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Inflammatory response-based prognostication and personalized therapy decisions in clear cell renal cell cancer to aid precision oncology
OBJECTIVE: The impact of inflammatory response on tumor development and therapeutic response is of significant importance in clear cell renal cell carcinoma (ccRCC). The customization of specialized prognostication approaches and the exploration of supplementary treatment options hold critical clini...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10601329/ https://www.ncbi.nlm.nih.gov/pubmed/37885006 http://dx.doi.org/10.1186/s12920-023-01687-5 |
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author | Zhong, Weimin Chen, Huijing Yang, Jiayi Huang, Chaoqun Lin, Yao Huang, Jiyi |
author_facet | Zhong, Weimin Chen, Huijing Yang, Jiayi Huang, Chaoqun Lin, Yao Huang, Jiyi |
author_sort | Zhong, Weimin |
collection | PubMed |
description | OBJECTIVE: The impact of inflammatory response on tumor development and therapeutic response is of significant importance in clear cell renal cell carcinoma (ccRCC). The customization of specialized prognostication approaches and the exploration of supplementary treatment options hold critical clinical implications in relation to the inflammatory response. METHODS: In the present study, unsupervised clustering was implemented on TCGA-KIRC tumors using transcriptome profiles of inflammatory response genes, which was then validated in two ccRCC datasets (E-MATB-1980 and ICGC) and two immunotherapy datasets (IMvigor210 and Liu et al.) via SubMap and NTP algorithms. Combining co-expression and LASSO analyses, inflammatory response-based scoring system was defined, which was evaluated in pan-cancer. RESULTS: Three reproducible inflammatory response subtypes (named IR1, IR2 and IR3) were determined and independently verified, each exhibiting distinct molecular, clinical, and immunological characteristics. Among these subtypes, IR2 had the best OS outcomes, followed by IR3 and IR1. In terms of anti-angiogenic agents, sunitinib may be appropriate for IR1 patients, while axitinib and pazopanib may be suitable for IR2 patients, and sorafenib for IR3 patients. Additionally, IR1 patients might benefit from anti-CTLA4 therapy. A scoring system called IRscore was defined for individual ccRCC patients. Patients with high IRscore presented a lower response rate to anti-PD-L1 therapy and worse prognostic outcomes. Pan-cancer analysis demonstrated the immunological features and prognostic relevance of the IRscore. CONCLUSION: Altogether, characterization of inflammatory response subtypes and IRscore provides a roadmap for patient risk stratification and personalized treatment decisions, not only in ccRCC, but also in pan-cancer. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12920-023-01687-5. |
format | Online Article Text |
id | pubmed-10601329 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-106013292023-10-27 Inflammatory response-based prognostication and personalized therapy decisions in clear cell renal cell cancer to aid precision oncology Zhong, Weimin Chen, Huijing Yang, Jiayi Huang, Chaoqun Lin, Yao Huang, Jiyi BMC Med Genomics Research OBJECTIVE: The impact of inflammatory response on tumor development and therapeutic response is of significant importance in clear cell renal cell carcinoma (ccRCC). The customization of specialized prognostication approaches and the exploration of supplementary treatment options hold critical clinical implications in relation to the inflammatory response. METHODS: In the present study, unsupervised clustering was implemented on TCGA-KIRC tumors using transcriptome profiles of inflammatory response genes, which was then validated in two ccRCC datasets (E-MATB-1980 and ICGC) and two immunotherapy datasets (IMvigor210 and Liu et al.) via SubMap and NTP algorithms. Combining co-expression and LASSO analyses, inflammatory response-based scoring system was defined, which was evaluated in pan-cancer. RESULTS: Three reproducible inflammatory response subtypes (named IR1, IR2 and IR3) were determined and independently verified, each exhibiting distinct molecular, clinical, and immunological characteristics. Among these subtypes, IR2 had the best OS outcomes, followed by IR3 and IR1. In terms of anti-angiogenic agents, sunitinib may be appropriate for IR1 patients, while axitinib and pazopanib may be suitable for IR2 patients, and sorafenib for IR3 patients. Additionally, IR1 patients might benefit from anti-CTLA4 therapy. A scoring system called IRscore was defined for individual ccRCC patients. Patients with high IRscore presented a lower response rate to anti-PD-L1 therapy and worse prognostic outcomes. Pan-cancer analysis demonstrated the immunological features and prognostic relevance of the IRscore. CONCLUSION: Altogether, characterization of inflammatory response subtypes and IRscore provides a roadmap for patient risk stratification and personalized treatment decisions, not only in ccRCC, but also in pan-cancer. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12920-023-01687-5. BioMed Central 2023-10-26 /pmc/articles/PMC10601329/ /pubmed/37885006 http://dx.doi.org/10.1186/s12920-023-01687-5 Text en © BioMed Central Ltd., part of Springer Nature 2023 https://creativecommons.org/licenses/by/4.0/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 licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence 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 licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data. |
spellingShingle | Research Zhong, Weimin Chen, Huijing Yang, Jiayi Huang, Chaoqun Lin, Yao Huang, Jiyi Inflammatory response-based prognostication and personalized therapy decisions in clear cell renal cell cancer to aid precision oncology |
title | Inflammatory response-based prognostication and personalized therapy decisions in clear cell renal cell cancer to aid precision oncology |
title_full | Inflammatory response-based prognostication and personalized therapy decisions in clear cell renal cell cancer to aid precision oncology |
title_fullStr | Inflammatory response-based prognostication and personalized therapy decisions in clear cell renal cell cancer to aid precision oncology |
title_full_unstemmed | Inflammatory response-based prognostication and personalized therapy decisions in clear cell renal cell cancer to aid precision oncology |
title_short | Inflammatory response-based prognostication and personalized therapy decisions in clear cell renal cell cancer to aid precision oncology |
title_sort | inflammatory response-based prognostication and personalized therapy decisions in clear cell renal cell cancer to aid precision oncology |
topic | Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10601329/ https://www.ncbi.nlm.nih.gov/pubmed/37885006 http://dx.doi.org/10.1186/s12920-023-01687-5 |
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