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RNA Sequencing Data for FFPE Tumor Blocks Can Be Used for Robust Estimation of Tumor Mutation Burden in Individual Biosamples
Tumor mutation burden (TMB) is a well-known efficacy predictor for checkpoint inhibitor immunotherapies. Currently, TMB assessment relies on DNA sequencing data. Gene expression profiling by RNA sequencing (RNAseq) is another type of analysis that can inform clinical decision-making and including TM...
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/PMC8506044/ https://www.ncbi.nlm.nih.gov/pubmed/34650919 http://dx.doi.org/10.3389/fonc.2021.732644 |
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author | Sorokin, Maxim Gorelyshev, Alexander Efimov, Victor Zotova, Evgenia Zolotovskaia, Marianna Rabushko, Elizaveta Kuzmin, Denis Seryakov, Alexander Kamashev, Dmitry Li, Xinmin Poddubskaya, Elena Suntsova, Maria Buzdin, Anton |
author_facet | Sorokin, Maxim Gorelyshev, Alexander Efimov, Victor Zotova, Evgenia Zolotovskaia, Marianna Rabushko, Elizaveta Kuzmin, Denis Seryakov, Alexander Kamashev, Dmitry Li, Xinmin Poddubskaya, Elena Suntsova, Maria Buzdin, Anton |
author_sort | Sorokin, Maxim |
collection | PubMed |
description | Tumor mutation burden (TMB) is a well-known efficacy predictor for checkpoint inhibitor immunotherapies. Currently, TMB assessment relies on DNA sequencing data. Gene expression profiling by RNA sequencing (RNAseq) is another type of analysis that can inform clinical decision-making and including TMB estimation may strongly benefit this approach, especially for the formalin-fixed, paraffin-embedded (FFPE) tissue samples. Here, we for the first time compared TMB levels deduced from whole exome sequencing (WES) and RNAseq profiles of the same FFPE biosamples in single-sample mode. We took TCGA project data with mean sequencing depth 23 million gene-mapped reads (MGMRs) and found 0.46 (Pearson)–0.59 (Spearman) correlation with standard mutation calling pipelines. This was converted into low (<10) and high (>10) TMB per megabase classifier with area under the curve (AUC) 0.757, and application of machine learning increased AUC till 0.854. We then compared 73 experimental pairs of WES and RNAseq profiles with lower (mean 11 MGMRs) and higher (mean 68 MGMRs) RNA sequencing depths. For higher depth, we observed ~1 AUC for the high/low TMB classifier and 0.85 (Pearson)–0.95 (Spearman) correlation with standard mutation calling pipelines. For the lower depth, the AUC was below the high-quality threshold of 0.7. Thus, we conclude that using RNA sequencing of tumor materials from FFPE blocks with enough coverage can afford for high-quality discrimination of tumors with high and low TMB levels in a single-sample mode. |
format | Online Article Text |
id | pubmed-8506044 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-85060442021-10-13 RNA Sequencing Data for FFPE Tumor Blocks Can Be Used for Robust Estimation of Tumor Mutation Burden in Individual Biosamples Sorokin, Maxim Gorelyshev, Alexander Efimov, Victor Zotova, Evgenia Zolotovskaia, Marianna Rabushko, Elizaveta Kuzmin, Denis Seryakov, Alexander Kamashev, Dmitry Li, Xinmin Poddubskaya, Elena Suntsova, Maria Buzdin, Anton Front Oncol Oncology Tumor mutation burden (TMB) is a well-known efficacy predictor for checkpoint inhibitor immunotherapies. Currently, TMB assessment relies on DNA sequencing data. Gene expression profiling by RNA sequencing (RNAseq) is another type of analysis that can inform clinical decision-making and including TMB estimation may strongly benefit this approach, especially for the formalin-fixed, paraffin-embedded (FFPE) tissue samples. Here, we for the first time compared TMB levels deduced from whole exome sequencing (WES) and RNAseq profiles of the same FFPE biosamples in single-sample mode. We took TCGA project data with mean sequencing depth 23 million gene-mapped reads (MGMRs) and found 0.46 (Pearson)–0.59 (Spearman) correlation with standard mutation calling pipelines. This was converted into low (<10) and high (>10) TMB per megabase classifier with area under the curve (AUC) 0.757, and application of machine learning increased AUC till 0.854. We then compared 73 experimental pairs of WES and RNAseq profiles with lower (mean 11 MGMRs) and higher (mean 68 MGMRs) RNA sequencing depths. For higher depth, we observed ~1 AUC for the high/low TMB classifier and 0.85 (Pearson)–0.95 (Spearman) correlation with standard mutation calling pipelines. For the lower depth, the AUC was below the high-quality threshold of 0.7. Thus, we conclude that using RNA sequencing of tumor materials from FFPE blocks with enough coverage can afford for high-quality discrimination of tumors with high and low TMB levels in a single-sample mode. Frontiers Media S.A. 2021-09-28 /pmc/articles/PMC8506044/ /pubmed/34650919 http://dx.doi.org/10.3389/fonc.2021.732644 Text en Copyright © 2021 Sorokin, Gorelyshev, Efimov, Zotova, Zolotovskaia, Rabushko, Kuzmin, Seryakov, Kamashev, Li, Poddubskaya, Suntsova and Buzdin 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 Sorokin, Maxim Gorelyshev, Alexander Efimov, Victor Zotova, Evgenia Zolotovskaia, Marianna Rabushko, Elizaveta Kuzmin, Denis Seryakov, Alexander Kamashev, Dmitry Li, Xinmin Poddubskaya, Elena Suntsova, Maria Buzdin, Anton RNA Sequencing Data for FFPE Tumor Blocks Can Be Used for Robust Estimation of Tumor Mutation Burden in Individual Biosamples |
title | RNA Sequencing Data for FFPE Tumor Blocks Can Be Used for Robust Estimation of Tumor Mutation Burden in Individual Biosamples |
title_full | RNA Sequencing Data for FFPE Tumor Blocks Can Be Used for Robust Estimation of Tumor Mutation Burden in Individual Biosamples |
title_fullStr | RNA Sequencing Data for FFPE Tumor Blocks Can Be Used for Robust Estimation of Tumor Mutation Burden in Individual Biosamples |
title_full_unstemmed | RNA Sequencing Data for FFPE Tumor Blocks Can Be Used for Robust Estimation of Tumor Mutation Burden in Individual Biosamples |
title_short | RNA Sequencing Data for FFPE Tumor Blocks Can Be Used for Robust Estimation of Tumor Mutation Burden in Individual Biosamples |
title_sort | rna sequencing data for ffpe tumor blocks can be used for robust estimation of tumor mutation burden in individual biosamples |
topic | Oncology |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8506044/ https://www.ncbi.nlm.nih.gov/pubmed/34650919 http://dx.doi.org/10.3389/fonc.2021.732644 |
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