration and invasive ability of MC38 cells were detected by CCK-8 assay, Annexin-V APC/7-AAD double staining, scratch assay and transwell assay, respectively. Transmission electron microscopy was used to observe the ER structure of CD8+ T cells. Western blotting was used to detect the expression of ERS and mitophagy-related proteins. Mitochondrial function and energy metabolism were measured. Immunoprecipitation was used to detect the interaction of endoplasmic reticulum-mitochondria contact site (ERMC) proteins. Immunofluorescence colocalization was used to detect the expression and intracellular localization of ERMC-related molecules. RESULTS: Peripheral blood cholesterol-related indices, including Tc, low density lipoproteins (LDL) and Apo(a), were all increased, and high density lipoprotein (HDL) was decreased in CRCs. The proliferation, migration and invasion abilities of MC38 cells were enhanced, and the proportion of tumor cell apoptosis was decreased in the high cholesterol group. The expression of IL-2 and TNF-α was decreased, while IFN-γ was increased in the high cholesterol group. It indicated high cholesterol could induce exhaustion of CD8+ T cells, leading to CRC immune escape. Hypercholesterolemia damaged the ER structure of CD8+ T cells and increased the expression of ER stress molecules (CHOP and GRP78), lead to CD8+ T cell exhaustion. The expression of mitophagy-related proteins (BNIP3, PINK and Parkin) in exhausted CD8+ T cells increased at high cholesterol levels, causing mitochondrial energy disturbance. High cholesterol enhanced the colocalization of Fis1/Bap31, MFN2/cox4/HSP90B1, VAPB/PTPIP51, VDAC1/IPR3/GRP75 in ERMCs, indicated that high cholesterol promoted the intermolecular interaction between ER and mitochondrial membranes in CD8+ T cells. CONCLUSION: High cholesterol regulated the ERS-ERMC-mitophagy axis to induce the exhaustion of CD8+ T cells in CRC.

Prediction model of colorectal cancer (CRC) lymph node metastasis based on intestinal bacteria.

BACKGROUND: Lymph node metastasis is the main metastatic mode of CRC. Lymph node metastasis affects patient prognosis. OBJECTIVE: To screen differential intestinal bacteria for CRC lymph node metastasis and construct a prediction model. METHODS: First, fecal samples of 119 CRC patients with lymph node metastasis and 110 CRC patients without lymph node metastasis were included for the detection of intestinal bacterial 16S rRNA. Then, bioinformatics analysis of the sequencing data was performed. Community structure and composition analysis, difference analysis, and intragroup and intergroup correlation analysis were conducted between the two groups. Finally, six machine learning models were used to construct a prediction model for CRC lymph node metastasis. RESULTS: The community richness and the community diversity at the genus level of the two groups were basically consistent. A total of 12 differential bacteria (Agathobacter, Catenibacterium, norank_f__Oscillospiraceae, Lachnospiraceae_FCS020_group, Lachnospiraceae_UCG-004, etc.) were screened at the genus level. Differential bacteria, such as Agathobacter, Catenibacterium, norank_f__Oscillospiraceae, and Lachnospiraceae_FCS020_group, were more associated with no lymph node metastasis in CRC. In the discovery set, the RF model had the highest prediction accuracy (AUC = 1.00, 98.89% correct, specificity = 55.21%, sensitivity = 55.95%). In the test set, SVM model had the highest prediction accuracy (AUC = 0.73, 72.92% correct, specificity = 69.23%, sensitivity = 88.89%). Lachnospiraceae_FCS020_group was the most important variable in the RF model. Lachnospiraceae_UCG - 004 was the most important variable in the SVM model. CONCLUSION: CRC lymph node metastasis is closely related to intestinal bacteria. The prediction model based on intestinal bacteria can provide a new evaluation method for CRC lymph node metastasis.

Using whole-genome sequencing (WGS) to plot colorectal cancer-related gut microbiota in a population with varied geography.

