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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 prognos...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6819376/ https://www.ncbi.nlm.nih.gov/pubmed/31665031 http://dx.doi.org/10.1186/s12967-019-2102-1 |
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author | Xi, Yang Yuefen, Pan Wei, Wu Quan, Qi Jing, Zhuang Jiamin, Xu Shuwen, Han |
author_facet | Xi, Yang Yuefen, Pan Wei, Wu Quan, Qi Jing, Zhuang Jiamin, Xu Shuwen, Han |
author_sort | Xi, Yang |
collection | PubMed |
description | 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. |
format | Online Article Text |
id | pubmed-6819376 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-68193762019-10-31 Analysis of prognosis, genome, microbiome, and microbial metabolome in different sites of colorectal cancer Xi, Yang Yuefen, Pan Wei, Wu Quan, Qi Jing, Zhuang Jiamin, Xu Shuwen, Han J Transl Med Research 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. BioMed Central 2019-10-29 /pmc/articles/PMC6819376/ /pubmed/31665031 http://dx.doi.org/10.1186/s12967-019-2102-1 Text en © The Author(s) 2019 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated. |
spellingShingle | Research Xi, Yang Yuefen, Pan Wei, Wu Quan, Qi Jing, Zhuang Jiamin, Xu Shuwen, Han Analysis of prognosis, genome, microbiome, and microbial metabolome in different sites of colorectal cancer |
title | Analysis of prognosis, genome, microbiome, and microbial metabolome in different sites of colorectal cancer |
title_full | Analysis of prognosis, genome, microbiome, and microbial metabolome in different sites of colorectal cancer |
title_fullStr | Analysis of prognosis, genome, microbiome, and microbial metabolome in different sites of colorectal cancer |
title_full_unstemmed | Analysis of prognosis, genome, microbiome, and microbial metabolome in different sites of colorectal cancer |
title_short | Analysis of prognosis, genome, microbiome, and microbial metabolome in different sites of colorectal cancer |
title_sort | analysis of prognosis, genome, microbiome, and microbial metabolome in different sites of colorectal cancer |
topic | Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6819376/ https://www.ncbi.nlm.nih.gov/pubmed/31665031 http://dx.doi.org/10.1186/s12967-019-2102-1 |
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