Gut microbes on the risk of advanced adenomas.

BACKGROUND: More than 90% of colorectal cancer (CRC) arises from advanced adenomas (AA) and gut microbes are closely associated with the initiation and progression of both AA and CRC. OBJECTIVE: To analyze the characteristic microbes in AA. METHODS: Fecal samples were collected from 92 AA and 184 negative control (NC). Illumina HiSeq X sequencing platform was used for high-throughput sequencing of microbial populations. The sequencing results were annotated and compared with NCBI RefSeq database to find the microbial characteristics of AA. R-vegan package was used to analyze α diversity and ß diversity. α diversity included box diagram, and ß diversity included Principal Component Analysis (PCA), principal co-ordinates analysis (PCoA), and non-metric multidimensional scaling (NMDS). The AA risk prediction models were constructed based on six kinds of machine learning algorithms. In addition, unsupervised clustering methods were used to classify bacteria and viruses. Finally, the characteristics of bacteria and viruses in different subtypes were analyzed. RESULTS: The abundance of Prevotella sp900557255, Alistipes putredinis, and Megamonas funiformis were higher in AA, while the abundance of Lilyvirus, Felixounavirus, and Drulisvirus were also higher in AA. The Catboost based model for predicting the risk of AA has the highest accuracy (bacteria test set: 87.27%; virus test set: 83.33%). In addition, 4 subtypes (B1V1, B1V2, B2V1, and B2V2) were distinguished based on the abundance of gut bacteria and enteroviruses (EVs). Escherichia coli D, Prevotella sp900557255, CAG-180 sp000432435, Phocaeicola plebeiuA, Teseptimavirus, Svunavirus, Felixounavirus, and Jiaodavirus are the characteristic bacteria and viruses of 4 subtypes. The results of Catboost model indicated that the accuracy of prediction improved after incorporating subtypes. The accuracy of discovery sets was 100%, 96.34%, 100%, and 98.46% in 4 subtypes, respectively. CONCLUSION: Prevotella sp900557255 and Felixounavirus have high value in early warning of AA. As promising non-invasive biomarkers, gut microbes can become potential diagnostic targets for AA, and the accuracy of predicting AA can be improved by typing.

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.

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 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.

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.

Analysis of T lymphocyte-related biomarkers in pancreatic cancer.

BACKGROUND: Pancreatic cancer remains one of the most lethal cancers. OBJECTIVE: This study aimed to analyze T cell-related biomarkers and their molecular network in pancreatic cancer. METHODS: RNAseq sequencing data and clinical data of pancreatic cancer were obtained from TCGA database. The STromal and Immune cells in MAlignant Tumours using Expression data (ESTIMATE) algorithm was used to screen the DEGs related to the tumor immune cells. The pearson correlation analysis were used to analyze the relationships between DEGs and T cells. Additionally, the T cell-related DEGs were subjected to protein-protein interaction, competing endogenous RNA (ceRNA), and chemical small molecule-target network construction. Furthermore, the prognosis-associated DEGs were screened. RESULTS: A total of 412 stromal score-associated and 312 immune score-associated DEGs were obtained. From these DEGs, 50 CD4+ T cell-related genes and 13 CD8+ T cell-related genes were selected. The PPI networks associated with immune cell-related genes were constructed and found that CD22, SELL, and OLR1 had higher degrees in the PPI network. The number of ceRNA regulatory relation pairs obtained from CD4+ T cells and CD8+ T cells were 59 and 48, respectively. Additionally, both CD4+ T cell- and CD8+ T cell-related genes predicted 29 small molecules. CXCL9 and GIMAP7 were screened out from CD4+ T cell-related genes, which were related with the survival of pancreatic cancer. CONCLUSION: We mapped T cell-related gene profile in pancreatic cancer and constructed their potential regulatory network.