BACKGROUND: Colorectal cancer (CRC) is a multifactorial disease with genetic and environmental factors. Regional differences in risk factors are an important reason for the different incidences of CRC in different regions. OBJECTIVE: The goal was to clarify the intestinal microbial composition and structure of CRC patients in different regions and construct CRC risk prediction models based on regional differences. METHODS: A metagenomic dataset of 601 samples from 6 countries in the GMrepo and NCBI databases was collected. All whole-genome sequencing (WGS) data were annotated for species by MetaPhlAn2. We obtained the relative abundance of species composition at the species level and genus level. The MicrobiotaProcess package was used to visualize species composition and PCA. LEfSe analysis was used to analyze the differences in the datasets in each region. Spearman correlation analysis was performed for CRC differential species. Finally, the CRC risk prediction model was constructed and verified in each regional dataset. RESULTS: The composition of the intestinal bacterial community varied in different regions. Differential intestinal bacteria of CRC in different regions are inconsistent. There was a common diversity of bacteria in all six countries, such as Peptostreptococcus stomatis and Fusobacterium nucleatum at the species level. Peptostreptococcus stomatis (species level) and Peptostreptococcus (genus level) are important CRC-related bacteria that are related to other bacteria in different regions. Region has little influence on the accuracy of the CRC risk prediction model. Peptostreptococcus stomatis is an important variable in CRC risk prediction models in all regions. CONCLUSION: Peptostreptococcus stomatis is a common high-risk pathogen of CRC worldwide, and it is an important variable in CRC risk prediction models in all regions. However, regional differences in intestinal bacteria had no significant impact on the accuracy of the CRC risk prediction model.

Biological roles of toll-like receptors and gut microbiota in colorectal cancer.

Colorectal cancer (CRC) is one of the most considerably common malignancies of the alimentary system, with high mortality and incidence rates.  The present study suggested that the occurrence of CRC is closely related to bacteria, as the large intestine is a gathering place for human micro-organisms. However, the nosogenesis of bacteria leading to tumorigenesis is still obscure. Recently, many studies have reported that toll-like receptors and their related molecular pathways are involved in the process of gut micro-organisms generating CRC. Gut micro-organisms can promote or inhibit the development of CRC via binding to special toll-like receptors. In this paper, the authors review the relationship among toll-like receptors, gut micro-organisms and CRC in order to provide a reference for future tumor immunotherapy and targeted therapy.

Novel acetylation-related gene signatures for predicting the prognosis of patients with colorectal cancer.

Histone acetylation may affect the tumorigenesis and prognosis of colorectal cancer (CRC). However, there is still a lack of studies exploring the effect of acetylation-related genes on the prognosis of CRC. To explore the role of acetylation-related genes in CRC prognosis using bioinformatics strategies, the expression data and survival information of CRC patients were collected from the Gene Expression Omnibus. The Molecular Signatures Database was used to select acetylation-related genes. Univariate and least absolute shrinkage and selection operator regression analyses were used to screen prognostic genes. Kaplan-Meier curves were plotted for survival analysis. Cibersort and pRRophetics were used to analyze immune infiltration and predict drug sensitivity, respectively. By implementing independent prognostic factors, a nomogram model was constructed. The result showed that a total of 48 prognostic genes which screened from the acetylation-related gene set were mainly enriched in ABC transporters and acetylation/deacetylation-related pathways. Three gene signatures (SDR16C5, MEAF6, and SOX4) were further defined, and a prognostic model was constructed that showed high sensitivity and specificity for predicting CRC prognosis in both training and validation cohorts. Patients with different prognostic risks also presented differential expression of gene signatures, infiltration of activated CD4 memory T cells, and drug sensitivity to bicalutamide, gefitinib, Lenalidomide, and imatinib. The nomogram suggested the potential of a risk score-based model in predicting 1- and 2-year survival in patients with CRC. In conclusion, we proposed three gene signatures from an acetylation-related gene set as potential targets for epigenetic therapy and constructed a prognostic model for CRC.

