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.

Investigating the influence of the gut microbiome on cholelithiasis: unveiling insights through sequencing and predictive modeling.

BACKGROUND: Cholelithiasis is one of the most common disorders of hepatobiliary system. Gut bacteria may be involved in the process of gallstone formation and are, therefore considered as potential targets for cholelithiasis prediction. OBJECTIVE: To reveal the correlation between cholelithiasis and gut bacteria. METHODS: Stool samples were collected from 100 cholelithiasis and 250 healthy individuals from Huzhou Central Hospital; The 16S rRNA of gut bacteria in the stool samples was sequenced using the third-generation Pacbio sequencing platform; Mothur v.1.21.1 was used to analyze the diversity of gut bacteria; Wilcoxon rank-sum test and linear discriminant analysis of effect sizes (LEfSe) were used to analyze differences in gut bacteria between patients suffering from cholelithiasis and healthy individuals; Chord diagram and Plot-related heat maps were used to analyze the correlation between cholelithiasis and gut bacteria; six machine algorithms were used to construct models to predict cholelithiasis. RESULTS: There were differences in the abundance of gut bacteria between cholelithiasis and healthy individuals, but there were no differences in their community diversity. Increased abundance of Costridia, Escherichia flexneri, and Klebsiella pneumonae were found in cholelithiasis, while Bacteroidia, Phocaeicola, and Phocaeicola vulgatus were more abundant in healthy individuals. The top four bacteria that were most closely associated with cholelithiasis were Escherichia flexneri, Escherichia dysenteriae, Streptococcus salivarius, and Phocaeicola vulgatus. The cholelithiasis model based on CatBoost algorithm had the best prediction effect (sensitivity: 90.48%, specificity: 88.32%, and AUC: 0.962). CONCLUSION: The identification of characteristic gut bacteria may provide new predictive targets for gallstone screening. As being screened by the predictive model, people at high risk of cholelithiasis can determine the need for further testing, thus enabling early warning of cholelithiasis.

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.

Traditional Chinese medicine bufalin inhibits infectious hematopoietic necrosis virus infection in vitro and in vivo.

Infectious hematopoietic necrosis virus (IHNV) causes infectious hematopoietic necrosis and severe economic losses to salmon and trout aquaculture worldwide. Currently, the only commercial vaccine against IHNV is a DNA vaccine with some biosafety concerns. Hence, more effective vaccines and antiviral drugs are needed to prevent IHNV infection. In this study, 1,483 compounds were screened from a traditional Chinese medicine monomer library, and bufalin showed potential antiviral activity against IHNV. The 50% cytotoxic concentration of bufalin was >20 µM, and the 50% inhibitory concentration was 0.1223 µΜ against IHNV. Bufalin showed the inhibition of diverse IHNV strains in vitro, which confirmed that it had an inhibitory effect against all IHNV strains, rather than random activity against a single strain. The bufalin-mediated block of IHNV infection occurred at the viral attachment and RNA replication stages, but not internalization. Bufalin also inhibited IHNV infection in vivo and significantly increased the survival of rainbow trout compared with the mock drug-treated group, and this was confirmed by in vivo viral load monitoring. Our data showed that the anti-IHNV activity of bufalin was proportional to extracellular Na+ concentration and inversely proportional to extracellular K+ concentration, and bufalin may inhibit IHNV infection by targeting Na+/K+-ATPase. The in vitro and in vivo studies showed that bufalin significantly inhibited IHNV infection and may be a promising candidate drug against the disease in rainbow trout. IMPORTANCE: Infectious hematopoietic necrosis virus (IHNV) is the pathogen of infectious hematopoietic necrosis (IHN) which outbreak often causes huge economic losses and hampers the healthy development of salmon and trout farming. Currently, there is only one approved DNA vaccine for IHN worldwide, but it faces some biosafety problems. Hence, more effective vaccines and antiviral drugs are needed to prevent IHNV infection. In this study, we report that bufalin, a traditional Chinese medicine, shows potential antiviral activity against IHNV both in vitro and in vivo. The bufalin-mediated block of IHNV infection occurred at the viral attachment and RNA replication stages, but not internalization, and bufalin inhibited IHNV infection by targeting Na+/K+-ATPase. The in vitro and in vivo studies showed that bufalin significantly inhibited IHNV infection and may be a promising candidate drug against the disease in rainbow trout.

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.

Correlation of gut microbiota with leukopenia after chemotherapy in patients with colorectal cancer.

