Dataset Information

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

ABSTRACT: 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.

SUBMITTER: Xi Y

PROVIDER: S-EPMC6819376 | biostudies-literature | 2019 Oct

REPOSITORIES: biostudies-literature

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

Xi Yang Y Yuefen Pan P Wei Wu W Quan Qi Q Jing Zhuang Z Jiamin Xu X Shuwen Han H

Journal of translational medicine 20191029 1

<h4>Background</h4>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.<h4>Purpose</h4>This study aimed to analyse prognosis, genes, bacteria, fungi, and microbial metabolome in different sites of CRC.<h4>Methods</h4>The Surveillance, Epidemiology, and End Results (SEER) database and STAT were used to statis ...[more]

PMID: 31665031

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Project description:Accumulating evidence indicates that the gut microbiome and metabolites are associated with colorectal cancer (CRC). However, the influence of surgery for CRC treatment on the gut microbiome and metabolites and how it relates to CRC risk in postoperative CRC patients remain partially understood. Here, we collected 170 fecal samples from 85 CRC patients pre- and approximately 1 year postsurgery and performed shotgun metagenomic sequencing and capillary electrophoresis-time of flight mass spectrometry-based metabolomics analyses to characterize alterations between pre- and postsurgery. We determined that the relative abundance of 114 species was altered postsurgery (P < 0.005). CRC-associated species, such as Fusobacterium nucleatum, were decreased postsurgery. On the other hand, Clostridium scindens, carcinogenesis-associated deoxycholate (DCA)-producing species, and its biotransformed genes (bai operon) were increased postsurgery. The concentration of 60 fecal metabolites was also altered postsurgery (P < 0.005). Two bile acids, cholate and DCA, were increased postsurgery. We developed methods to estimate postoperative CRC risk based on the gut microbiome and metabolomic compositions using a random forest machine-learning algorithm that classifies large adenoma or early-stage CRC and healthy controls from publicly available data sets. We applied methods to preoperative samples and then compared the estimated CRC risk between the two groups according to the presence of large adenoma or tumors 5 years postsurgery (P < 0.05). Overall, our results show that the gut microbiome and metabolites dynamically change from pre- to postsurgery. In postoperative CRC patients, potential CRC risk derived from gut microbiome and metabolites still remains, which indicates the importance of follow-up assessments. IMPORTANCE The gut microbiome and metabolites are associated with CRC progression and carcinogenesis. Postoperative CRC patients are reported to be at an increased CRC risk; however, how gut microbiome and metabolites are related to CRC risk in postoperative patients remains only partially understood. In this study, we investigated the influence of surgical CRC treatment on the gut microbiome and metabolites. We found that the CRC-associated species Fusobacterium nucleatum was decreased postsurgery, whereas carcinogenesis-associated DCA and its producing species and genes were increased postsurgery. We developed methods to estimate postoperative CRC risk based on the gut microbiome and metabolomic compositions. We applied methods to compare the estimated CRC risk between two groups according to the presence of large adenoma or tumors after 5 years postsurgery. To our knowledge, this study is the first report on differences between pre- and postsurgery using metagenomics and metabolomics data analysis. Our methods might be used for CRC risk assessment in postoperative patients.

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Dataset Information

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

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

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