Immune-Related Biomarkers Associated with Lung Metastasis from the Colorectal Cancer Microenvironment.

Immune-associated biomarkers can predict lung metastases from colorectal cancer. Differentially expressed genes (DEGs) were screened from sample data extracted from gene expression omnibus (GEO) database. The DEGs were screened from the lung metastasis (LM) and primary cancer (PC) groups of the Moffitt Cancer Center cohort dataset. Then, the tumor immune microenvironment and abundance of immune cell infiltration analyses were performed, and the immune-related DEGs were retrieved. In addition, the transcription factor (TF)-miRNA-mRNA network was constructed and enrichment analyses of the immune-related DEGs and upregulated and downregulated DEGs were carried out. Then, the protein-protein interaction (PPI) network was conducted and the drug-gene interaction was predicted. A total of 268 DEGs were screened. The Immune_Score of samples in the LM group was significantly higher compared with the PC group. The infiltration ratio of M0 macrophages and M2 macrophages of samples was higher than others. A total of 54 immune-related DEGs in M0 macrophages were screened. Moreover, the TF-miRNA-mRNA network was constructed among 8 miRNA-mRNA and 50 TF-mRNA, and the secreted phosphoprotein 1 was regulated by 12 TFs, and the oxidized low-density lipoprotein receptor 1 was regulated by 3 miRNAs and 3 TFs. The TF SAM pointed domain containing ETS TF was also a downregulated DEG. The Kyoto Encyclopedia of Genes and Genomes pathway analysis showed that the DEGs in the TF-miRNA-mRNA network were mainly involved in the interleukin-7 signaling pathway and cell adhesion molecules. In total, 23 protein interactions in this PPI network of M0 macrophage cells were involved in 27 mRNAs. There were 38 drug-gene interactions of immune-related DEGs of M0 macrophage cells predicted to contain 34 small molecule drugs and 8 mRNAs. Finally, the CON cohort dataset verified that the infiltration ratio of M0 and M2 macrophages of the samples was higher.

Open Reading Frame-3a gene of the 2019 novel coronavirus inhibits the occurrence and development of colorectal cancer.

Intestinal microecology is composed of bacteria, fungi and viruses. As a part of intestinal microecology, viruses participate in the occurrence and development of colorectal cancer. The 2019-nCoV was detected in stool samples from patients during COVID-19, suggesting that the 2019-nCoV may be associated with intestinal microecology. However, the relationship of the 2019-nCoV and CRC is unclear. The aim of this study is to explore the role of Open Reading Frame-3a (ORF3a) of the 2019-nCoV in CRC. After the pCDH-CMV-MCS-EF1-Puro vector that provides high expression of ORF3a was transfected into the SW480 CRC cell line, immunofluorescence was used to determine the localization of ORF3a in SW480 cells. The proliferation, migration, invasion, apoptosis, and cell cycle progression of SW480 cells were measured using the Cell Counting Kit-8 (CCK-8), wound healing, Transwell assay, flow cytometry, the TUNEL assay, and propidium iodide single staining. The results showed that ORF3a inhibited the proliferation, invasion, and migration of SW480 cells and induced their apoptosis after 24, 48, 72 h. Meanwhile, ORF3a inhibited the cell cycle and blocked SW480 CRC cells in the G1 phase. In in vivo experiments, high ORF3a expression was associated with decreased tumor volume, tumor weight, relative tumor volume, and tumor activity. ORF3a inhibited the growth and induced apoptosis and necrosis of tumor tissues. Based on this, we demonstrated that ORF3a might play a role in CRC, providing a new direction for the prevention and treatment of CRC.

Screening and analysis of RNAs associated with activated memory CD4 and CD8 T cells in liver cancer.