BACKGROUND: The most common toxic side effect after chemotherapy, one of the main treatments for colorectal cancer (CRC), is myelosuppression. OBJECTIVE: To analyze the correlation between gut microbiota and leukopenia after chemotherapy in CRC patients. METHODS: Stool samples were collected from 56 healthy individuals and 55 CRC patients. According to the leukocytes levels in peripheral blood, the CRC patients were divided into hypoleukocytes group (n = 13) and normal leukocytes group (n = 42). Shannon index, Simpson index, Ace index, Chao index and Coverage index were used to analyze the diversity of gut microbiota. LDA and Student's t-test(St test) were used for analysis of differences. Six machine learning algorithms, including logistic regression (LR) algorithm, random forest (RF) algorithm, neural network (NN) algorithm, support vector machine (SVM) algorithm, catboost algorithm and gradient boosting tree algorithm, were used to construct the prediction model of gut microbiota with leukopenia after chemotherapy for CRC. RESULTS: Compared with healthy group, the microbiota alpha diversity of CRC patients was significantly decreased (p < 0.05). After analyzing the gut microbiota differences of the two groups, 15 differential bacteria, such as Bacteroides, Faecalibacterium and Streptococcus, were screened. RF prediction model had the highest accuracy, and the gut microbiota with the highest predictive value were Peptostreptococcus, Faecalibacterium, and norank_f__Ruminococcaceae, respectively. Compared with normal leukocytes group, the microbiota alpha diversity of hypoleukocytes group was significantly decreased (p < 0.05). The proportion of Escherichia-Shigella was significantly decreased in the hypoleukocytes group. After analyzing the gut microbiota differences of the two groups, 9 differential bacteria, such as Escherichia-Shigella, Fusicatenibacter and Cetobacterium, were screened. RF prediction model had the highest accuracy, and the gut microbiota with the highest predictive value were Fusicatenibacte, Cetobacterium, and Paraeggerthella. CONCLUSION: Gut microbiota is related to leukopenia after chemotherapy. The gut microbiota may provide a novel method for predicting myelosuppression after chemotherapy in CRC patients.

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.

Synergistic effect of sodium butyrate and oxaliplatin on colorectal cancer.

BACKGROUND: Oxaliplatin (OXA) is a chemotherapy agent commonly used in the treatment of colorectal cancer (CRC). Sodium butyrate (NaB) has an antitumor effect. METHODS: In total, 30 patients in stage III who completed 8 cycles of chemotherapy regimens were recruited for this study. The patients were divided into good and bad groups based on the chemotherapy efficacy. Gas chromatography-mass spectrometry (GC/MS) was used to detect microbial metabolites in stool samples from CRC patients. Cell counting kit-8 (CCK-8), Annexin-V APC/7-AAD double staining, Transwell assays, scratch-wound assays, and EdU assays were used to detect cell proliferation, apoptosis, invasion and migration, respectively. Fluoroelectron microscopy was used to observe the cell structures. To verify the inhibitory effect of NaB and OXA at animal level, a subcutaneous transplanted tumor model was established. Finally, 16S sequencing technology was used to detect intestinal bacteria. GC-MS was used to detect metabolites in mouse stools. RESULTS: NaB was a differential metabolite that affected the efficacy of OXA. NAB and oxaliplatin can synergically inhibit cell proliferation, migration and invasion, and induce cell apoptosis. Animal experiments confirmed the inhibitory effect of oxaliplatin and sodium butyrate on tumor in mice. In addition, the intestinal microbe detection and microbial metabolite detection in fecal samples from mice showed significant differences between butyrate-producing bacteria and NaB. CONCLUSION: NaB and OXA can synergistically inhibit the proliferation, invasion and metastasis of CRC cells and promote the apoptosis of CRC cells. NaB, as an OXA synergist, has the potential to become a new clinical adjuvant in CRC chemotherapy.

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.

Prediction model of poorly differentiated colorectal cancer (CRC) based on gut bacteria.

