Panels and models for accurate prediction of tumor mutation burden in tumor samples

Abstract Immune checkpoint blockade (ICB) is becoming standard-of-care in many types of human malignancies, but patient selection is still imperfect. Tumor mutation burden (TMB) is being evaluated as a biomarker for ICB in clinical trials, but most of the sequencing panels used to estimate it are in...

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Autores principales:	Elizabeth Martínez-Pérez, Miguel Angel Molina-Vila, Cristina Marino-Buslje
Formato:	article
Lenguaje:	EN
Publicado:	Nature Portfolio 2021
Materias:	Neoplasms. Tumors. Oncology. Including cancer and carcinogens RC254-282
Acceso en línea:	https://doaj.org/article/1b76c4e637d44f018df09d860ec13ed7
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spelling	oai:doaj.org-article:1b76c4e637d44f018df09d860ec13ed72021-12-02T14:25:15ZPanels and models for accurate prediction of tumor mutation burden in tumor samples10.1038/s41698-021-00169-02397-768Xhttps://doaj.org/article/1b76c4e637d44f018df09d860ec13ed72021-04-01T00:00:00Zhttps://doi.org/10.1038/s41698-021-00169-0https://doaj.org/toc/2397-768XAbstract Immune checkpoint blockade (ICB) is becoming standard-of-care in many types of human malignancies, but patient selection is still imperfect. Tumor mutation burden (TMB) is being evaluated as a biomarker for ICB in clinical trials, but most of the sequencing panels used to estimate it are inadequately designed. Here, we present a bioinformatics-based method to select panels and mathematical models for accurate TMB prediction. Our method is based on tumor-specific, forward-step selection of genes, generation of panels using a linear regression algorithm, and rigorous internal and external validation comparing predicted with experimental TMB. As a result, we propose cancer-specific panels for 14 malignancies which can offer reliable, clinically relevant estimates of TMBs. Our work facilitates a better prediction of TMB that can improve the selection of patients for ICB therapy.Elizabeth Martínez-PérezMiguel Angel Molina-VilaCristina Marino-BusljeNature PortfolioarticleNeoplasms. Tumors. Oncology. Including cancer and carcinogensRC254-282ENnpj Precision Oncology, Vol 5, Iss 1, Pp 1-8 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Neoplasms. Tumors. Oncology. Including cancer and carcinogens RC254-282
spellingShingle	Neoplasms. Tumors. Oncology. Including cancer and carcinogens RC254-282 Elizabeth Martínez-Pérez Miguel Angel Molina-Vila Cristina Marino-Buslje Panels and models for accurate prediction of tumor mutation burden in tumor samples
description	Abstract Immune checkpoint blockade (ICB) is becoming standard-of-care in many types of human malignancies, but patient selection is still imperfect. Tumor mutation burden (TMB) is being evaluated as a biomarker for ICB in clinical trials, but most of the sequencing panels used to estimate it are inadequately designed. Here, we present a bioinformatics-based method to select panels and mathematical models for accurate TMB prediction. Our method is based on tumor-specific, forward-step selection of genes, generation of panels using a linear regression algorithm, and rigorous internal and external validation comparing predicted with experimental TMB. As a result, we propose cancer-specific panels for 14 malignancies which can offer reliable, clinically relevant estimates of TMBs. Our work facilitates a better prediction of TMB that can improve the selection of patients for ICB therapy.
format	article
author	Elizabeth Martínez-Pérez Miguel Angel Molina-Vila Cristina Marino-Buslje
author_facet	Elizabeth Martínez-Pérez Miguel Angel Molina-Vila Cristina Marino-Buslje
author_sort	Elizabeth Martínez-Pérez
title	Panels and models for accurate prediction of tumor mutation burden in tumor samples
title_short	Panels and models for accurate prediction of tumor mutation burden in tumor samples
title_full	Panels and models for accurate prediction of tumor mutation burden in tumor samples
title_fullStr	Panels and models for accurate prediction of tumor mutation burden in tumor samples
title_full_unstemmed	Panels and models for accurate prediction of tumor mutation burden in tumor samples
title_sort	panels and models for accurate prediction of tumor mutation burden in tumor samples
publisher	Nature Portfolio
publishDate	2021
url	https://doaj.org/article/1b76c4e637d44f018df09d860ec13ed7
work_keys_str_mv	AT elizabethmartinezperez panelsandmodelsforaccuratepredictionoftumormutationburdenintumorsamples AT miguelangelmolinavila panelsandmodelsforaccuratepredictionoftumormutationburdenintumorsamples AT cristinamarinobuslje panelsandmodelsforaccuratepredictionoftumormutationburdenintumorsamples
_version_	1718391412735606784

Panels and models for accurate prediction of tumor mutation burden in tumor samples

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