BACKGROUND: Liver cancer is one of the most common malignant tumors in the world. T cell-mediated antitumor immune response is the basis of liver cancer immunotherapy. OBJECTIVE: To screen and analyze the RNAs associated with activated memory CD4 T cells and CD8 T cells in liver cancer. METHODS: ESTIMATE was used to calculate the stromal and immune scores of tumor samples, which were downloaded from The Cancer Genome Atlas (TCGA). The differentially expressed genes (DEGs) in high and low stromal and immune scores were screened, followed by functional enrichment of overlapped DEGs. We then conducted a survival analysis to identify immune-related prognostic indicators and constructed protein-protein interaction (PPI) networks and ceRNA networks. Finally, chemical small-molecule-target interaction pairs associated with liver cancer were screened. RESULTS: A total of 55,955 stromal-related DEGs and 1811 immune-related DEGs were obtained. The 1238 overlapped DEGs were enriched in 1457 biological process terms and 74 KEGG pathways. In addition, a total of 120 activated memory CD4 T cell-related genes and 309 CD8 T cell-related genes were identified. The survival analysis revealed that upregulated expression of T cell-related genes including EOMES, CST7, and CD5L indicated the favorable prognosis of liver cancer. EOMES was regulated by has-miR-23b-3p and has-miR-23b-3p was regulated by lncRNA AC104820.2 in the ceRNA network of activated memory CD4 T cell-related genes. In addition, EOMES was regulated by has-miR-23a-3p and has-miR-23a-3p was regulated by lncRNA AC000476.1 in the ceRNA network of CD8 T cells. CONCLUSION: T cell-related RNAs EOMES, CST7, CD5L, has-miR-23b-3p, and has-miR-23a-3p may be associated with the prognosis of liver cancer. And the molecular characteristics of these T cell-related genes were plotted.

Mechanisms of induction of tumors by cholesterol and potential therapeutic prospects.

Increasing evidence suggested that cholesterol is an important integrant of cell membranes, that plays a key role in tumor progression, immune dysregulation, and pathological changes in epigenetic mechanisms. Based on these theories, there is a growing interest on targeting cholesterol in the treatment of cancer. Here, we comprehensively reviewed the major function of cholesterol on oncogenicity, the therapeutic targets of cholesterol and its metabolites in cancer, and provide detailed insight into the essential roles of cholesterol in mediating immune and epigenetic mechanisms of the tumor microenvironment. It is also worth mentioning that the gut microbiome is an indispensable component of cancer mediation because of its role in cholesterol metabolism. Finally, we summarized recent studies on the potential targets of cholesterol and their metabolism, to provide more therapeutic interventions in oncology.

Differences in T cell immune-related lncRNA and mRNA expression patterns between right- and left-sided colorectal cancers.

BACKGROUND: Right-sided colorectal cancer (RCRC) and left-sided colorectal cancer (LCRC) harbor different genetic alterations associated with immune response. OBJECTIVE: This study aimed to analyze the differences in T cell immune-related RNA expression patterns between RCRC and LCRC. METHODS: The differentially expressed genes (DEGs) and lncRNAs (DElncRNAs) between LCRC and RCRC were screened from the Cancer Genome Atlas (TCGA) database. A correlation analysis between DEGs or DElncRNAs and differential T cells was also performed to obtain T cell-related genes, followed by miRNA prediction. The mRNA-lncRNA network and the competitive endogenous RNA (ceRNA) network were subsequently constructed, and the expression level of mRNA in the ceRNA network was verified using GSE104645. RESULTS: RCRC patients had a poorer prognosis and were older than LCRC patients. In total, 923 DEGs and 328 DElncRNAs were screened between LCRC and RCRC patients. Compared to RCRC patients, LCRC patients showed a decrease in CD8+ T cells. In addition, 26 miRNAs, 8 mRNAs, and 10 lncRNAs were included in the ceRNA network. Finally, the validation analysis revealed that CDHR1 and PRLR were significantly downregulated, while TRIB2 was upregulated in RCRC patients compared to LCRC patients. CONCLUSION: The analysis of T cell immune-related RNA expression might provide new insights into the underlying molecular mechanisms of the differences between LCRC and RCRC.