BACKGROUND: The mortality of colorectal cancer is high, the malignant degree of poorly differentiated colorectal cancer is high, and the prognosis is poor. OBJECTIVE: To screen the characteristic intestinal microbiota of poorly differentiated intestinal cancer. METHODS: Fecal samples were collected from 124 patients with moderately differentiated CRC and 123 patients with poorly differentiated CRC, and the bacterial 16S rRNA V1-V4 region of the fecal samples was sequenced. Alpha diversity analysis was performed on fecal samples to assess the diversity and abundance of flora. The RDP classifier Bayesian algorithm was used to analyze the community structure. Linear discriminant analysis and Student's t test were used to screen the differences in flora. The PICRUSt1 method was used to predict the bacterial function, and six machine learning models, including logistic regression, random forest, neural network, support vector machine, CatBoost and gradient boosting decision tree, were used to construct a prediction model for the poor differentiation of colorectal cancer. RESULTS: There was no significant difference in fecal flora alpha diversity between moderately and poorly differentiated colorectal cancer (P > 0.05). The bacteria that accounted for a large proportion of patients with poorly differentiated and moderately differentiated colorectal cancer were Blautia, Escherichia-Shigella, Streptococcus, Lactobacillus, and Bacteroides. At the genus level, there were nine bacteria with high abundance in the poorly differentiated group, including Bifidobacterium, norank_f__Oscillospiraceae, Eisenbergiella, etc. There were six bacteria with high abundance in the moderately differentiated group, including Megamonas, Erysipelotrichaceae_UCG-003, Actinomyces, etc. The RF model had the highest prediction accuracy (100.00% correct). The bacteria that had the greatest variable importance in the model were Pseudoramibacter, Megamonas and Bifidobacterium. CONCLUSION: The degree of pathological differentiation of colorectal cancer was related to gut flora, and poorly differentiated colorectal cancer had some different bacterial flora, and intestinal bacteria can be used as biomarkers for predicting poorly differentiated CRC.

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.

Identification and characterization of DEAD-box RNA helicase DDX3 in rainbow trout (Oncorhynchus mykiss) and its relationship with infectious hematopoietic necrosis virus infection.

DDX3, a member of the DEAD-box RNA helicase family and has highly conserved ATP-dependent RNA helicase activity, has important roles in RNA metabolism and innate anti-viral immune responses. In this study, five transcript variants of the DDX3 gene were cloned and characterized from rainbow trout (Oncorhynchus mykiss). These five transcript variants of DDX3 encoded proteins were 74.2 kDa (686 aa), 76.4 kDa (709 aa), 77.8 kDa (711 aa), 78.0 kDa (718 aa), and 78.8 kDa (729 aa) and the predicted isoelectric points were 6.91, 7.63, 7.63, 7.18, and 7.23, respectively. All rainbow trout DDX3 proteins contained two conserved RecA-like domains that were similar to the DDX3 protein reported in mammals. Phylogenetic analysis showed that the five cloned rainbow trout DDX3 were separate from mammals but clustered with fish, especially Northern pike (Esox lucius) and Nile tilapia (Oreochromis niloticus). RT-qPCR analysis showed that the DDX3 gene was broadly expressed in all tissues studied. The expression of DDX3 after infectious hematopoietic necrosis virus (IHNV) infection increased gradually after the early stage of IHNV infection, decreased gradually with the proliferation of IHNV in vivo (liver, spleen, and kidney), and was significantly decreased after the in vitro infection of epithelioma papulosum cyprini (EPC) and rainbow trout gonad cell line-2 (RTG-2) cell lines. We also found that rainbow trout DDX3 was significantly increased by a time-dependent mechanism after the poly I:C treatment of EPC and RTG cells; however no significant changes were observed with lipopolysaccharide (LPS) treatment. Knockdown of DDX3 by siRNA showed significantly increased IHNV replication in infected RTG cells. This study suggests that DDX3 has an important role in host defense against IHNV infection and these results may provide new insights into IHNV pathogenesis and antiviral drug research.

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.

Prognostic model based on six PD-1 expression and immune infiltration-associated genes predicts survival in breast cancer.

BACKGROUND: The prognosis of breast cancer (BC) was associated with the expression of programmed cell death-1 (PD-1). METHODS: BC-related expression and clinical data were downloaded from TCGA database. PD-1 expression with overall survival and clinical factors were investigated. Gene set variation analysis (GSVA) and weighted gene correlation network analysis were performed to investigate the PD-1 expression-associated KEGG pathways and genes, respectively. Immune infiltration was analyzed using the ssGSEA algorithm and DAVID, respectively. Univariate and multivariable Cox and LASSO regression analyses were performed to select prognostic genes for modeling. RESULTS: High PD-1 expression was related to prolonged survival time (P = 0.014). PD-1 expression status showed correlations with age, race, and pathological subtype. ER- and PR-negative patients exhibited high PD-1 expression. The GSVA revealed that high PD-1 expression was associated with various immune-associated pathways, such as T cell/B cell receptor signaling pathway or natural killer cell-mediated cytotoxicity. The patients in the high-immune infiltration group exhibited significantly higher PD-1 expression levels. In summary, 397 genes associated with both immune infiltration and PD-1 expression were screened. Univariate analysis and LASSO regression model identified the six most valuable prognostic genes, namely IRC3, GBP2, IGJ, KLHDC7B, KLRB1, and RAC2. The prognostic model could predict survival for BC patients. CONCLUSION: High PD-1 expression was associated with high-immune infiltration in BC patients. Genes closely associated with PD-1, immune infiltration and survival prognosis were screened to predict prognosis.

