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Prediction of Biochemical Recurrence-Free Survival of Prostate Cancer Patients Leveraging Multiple Gene Expression Profiles in Tumor Microenvironment
Tumor-adjacent normal (TAN) tissues, which constitute tumor microenvironment and are different from healthy tissues, provide critical information at molecular levels that can be used to differentiate aggressive tumors from indolent tumors. In this study, we analyzed 52 TAN samples from the Cancer Ge...
Autores principales: | , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8495167/ https://www.ncbi.nlm.nih.gov/pubmed/34631510 http://dx.doi.org/10.3389/fonc.2021.632571 |
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author | Zhou, Rui Feng, Yuanfa Ye, Jianheng Han, Zhaodong Liang, Yuxiang Chen, Qingbiao Xu, Xiaoming Huang, Yuhan Jia, Zhenyu Zhong, Weide |
author_facet | Zhou, Rui Feng, Yuanfa Ye, Jianheng Han, Zhaodong Liang, Yuxiang Chen, Qingbiao Xu, Xiaoming Huang, Yuhan Jia, Zhenyu Zhong, Weide |
author_sort | Zhou, Rui |
collection | PubMed |
description | Tumor-adjacent normal (TAN) tissues, which constitute tumor microenvironment and are different from healthy tissues, provide critical information at molecular levels that can be used to differentiate aggressive tumors from indolent tumors. In this study, we analyzed 52 TAN samples from the Cancer Genome Atlas (TCGA) prostate cancer patients and developed a 10-gene prognostic model that can accurately predict biochemical recurrence-free survival based on the profiles of these genes in TAN tissues. The predictive ability was validated using TAN samples from an independent cohort. These 10 prognostic genes in tumor microenvironment are different from the prognostic genes detected in tumor tissues, indicating distinct progression-related mechanisms in two tissue types. Bioinformatics analysis showed that the prognostic genes in tumor microenvironment were significantly enriched by p53 signaling pathway, which may represent the crosstalk tunnels between tumor and its microenvironment and pathways involving cell-to-cell contact and paracrine/endocrine signaling. The insight acquired by this study has advanced our knowledge of the potential role of tumor microenvironment in prostate cancer progression. |
format | Online Article Text |
id | pubmed-8495167 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-84951672021-10-08 Prediction of Biochemical Recurrence-Free Survival of Prostate Cancer Patients Leveraging Multiple Gene Expression Profiles in Tumor Microenvironment Zhou, Rui Feng, Yuanfa Ye, Jianheng Han, Zhaodong Liang, Yuxiang Chen, Qingbiao Xu, Xiaoming Huang, Yuhan Jia, Zhenyu Zhong, Weide Front Oncol Oncology Tumor-adjacent normal (TAN) tissues, which constitute tumor microenvironment and are different from healthy tissues, provide critical information at molecular levels that can be used to differentiate aggressive tumors from indolent tumors. In this study, we analyzed 52 TAN samples from the Cancer Genome Atlas (TCGA) prostate cancer patients and developed a 10-gene prognostic model that can accurately predict biochemical recurrence-free survival based on the profiles of these genes in TAN tissues. The predictive ability was validated using TAN samples from an independent cohort. These 10 prognostic genes in tumor microenvironment are different from the prognostic genes detected in tumor tissues, indicating distinct progression-related mechanisms in two tissue types. Bioinformatics analysis showed that the prognostic genes in tumor microenvironment were significantly enriched by p53 signaling pathway, which may represent the crosstalk tunnels between tumor and its microenvironment and pathways involving cell-to-cell contact and paracrine/endocrine signaling. The insight acquired by this study has advanced our knowledge of the potential role of tumor microenvironment in prostate cancer progression. Frontiers Media S.A. 2021-09-23 /pmc/articles/PMC8495167/ /pubmed/34631510 http://dx.doi.org/10.3389/fonc.2021.632571 Text en Copyright © 2021 Zhou, Feng, Ye, Han, Liang, Chen, Xu, Huang, Jia and Zhong https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. |
spellingShingle | Oncology Zhou, Rui Feng, Yuanfa Ye, Jianheng Han, Zhaodong Liang, Yuxiang Chen, Qingbiao Xu, Xiaoming Huang, Yuhan Jia, Zhenyu Zhong, Weide Prediction of Biochemical Recurrence-Free Survival of Prostate Cancer Patients Leveraging Multiple Gene Expression Profiles in Tumor Microenvironment |
title | Prediction of Biochemical Recurrence-Free Survival of Prostate Cancer Patients Leveraging Multiple Gene Expression Profiles in Tumor Microenvironment |
title_full | Prediction of Biochemical Recurrence-Free Survival of Prostate Cancer Patients Leveraging Multiple Gene Expression Profiles in Tumor Microenvironment |
title_fullStr | Prediction of Biochemical Recurrence-Free Survival of Prostate Cancer Patients Leveraging Multiple Gene Expression Profiles in Tumor Microenvironment |
title_full_unstemmed | Prediction of Biochemical Recurrence-Free Survival of Prostate Cancer Patients Leveraging Multiple Gene Expression Profiles in Tumor Microenvironment |
title_short | Prediction of Biochemical Recurrence-Free Survival of Prostate Cancer Patients Leveraging Multiple Gene Expression Profiles in Tumor Microenvironment |
title_sort | prediction of biochemical recurrence-free survival of prostate cancer patients leveraging multiple gene expression profiles in tumor microenvironment |
topic | Oncology |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8495167/ https://www.ncbi.nlm.nih.gov/pubmed/34631510 http://dx.doi.org/10.3389/fonc.2021.632571 |
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