Infectious pancreatic necrosis virus inhibits infectious hematopoietic necrosis virus at the early stage of infection in a time dependent manner during Co-infection in Chinook salmon embryo cell lines.

Salmonids can be co-infected by infectious hematopoietic necrosis virus (IHNV) and infectious pancreatic necrosis virus (IPNV) under natural or experimental conditions. To reveal the influence of IPNV on IHNV in co-infections, CHSE-214 cells were inoculated with IPNV at different time intervals prior to or after IHNV infection. Propagation of IHNV was determined by an immunofluorescence antibody test, real-time quantitative polymerase chain reaction, flow cytometry, and virus titration. The results showed that when cells were inoculated with IPNV prior to IHNV, IHNV multiplication was inhibited. This inhibitory effect became stronger with increasing time intervals (P < 0.05). When cells were inoculated with IPNV after IHNV, the inhibitory effect became weaker with increasing time intervals (P < 0.05), and no significant inhibition was observed at 12 h (P > 0.05) compared with the single IHNV infection group. The findings suggest that IHNV is inhibited at the early stage of infection by IPNV and in a time dependent manner during co-infection. Furthermore, the effect of IPNV on IHNV entry and expression of IHNV entry-related genes clathrin, dynamin-2, adaptor protein 2, and vacuolar protein sorting 35 were also determined. The results showed that IPNV did not affect the amount of IHNV entering the cells. However, the expression levels of clathrin and dynamin-2 were significantly lower in co-infection than those in single IHNV infection, which suggests that IPNV likely inhibits IHNV by affecting IHNV invasion via downregulating IHNV entry-related genes clathrin and dynamin-2.

Analysis of prognosis, genome, microbiome, and microbial metabolome in different sites of colorectal cancer.

BACKGROUND: The colorectum includes ascending colon, transverse colon, descending colon, sigmoid colon, and rectum. Different sites of colorectal cancer (CRC) are different in many aspects, including clinical symptoms, biological behaviour, and prognosis. PURPOSE: This study aimed to analyse prognosis, genes, bacteria, fungi, and microbial metabolome in different sites of CRC. METHODS: The Surveillance, Epidemiology, and End Results (SEER) database and STAT were used to statistically describe and analyse the prognosis in different sites of CRC. RNA sequences of CRC from Broad Institute's GDAC Firehose were re-annotated and reanalysed based on different sites using weighted gene co-expression network analysis (WGCNA). The Kaplan-Meier method was used to analyse the prognosis and Cytoscape was used to construct a drug-target network based on DGIdb databases. Bacterial 16S V3-V4 and fungal ITS V3-V4 ribosomal RNA genes of stool samples were sequenced. Gas chromatography/mass spectrometry (GS/MS) was performed to detect the microbial metabolites in stool samples. Bioinformatics analysis was performed to compare distinct gut microorganisms and microbial metabolites between rectal and sigmoid cancers. RESULTS: The prognosis in CRC with different sites is significantly different. The closer to the anus predicted longer survival time. The difference between genes and co-expression pairs in CRC with different sites were constructed. The relative abundance of 112 mRNAs and 26 lncRNAs correlated with the sites of CRC were listed. Nine differentially expressed genes at different sites of CRC were correlated with prognosis. A drug-gene interaction network contained 227 drug-gene pairs were built. The relative abundance of gut bacteria and gut fungus, and the content of microbe-related metabolites were statistically different between rectal and sigmoid cancers. CONCLUSIONS: There are many differences in prognosis, genome, drug targets, gut microbiome, and microbial metabolome in different colorectal cancer sites. These findings may improve our understanding of the role of the CRC sites in personalized and precision medicine.

Identification of the optimal insertion site for expression of a foreign gene in an infectious hematopoietic necrosis virus vector.

