CLCA1

To explore underlying mechanisms related to the progression of colon cancer and identify hub genes associated with the prognosis of patients with colon cancer. GSE10950 and GSE62932 were downloaded from the Gene Expression Omnibus (GEO) database. GEO2R was utilized to screen out the differentially expressed genes (DEGs). Gene ontology (GO) analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis were conducted on DEGs. Moreover, STRING and Cytoscape software were utilized for establishing the network of protein-protein interaction (PPI) and identifying hub genes. Afterward, data from The Cancer Genome Atlas (TCGA) was utilized for identifying prognosis-related hub genes by Kaplan-Meier survival analysis. Colon cancer cell line LOVO and human normal intestinal epithelial cell line NCM-460 were exploited to demonstrate the differential expression of selected hub genes through RT-qPCR and western blot. The LOVO cells were transfected to regulate expressions of prognosis-associated genes, followed by exploring the effects of those genes on prognosis by Cell Counting Kit-8 assay and colony-forming assay for cancer cell proliferation, cell scratch test and transwell migration assay for cancer cell migration and Annexin V-PE/7-AAD double staining as well as flow cytometry for cancer cell apoptosis. In this study, 266 common DEGs were obtained from the intersection of two datasets. The GO analysis suggested the common DEGs mainly participated in the one-carbon metabolic process, cell cycle G2/M phase transition, organelle fission, cell cycle phase transition regulation, and regulation of mitotic cell cycle phase transition. The KEGG analysis demonstrated the common DEGs were related to the p53 signaling pathway, nitrogen metabolism, mineral absorption, and cell cycle. 10 hub genes including CCNB1, KIF4A, TPX2, MT1F, PRC1, PLK4, CALD1, MMP9, CLCA1, and MMP1 were identified and CCNB1, CLCA1, and PLK4 were prognosis-related. Increased expression of CCNB1, CLCA1, and PLK4 restrained proliferation as well as migration of cancer cells and induced apoptosis of cancer cells. CCNB1, KIF4A, TPX2, MT1F, PRC1, PLK4, CALD1, MMP9, CLCA1, and MMP1 were identified as hub genes and CCNB1, CLCA1, and PLK4 could inhibit the progression of colon cancer through inhibiting proliferation as well as migration of the cancer cell and promoting apoptosis of cancer cell.

Animals host complex bacterial communities in their gastrointestinal tracts, with which they share a mutualistic interaction. The numerous effects these interactions grant to the host include regulation of the immune system, defense against pathogen invasion, digestion of otherwise undigestible foodstuffs, and impacts on host behaviour. Exposure to stressors, such as environmental pollution, parasites, and/or predators, can alter the composition of the gut microbiome, potentially affecting host-microbiome interactions that can be manifest in the host as, for example, metabolic dysfunction or inflammation. However, whether a change in gut microbiota in wild animals associates with a change in host condition is seldom examined. Thus, we quantified whether wild bank voles inhabiting a polluted environment, areas where there are environmental radionuclides, exhibited a change in gut microbiota (using 16S amplicon sequencing) and concomitant change in host health using a combined approach of transcriptomics, histological staining analyses of colon tissue, and quantification of short-chain fatty acids in faeces and blood. Concomitant with a change in gut microbiota in animals inhabiting contaminated areas, we found evidence of poor gut health in the host, such as hypotrophy of goblet cells and likely weakened mucus layer and related changes in Clca1 and Agr2 gene expression, but no visible inflammation in colon tissue. Through this case study we show that inhabiting a polluted environment can have wide reaching effects on the gut health of affected animals, and that gut health and other host health parameters should be examined together with gut microbiota in ecotoxicological studies.

This study is designed to explore hub genes participating in colorectal cancer (CRC) development through weighted gene co-expression network analysis (WGCNA).

Expression profiles of CRC and normal samples were retrieved from the Gene Expression Omnibus (GEO) and the Cancer Genome Atlas (TCGA), and were subjected to WGCNA to filter differentially expressed genes with significant association with CRC. Functional enrichment analysis and protein-protein interaction (PPI) analysis were carried out to filter the candidate genes, further and survival analysis was performed for the candidate genes to obtain potential regulatory hub genes in CRC. Expression analysis was conducted for the candidate genes and a multifactor model was established.

After differential analysis and WGCNA, 289 candidate genes were filtered from the GEO and TCGA. Further functional enrichment analysis demonstrated possible regulatory pathways and functions. PPI analysis filtered 15 hub genes and survival analysis indicated a significant correlation of CLCA1, CLCA4, and CPT1A with prognosis of patients with CRC. The multifactor Cox risk model established based on the three genes revealed that if the three genes were a gene set, they had well predictive capacity for the prognosis of patients with CRC.

CLCA1, CLCA4, and CPT1A express at low levels in CRC and function as core anti-tumor genes. As a gene set, they can predict prognosis well.