Cargando…
Bias and inconsistency in the estimation of tumour mutation burden
BACKGROUND: Tumour mutation burden (TMB), defined as the number of somatic mutations per megabase within the sequenced region in the tumour sample, has been used as a biomarker for predicting response to immune therapy. Several studies have been conducted to assess the utility of TMB for various can...
Autores principales: | , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2022
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9347149/ https://www.ncbi.nlm.nih.gov/pubmed/35918650 http://dx.doi.org/10.1186/s12885-022-09897-3 |
_version_ | 1784761802855284736 |
---|---|
author | Makrooni, Mohammad A. O’Sullivan, Brian Seoighe, Cathal |
author_facet | Makrooni, Mohammad A. O’Sullivan, Brian Seoighe, Cathal |
author_sort | Makrooni, Mohammad A. |
collection | PubMed |
description | BACKGROUND: Tumour mutation burden (TMB), defined as the number of somatic mutations per megabase within the sequenced region in the tumour sample, has been used as a biomarker for predicting response to immune therapy. Several studies have been conducted to assess the utility of TMB for various cancer types; however, methods to measure TMB have not been adequately evaluated. In this study, we identified two sources of bias in current methods to calculate TMB. METHODS: We used simulated data to quantify the two sources of bias and their effect on TMB calculation, we down-sampled sequencing reads from exome sequencing datasets from TCGA to evaluate the consistency in TMB estimation across different sequencing depths. We analyzed data from ten cancer cohorts to investigate the relationship between inferred TMB and sequencing depth. RESULTS: We found that TMB, estimated by counting the number of somatic mutations above a threshold frequency (typically 0.05), is not robust to sequencing depth. Furthermore, we show that, because only mutations with an observed frequency greater than the threshold are considered, the observed mutant allele frequency provides a biased estimate of the true frequency. This can result in substantial over-estimation of the TMB, when the cancer sample includes a large number of somatic mutations at low frequencies, and exacerbates the lack of robustness of TMB to variation in sequencing depth and tumour purity. CONCLUSION: Our results demonstrate that care needs to be taken in the estimation of TMB to ensure that results are unbiased and consistent across studies and we suggest that accurate and robust estimation of TMB could be achieved using statistical models that estimate the full mutant allele frequency spectrum. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at (10.1186/s12885-022-09897-3). |
format | Online Article Text |
id | pubmed-9347149 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-93471492022-08-04 Bias and inconsistency in the estimation of tumour mutation burden Makrooni, Mohammad A. O’Sullivan, Brian Seoighe, Cathal BMC Cancer Research BACKGROUND: Tumour mutation burden (TMB), defined as the number of somatic mutations per megabase within the sequenced region in the tumour sample, has been used as a biomarker for predicting response to immune therapy. Several studies have been conducted to assess the utility of TMB for various cancer types; however, methods to measure TMB have not been adequately evaluated. In this study, we identified two sources of bias in current methods to calculate TMB. METHODS: We used simulated data to quantify the two sources of bias and their effect on TMB calculation, we down-sampled sequencing reads from exome sequencing datasets from TCGA to evaluate the consistency in TMB estimation across different sequencing depths. We analyzed data from ten cancer cohorts to investigate the relationship between inferred TMB and sequencing depth. RESULTS: We found that TMB, estimated by counting the number of somatic mutations above a threshold frequency (typically 0.05), is not robust to sequencing depth. Furthermore, we show that, because only mutations with an observed frequency greater than the threshold are considered, the observed mutant allele frequency provides a biased estimate of the true frequency. This can result in substantial over-estimation of the TMB, when the cancer sample includes a large number of somatic mutations at low frequencies, and exacerbates the lack of robustness of TMB to variation in sequencing depth and tumour purity. CONCLUSION: Our results demonstrate that care needs to be taken in the estimation of TMB to ensure that results are unbiased and consistent across studies and we suggest that accurate and robust estimation of TMB could be achieved using statistical models that estimate the full mutant allele frequency spectrum. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at (10.1186/s12885-022-09897-3). BioMed Central 2022-08-02 /pmc/articles/PMC9347149/ /pubmed/35918650 http://dx.doi.org/10.1186/s12885-022-09897-3 Text en © The Author(s) 2022 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 Makrooni, Mohammad A. O’Sullivan, Brian Seoighe, Cathal Bias and inconsistency in the estimation of tumour mutation burden |
title | Bias and inconsistency in the estimation of tumour mutation burden |
title_full | Bias and inconsistency in the estimation of tumour mutation burden |
title_fullStr | Bias and inconsistency in the estimation of tumour mutation burden |
title_full_unstemmed | Bias and inconsistency in the estimation of tumour mutation burden |
title_short | Bias and inconsistency in the estimation of tumour mutation burden |
title_sort | bias and inconsistency in the estimation of tumour mutation burden |
topic | Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9347149/ https://www.ncbi.nlm.nih.gov/pubmed/35918650 http://dx.doi.org/10.1186/s12885-022-09897-3 |
work_keys_str_mv | AT makroonimohammada biasandinconsistencyintheestimationoftumourmutationburden AT osullivanbrian biasandinconsistencyintheestimationoftumourmutationburden AT seoighecathal biasandinconsistencyintheestimationoftumourmutationburden |