Infectious hematopoietic necrosis virus (IHNV) was developed as a vector to aid the construction of vaccines against viral diseases such as viral hemorrhagic septicemia virus, spring viremia of carp virus, and influenza virus H1N1. However, the optimal site for foreign gene expression in the IHNV vector has not been determined. In the present study, five recombinant viruses with the green fluorescence protein (GFP) gene inserted into different genomic junction regions of the IHNV genomic sequence were generated using reverse genetics technology. Viral growth was severely delayed when the GFP gene was inserted into the intergenic region between the N and P genes. Real-time fluorescence quantitative PCR assays showed that the closer the GFP gene was inserted towards the 3' end, the higher the GFP mRNA levels. Measurement of the GFP fluorescence intensity, which is the most direct method to determine the GFP protein expression level, showed that the highest GFP protein level was obtained when the gene was inserted into the intergenic region between the P and M genes. The results of this study suggest that the P and M gene junction region is the optimal site within the IHNV vector to express foreign genes, providing valuable information for the future development of live vector vaccines.

Complete genomic sequence of an infectious pancreatic necrosis virus isolated from rainbow trout (Oncorhynchus mykiss) in China.

Infectious pancreatic necrosis (IPN) is a significant disease of farmed salmonids resulting in direct economic losses due to high mortality in China. However, no gene sequence of any Chinese infectious pancreatic necrosis virus (IPNV) isolates was available. In the study, moribund rainbow trout fry samples were collected during an outbreak of IPN in Yunnan province of southwest China in 2013. An IPNV was isolated and tentatively named ChRtm213. We determined the full genome sequence of the IPNV ChRtm213 and compared it with previously identified IPNV sequences worldwide. The sequences of different structural and non-structural protein genes were compared to those of other aquatic birnaviruses sequenced to date. The results indicated that the complete genome sequence of ChRtm213 strain contains a segment A (3099 nucleotides) coding a polyprotein VP2-VP4-VP3, and a segment B (2789 nucleotides) coding a RNA-dependent RNA polymerase VP1. The phylogenetic analyses showed that ChRtm213 strain fell within genogroup 1, serotype A9 (Jasper), having similarities of 96.3% (segment A) and 97.3% (segment B) with the IPNV strain AM98 from Japan. The results suggest that the Chinese IPNV isolate has relative closer relationship with Japanese IPNV strains. The sequence of ChRtm213 was the first gene sequence of IPNV isolates in China. This study provided a robust reference for diagnosis and/or control of IPNV prevalent in China.

Epitope mapping of the infectious hematopoietic necrosis virus glycoprotein by flow cytometry.

The glycoprotein of infectious hematopoietic necrosis virus was truncated to ten overlapping fragments. All fragments were displayed on the inner membrane of the Escherichia coli periplasm. After disruption of the outer membrane, spheroplasts that had anchored with the glycoprotein fragment were incubated with an anti-glycoprotein polyclonal antibody. Prey pairs were detected and quantitated by flow cytometry with all fragments but one, G2, reacting with the polyclonal antibody. The antigenicity of all ten fragments was analyzed using conventional methods, and epitopes were localized in all fragments, except for G2 and were consistent with FCM analysis. Antigenicity of purified glycoprotein fusion proteins was confirmed by western blotting and ELISA. This method provides a rapid, quantitative and simple strategy for identifying linear B cell epitopes of a given protein.

scFv antibodies against infectious bursal disease virus isolated from a combinatorial antibody library by flow cytometry.

Infectious bursal disease is an economically important disease that affects chickens worldwide. Here, a recombinant single chain variable fragment (scFv) antibody library derived from chickens immunized with VP2 protein of infectious bursal disease virus (IBDV) was constructed. The library was subjected to three rounds of screening by flow cytometry against VP2 protein through a bacteria display technology, resulting in the enrichment of scFv. Three scFv clones with different fluorescence intensity were obtained by random colony pick up. The isolated scFv antibodies were expressed and purified. Relative affinity assay showed the three clones had different sensitivity to VP2, in accordance with fluorescence activity cell sorting analysis. The potential use of the selected IBDV-specific scFv antibodies was demonstrated by the successful application of the isolated antibodies in western blotting assay and ELISA.

