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Optimizing cancer immunotherapy response prediction by tumor aneuploidy score and fraction of copy number alterations

Identifying patients that are likely to respond to cancer immunotherapy is an important, yet highly challenging clinical need. Using 3139 patients across 17 different cancer types, we comprehensively studied the ability of two common copy-number alteration (CNA) scores—the tumor aneuploidy score (AS...

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Autores principales: Chang, Tian-Gen, Cao, Yingying, Shulman, Eldad D., Ben-David, Uri, Schäffer, Alejandro A., Ruppin, Eytan
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10239491/
https://www.ncbi.nlm.nih.gov/pubmed/37270587
http://dx.doi.org/10.1038/s41698-023-00408-6
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author Chang, Tian-Gen
Cao, Yingying
Shulman, Eldad D.
Ben-David, Uri
Schäffer, Alejandro A.
Ruppin, Eytan
author_facet Chang, Tian-Gen
Cao, Yingying
Shulman, Eldad D.
Ben-David, Uri
Schäffer, Alejandro A.
Ruppin, Eytan
author_sort Chang, Tian-Gen
collection PubMed
description Identifying patients that are likely to respond to cancer immunotherapy is an important, yet highly challenging clinical need. Using 3139 patients across 17 different cancer types, we comprehensively studied the ability of two common copy-number alteration (CNA) scores—the tumor aneuploidy score (AS) and the fraction of genome single nucleotide polymorphism encompassed by copy-number alterations (FGA)—to predict survival following immunotherapy in both pan-cancer and individual cancer types. First, we show that choice of cutoff during CNA calling significantly influences the predictive power of AS and FGA for patient survival following immunotherapy. Remarkably, by using proper cutoff during CNA calling, AS and FGA can predict pan-cancer survival following immunotherapy for both high-TMB and low-TMB patients. However, at the individual cancer level, our data suggest that the use of AS and FGA for predicting immunotherapy response is currently limited to only a few cancer types. Therefore, larger sample sizes are needed to evaluate the clinical utility of these measures for patient stratification in other cancer types. Finally, we propose a simple, non-parameterized, elbow-point-based method to help determine the cutoff used for calling CNAs.
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spelling pubmed-102394912023-06-05 Optimizing cancer immunotherapy response prediction by tumor aneuploidy score and fraction of copy number alterations Chang, Tian-Gen Cao, Yingying Shulman, Eldad D. Ben-David, Uri Schäffer, Alejandro A. Ruppin, Eytan NPJ Precis Oncol Article Identifying patients that are likely to respond to cancer immunotherapy is an important, yet highly challenging clinical need. Using 3139 patients across 17 different cancer types, we comprehensively studied the ability of two common copy-number alteration (CNA) scores—the tumor aneuploidy score (AS) and the fraction of genome single nucleotide polymorphism encompassed by copy-number alterations (FGA)—to predict survival following immunotherapy in both pan-cancer and individual cancer types. First, we show that choice of cutoff during CNA calling significantly influences the predictive power of AS and FGA for patient survival following immunotherapy. Remarkably, by using proper cutoff during CNA calling, AS and FGA can predict pan-cancer survival following immunotherapy for both high-TMB and low-TMB patients. However, at the individual cancer level, our data suggest that the use of AS and FGA for predicting immunotherapy response is currently limited to only a few cancer types. Therefore, larger sample sizes are needed to evaluate the clinical utility of these measures for patient stratification in other cancer types. Finally, we propose a simple, non-parameterized, elbow-point-based method to help determine the cutoff used for calling CNAs. Nature Publishing Group UK 2023-06-03 /pmc/articles/PMC10239491/ /pubmed/37270587 http://dx.doi.org/10.1038/s41698-023-00408-6 Text en © This is a U.S. Government work and not under copyright protection in the US; foreign copyright protection may apply 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 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/ (https://creativecommons.org/licenses/by/4.0/) .
spellingShingle Article
Chang, Tian-Gen
Cao, Yingying
Shulman, Eldad D.
Ben-David, Uri
Schäffer, Alejandro A.
Ruppin, Eytan
Optimizing cancer immunotherapy response prediction by tumor aneuploidy score and fraction of copy number alterations
title Optimizing cancer immunotherapy response prediction by tumor aneuploidy score and fraction of copy number alterations
title_full Optimizing cancer immunotherapy response prediction by tumor aneuploidy score and fraction of copy number alterations
title_fullStr Optimizing cancer immunotherapy response prediction by tumor aneuploidy score and fraction of copy number alterations
title_full_unstemmed Optimizing cancer immunotherapy response prediction by tumor aneuploidy score and fraction of copy number alterations
title_short Optimizing cancer immunotherapy response prediction by tumor aneuploidy score and fraction of copy number alterations
title_sort optimizing cancer immunotherapy response prediction by tumor aneuploidy score and fraction of copy number alterations
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10239491/
https://www.ncbi.nlm.nih.gov/pubmed/37270587
http://dx.doi.org/10.1038/s41698-023-00408-6
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