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A tumor microenvironment-specific gene expression signature predicts chemotherapy resistance in colorectal cancer patients
Studies have shown that tumor microenvironment (TME) might affect drug sensitivity and the classification of colorectal cancer (CRC). Using TME-specific gene signature to identify CRC subtypes with distinctive clinical relevance has not yet been tested. A total of 18 “bulk” RNA-seq datasets (total n...
Autores principales: | , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7881244/ https://www.ncbi.nlm.nih.gov/pubmed/33580207 http://dx.doi.org/10.1038/s41698-021-00142-x |
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author | Zhu, Xiaoqiang Tian, Xianglong Ji, Linhua Zhang, Xinyu Cao, Yingying Shen, Chaoqin Hu, Ye Wong, Jason W. H. Fang, Jing-Yuan Hong, Jie Chen, Haoyan |
author_facet | Zhu, Xiaoqiang Tian, Xianglong Ji, Linhua Zhang, Xinyu Cao, Yingying Shen, Chaoqin Hu, Ye Wong, Jason W. H. Fang, Jing-Yuan Hong, Jie Chen, Haoyan |
author_sort | Zhu, Xiaoqiang |
collection | PubMed |
description | Studies have shown that tumor microenvironment (TME) might affect drug sensitivity and the classification of colorectal cancer (CRC). Using TME-specific gene signature to identify CRC subtypes with distinctive clinical relevance has not yet been tested. A total of 18 “bulk” RNA-seq datasets (total n = 2269) and four single-cell RNA-seq datasets were included in this study. We constructed a “Signature associated with FOLFIRI resistant and Microenvironment” (SFM) that could discriminate both TME and drug sensitivity. Further, SFM subtypes were identified using K-means clustering and verified in three independent cohorts. Nearest template prediction algorithm was used to predict drug response. TME estimation was performed by CIBERSORT and microenvironment cell populations-counter (MCP-counter) methods. We identified six SFM subtypes based on SFM signature that discriminated both TME and drug sensitivity. The SFM subtypes were associated with distinct clinicopathological, molecular and phenotypic characteristics, specific enrichments of gene signatures, signaling pathways, prognosis, gut microbiome patterns, and tumor lymphocytes infiltration. Among them, SFM-C and -F were immune suppressive. SFM-F had higher stromal fraction with epithelial-to-mesenchymal transition phenotype, while SFM-C was characterized as microsatellite instability phenotype which was responsive to immunotherapy. SFM-D, -E, and -F were sensitive to FOLFIRI and FOLFOX, while SFM-A, -B, and -C were responsive to EGFR inhibitors. Finally, SFM subtypes had strong prognostic value in which SFM-E and -F had worse survival than other subtypes. SFM subtypes enable the stratification of CRC with potential chemotherapy response thereby providing more precise therapeutic options for these patients. |
format | Online Article Text |
id | pubmed-7881244 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-78812442021-02-25 A tumor microenvironment-specific gene expression signature predicts chemotherapy resistance in colorectal cancer patients Zhu, Xiaoqiang Tian, Xianglong Ji, Linhua Zhang, Xinyu Cao, Yingying Shen, Chaoqin Hu, Ye Wong, Jason W. H. Fang, Jing-Yuan Hong, Jie Chen, Haoyan NPJ Precis Oncol Article Studies have shown that tumor microenvironment (TME) might affect drug sensitivity and the classification of colorectal cancer (CRC). Using TME-specific gene signature to identify CRC subtypes with distinctive clinical relevance has not yet been tested. A total of 18 “bulk” RNA-seq datasets (total n = 2269) and four single-cell RNA-seq datasets were included in this study. We constructed a “Signature associated with FOLFIRI resistant and Microenvironment” (SFM) that could discriminate both TME and drug sensitivity. Further, SFM subtypes were identified using K-means clustering and verified in three independent cohorts. Nearest template prediction algorithm was used to predict drug response. TME estimation was performed by CIBERSORT and microenvironment cell populations-counter (MCP-counter) methods. We identified six SFM subtypes based on SFM signature that discriminated both TME and drug sensitivity. The SFM subtypes were associated with distinct clinicopathological, molecular and phenotypic characteristics, specific enrichments of gene signatures, signaling pathways, prognosis, gut microbiome patterns, and tumor lymphocytes infiltration. Among them, SFM-C and -F were immune suppressive. SFM-F had higher stromal fraction with epithelial-to-mesenchymal transition phenotype, while SFM-C was characterized as microsatellite instability phenotype which was responsive to immunotherapy. SFM-D, -E, and -F were sensitive to FOLFIRI and FOLFOX, while SFM-A, -B, and -C were responsive to EGFR inhibitors. Finally, SFM subtypes had strong prognostic value in which SFM-E and -F had worse survival than other subtypes. SFM subtypes enable the stratification of CRC with potential chemotherapy response thereby providing more precise therapeutic options for these patients. Nature Publishing Group UK 2021-02-12 /pmc/articles/PMC7881244/ /pubmed/33580207 http://dx.doi.org/10.1038/s41698-021-00142-x Text en © The Author(s) 2021 Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as 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 images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/. |
spellingShingle | Article Zhu, Xiaoqiang Tian, Xianglong Ji, Linhua Zhang, Xinyu Cao, Yingying Shen, Chaoqin Hu, Ye Wong, Jason W. H. Fang, Jing-Yuan Hong, Jie Chen, Haoyan A tumor microenvironment-specific gene expression signature predicts chemotherapy resistance in colorectal cancer patients |
title | A tumor microenvironment-specific gene expression signature predicts chemotherapy resistance in colorectal cancer patients |
title_full | A tumor microenvironment-specific gene expression signature predicts chemotherapy resistance in colorectal cancer patients |
title_fullStr | A tumor microenvironment-specific gene expression signature predicts chemotherapy resistance in colorectal cancer patients |
title_full_unstemmed | A tumor microenvironment-specific gene expression signature predicts chemotherapy resistance in colorectal cancer patients |
title_short | A tumor microenvironment-specific gene expression signature predicts chemotherapy resistance in colorectal cancer patients |
title_sort | tumor microenvironment-specific gene expression signature predicts chemotherapy resistance in colorectal cancer patients |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7881244/ https://www.ncbi.nlm.nih.gov/pubmed/33580207 http://dx.doi.org/10.1038/s41698-021-00142-x |
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