Escherichia coli on colorectal cancer: A two-edged sword.

Escherichia coli (E. coli) is a ubiquitous symbiotic bacterium in the gut, and the diversity of E. coli genes determines the diversity of its functions. In this review, the two-edged sword theory was innovatively proposed. For the question 'how can we harness the ambivalent nature of E. coli to screen and treat CRC?', in terms of CRC screening, the variations in the abundance and subtypes of E. coli across different populations present an opportunity to utilise it as a biomarker, while in terms of CRC treatment, the natural beneficial effect of E. coli on CRC may be limited, and engineered E. coli, particularly certain subtypes with probiotic potential, can indeed play a significant role in CRC treatment. It seems that the favourable role of E. coli as a genetic tool lies not in its direct impact on CRC but its potential as a research platform that can be integrated with various technologies such as nanoparticles, imaging methods, and synthetic biology modification. The relationship between gut microflora and CRC remains unclear due to the complex diversity and interaction of gut microflora. Therefore, the application of E. coli should be based on the 'One Health' view and take the interactions between E. coli and other microorganisms, host, and environmental factors, as well as its own changes into account. In this paper, the two-edged sword role of E. coli in CRC is emphasised to realise the great potential of E. coli in CRC screening and treatment.

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.

Trace elements in pancreatic cancer.

BACKGROUND: Pancreatic cancer (PCA) is an extremely aggressive malignant cancer with an increasing incidence and a low five-year survival rate. The main reason for this high mortality is that most patients are diagnosed with PCA at an advanced stage, missing early treatment options and opportunities. As important nutrients of the human body, trace elements play an important role in maintaining normal physiological functions. Moreover, trace elements are closely related to many diseases, including PCA. REVIEW: This review systematically summarizes the latest research progress on selenium, copper, arsenic, and manganese in PCA, elucidates their application in PCA, and provides a new reference for the prevention, diagnosis and treatment of PCA. CONCLUSION: Trace elements such as selenium, copper, arsenic and manganese are playing an important role in the risk, pathogenesis, diagnosis and treatment of PCA. Meanwhile, they have a certain inhibitory effect on PCA, the mechanism mainly includes: promoting ferroptosis, inducing apoptosis, inhibiting metastasis, and inhibiting excessive proliferation.

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.

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.

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.

[The long lasting effect of the murine fibroblast growth factor-21 on blood glucose control of diabetic animals].

Insulin is the most common medicine used for diabetic patients, unfortunately, its effective time is short, even the long-acting insulin cannot obtain a satisfactory effect. Fibroblast growth factor (FGF)-21 is a recently discovered glucose mediator and expected to be a potential anti-diabetic drug that does not rely on insulin. In this study, db/db mice were used as the type 2 diabetic model to examine whether mFGF-21 has the long-term blood lowering effect on the animal model. The results showed that mFGF-21 could stably maintain the blood glucose at normal level for a long-term in a dose-dependent manner. Administration of mFGF-21 once a day with three doses (0.125, 0.25 and 0.5 mg x kg(-1)) could maintain blood glucose of the model animals at normal level for at least 24 h. Administration of mFGF-21 every two days with the same doses could maintain blood glucose of the model animals at normal level for at least 48 h, although it took longer time for blood glucose to reach to normal level depending on doses used (twenty injections for 0.125 mg x kg(-1) and 0.25 mg x kg(-1) doses, ten injections for 0.5 mg x kg(-1) dose). Surprisingly, the blood glucose of the treated model animals still maintained at normal level for 24 h after the experiment terminated. Glycosylated hemoglobin level of the animals treated with mFGF-21, which represented long-term glucose status, decreased significantly compared to the control group and the insulin group. The results suggest that FGF-21 has potential to become a long-acting and potent anti-diabetic drug.