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Focus on pattern recognition receptors to identify prognosis and immune microenvironment in colon cancer
In 2011, J. Hoffman, and B. Beutler won the Nobel Prize of medicine for the fact that they discovered the pattern recognition receptors (PRRs) and meanwhile described their effect on cell activation from the innate and adaptive immune systems. There are more and more evidences that have proved the o...
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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Frontiers Media S.A.
2022
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Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9539811/ https://www.ncbi.nlm.nih.gov/pubmed/36212488 http://dx.doi.org/10.3389/fonc.2022.1010023 |
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author | Ren, Pengtao Zhang, Yuan |
author_facet | Ren, Pengtao Zhang, Yuan |
author_sort | Ren, Pengtao |
collection | PubMed |
description | In 2011, J. Hoffman, and B. Beutler won the Nobel Prize of medicine for the fact that they discovered the pattern recognition receptors (PRRs) and meanwhile described their effect on cell activation from the innate and adaptive immune systems. There are more and more evidences that have proved the obvious effect of PRRs on tumorigenesis progression. Nevertheless, the overall impact of PRR genes on prognosis, tumor microenvironmental characteristics and treatment response in patients with colon adenocarcinoma (COAD) remains unclear. In this research, we systematically assessed 20 PRR genes and comprehensively identified the prognostic value and enrichment degree of PRRs. The unsupervised clustering approach was employed for dividing COAD into 4 PRR subtypes, namely cluster A, cluster B, cluster C and cluster D, which were significantly different in terms of the clinical features, the immune infiltrations, and the functions. Among them, cluster B has better immune activities and functions. Cox and LASSO regression analysis was further applied to identify a prognostic five-PRR-based risk signature. Such signature can well predict patients’ overall survival (OS), together with a good robustness. Confounding parameters were controlled, with results indicating the ability of risk score to independently predict COAD patients’ OS. Besides, a nomogram with a strong reliability was created for enhancing the viability exhibited by the risk score in clinical practice. Also, patients who were classified based on the risk score owned distinguishable immune status and tumor mutation status, response to immunotherapy, as well as sensitivity to chemotherapy. A low risk score, featuring increased tumor stemness index (TSI), human leukocyte antigen (HLA), immune checkpoints, and immune activation, demonstrated a superior immunotherapeutic response. According to the study results, the prognostic PRR-based risk signature could serve as a robust biomarker for predicting the clinical outcomes as well as evaluating therapeutic response for COAD patients. |
format | Online Article Text |
id | pubmed-9539811 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-95398112022-10-08 Focus on pattern recognition receptors to identify prognosis and immune microenvironment in colon cancer Ren, Pengtao Zhang, Yuan Front Oncol Oncology In 2011, J. Hoffman, and B. Beutler won the Nobel Prize of medicine for the fact that they discovered the pattern recognition receptors (PRRs) and meanwhile described their effect on cell activation from the innate and adaptive immune systems. There are more and more evidences that have proved the obvious effect of PRRs on tumorigenesis progression. Nevertheless, the overall impact of PRR genes on prognosis, tumor microenvironmental characteristics and treatment response in patients with colon adenocarcinoma (COAD) remains unclear. In this research, we systematically assessed 20 PRR genes and comprehensively identified the prognostic value and enrichment degree of PRRs. The unsupervised clustering approach was employed for dividing COAD into 4 PRR subtypes, namely cluster A, cluster B, cluster C and cluster D, which were significantly different in terms of the clinical features, the immune infiltrations, and the functions. Among them, cluster B has better immune activities and functions. Cox and LASSO regression analysis was further applied to identify a prognostic five-PRR-based risk signature. Such signature can well predict patients’ overall survival (OS), together with a good robustness. Confounding parameters were controlled, with results indicating the ability of risk score to independently predict COAD patients’ OS. Besides, a nomogram with a strong reliability was created for enhancing the viability exhibited by the risk score in clinical practice. Also, patients who were classified based on the risk score owned distinguishable immune status and tumor mutation status, response to immunotherapy, as well as sensitivity to chemotherapy. A low risk score, featuring increased tumor stemness index (TSI), human leukocyte antigen (HLA), immune checkpoints, and immune activation, demonstrated a superior immunotherapeutic response. According to the study results, the prognostic PRR-based risk signature could serve as a robust biomarker for predicting the clinical outcomes as well as evaluating therapeutic response for COAD patients. Frontiers Media S.A. 2022-09-23 /pmc/articles/PMC9539811/ /pubmed/36212488 http://dx.doi.org/10.3389/fonc.2022.1010023 Text en Copyright © 2022 Ren and Zhang 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 Ren, Pengtao Zhang, Yuan Focus on pattern recognition receptors to identify prognosis and immune microenvironment in colon cancer |
title | Focus on pattern recognition receptors to identify prognosis and immune microenvironment in colon cancer |
title_full | Focus on pattern recognition receptors to identify prognosis and immune microenvironment in colon cancer |
title_fullStr | Focus on pattern recognition receptors to identify prognosis and immune microenvironment in colon cancer |
title_full_unstemmed | Focus on pattern recognition receptors to identify prognosis and immune microenvironment in colon cancer |
title_short | Focus on pattern recognition receptors to identify prognosis and immune microenvironment in colon cancer |
title_sort | focus on pattern recognition receptors to identify prognosis and immune microenvironment in colon cancer |
topic | Oncology |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9539811/ https://www.ncbi.nlm.nih.gov/pubmed/36212488 http://dx.doi.org/10.3389/fonc.2022.1010023 |
work_keys_str_mv | AT renpengtao focusonpatternrecognitionreceptorstoidentifyprognosisandimmunemicroenvironmentincoloncancer AT zhangyuan focusonpatternrecognitionreceptorstoidentifyprognosisandimmunemicroenvironmentincoloncancer |