An Integrative Bioinformatic Analysis of Microbiome and Transcriptome for Predicting the Risk of Colon Adenocarcinoma.
Jieyang YuCuizhen NongJingjie ZhaoLingzhang MengJian SongPublished in: Disease markers (2022)
The abundance of gut microbiota is significantly decreased in patients with colorectal tumors compared to healthy groups. However, few studies have been conducted to correlate the differences in gut microbiota in colon cancer patients with different prognosis. In this study, we analysed the gut microbiota among patients with colon cancer and determined the microbial characteristics of COAD and divided the overall survival of COAD data into the high- and low-risk groups. In addition, we established a microbiome-related gene map and determined the association between microbial features and immune cell infiltration in COAD. In comparison with the low-risk group, the high risk group of COAD samples exhibited a decreased proportion of activated CD4 T cells as well as an increased proportion of M2 macrophages. The current data suggested that different gut flora backgrounds lead to different gene expression profiles, which in turn affect immune cell typing and colorectal tumor prognosis.
Keyphrases
- genome wide
- microbial community
- electronic health record
- copy number
- big data
- squamous cell carcinoma
- gene expression
- single cell
- dna methylation
- antibiotic resistance genes
- sensitive detection
- machine learning
- fluorescent probe
- living cells
- deep learning
- high density
- rectal cancer
- free survival
- quantum dots
- genetic diversity
- network analysis