Comparative transcriptome analysis of rainbow trout gonadal cells (RTG-2) infected with U and J genogroup infectious hematopoietic necrosis virus.

Infectious hematopoietic necrosis virus (IHNV) is the causative pathogen of infectious hematopoietic necrosis, outbreaks of which are responsible for significant losses in rainbow trout aquaculture. Strains of IHNV isolated worldwide have been classified into five major genogroups, J, E, L, M, and U. To date, comparative transcriptomic analysis has only been conducted individually for the J and M genogroups. In this study, we compared the transcriptome profiles in U genogroup and J genogroup IHNV-infected RTG-2 cells with mock-infected RTG-2 cells. The RNA-seq results revealed 17,064 new genes, of which 7,390 genes were functionally annotated. Differentially expressed gene (DEG) analysis between U and J IHNV-infected cells revealed 2,238 DEGs, including 1,011 downregulated genes and 1,227 upregulated genes. Among the 2,238 DEGs, 345 new genes were discovered. The DEGs related to immune responses, cellular signal transduction, and viral diseases were further analyzed. RT-qPCR validation confirmed that the changes in expression of the immune response-related genes trpm2, sting, itgb7, ripk2, and irf1, cellular signal transduction-related genes irl, cacnb2, bmp2l, gadd45α, and plk2, and viral disease-related genes mlf1, mtor, armc5, pik3r1, and c-myc were consistent with the results of transcriptome analysis. Taken together, our findings provide a comprehensive transcriptional analysis of the differential virulence of the U and J genogroups of IHNV, and shed new light on the pathogenic mechanisms of IHNV strains.

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.

Inhibitory effect of sodium butyrate on colorectal cancer cells and construction of the related molecular network.

BACKGROUND: Sodium butyrate (NaB) is produced through the fermentation of dietary fiber that is not absorbed and digested by the small intestine. PURPOSE: Here, we aimed to investigate the effects of NaB on the proliferation, invasion, and metastasis of CRC cells and their potential underlying molecular mechanism(s). METHODS: The cell counting kit-8 (CCK-8) assay and EdU assay were used to detect cell proliferation ability, flow cytometry was used to investigate the induction of apoptosis and cell cycle progression, and the scratch-wound healing and transwell assays were used to evaluate cell migration and invasion, respectively. The human CRC genome information for tissues and CRC cells treated with NaB obtained from the NCBI GEO database was reannotated and used for differential RNA analysis. Functional and pathway enrichment analyses were performed for differentially expressed lncRNAs and mRNAs. A protein-protein interaction (PPI) network for the hub genes was constructed using the Cytoscape software. Targeted miRNAs were predicted based on the lnCeDB database, and a ceRNA network was constructed using the Cytoscape software. The Kaplan-Meier method was used to analyze patient prognosis using the clinical information and exon-seq data for CRC obtained from the Broad Institute's GDAC Firehose platform. RESULTS: NaB decreased the proliferation ability of CRC cells in a dose- and time-dependent manner. The number of apoptotic CRC cells increased with the increase in NaB concentrations, and NaB induced a G1 phase block in CRC cells. Moreover, NaB suppressed the migratory and invasive capabilities of CRC cells. There were 666 differentially expressed mRNAs and 30 differentially expressed lncRNAs involved in the CRC inhibition by NaB. The PPI network and ceRNA network were constructed based on the differentially expressed mRNAs and lncRNAs. Three differentially expressed mRNAs, including HMGA2, LOXL2, and ST7, were significantly correlated with the prognosis of CRC. CONCLUSION: NaB induces the apoptosis and inhibition of CRC cell proliferation, invasion, and metastasis by modulating complex molecular networks. RNA prediction and molecular network construction need to be the focus of further research in this direction.