Tumour mutational burden is overestimated by target cancer gene panels
Background: Tumour mutational burden (TMB) has emerged as a predictive marker for responsiveness to immune checkpoint inhibitors (ICI) in multiple tumour types. It can be calculated from somatic mutations detected from whole exome or targeted panel sequencing data. As mutations are unevenly distribu...
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| Format: | Article |
| Language: | English |
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Elsevier
2023-03-01
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| Series: | Journal of the National Cancer Center |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S2667005422000801 |
| _version_ | 1811160180337934336 |
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| author | Hu Fang Johanna Bertl Xiaoqiang Zhu Tai Chung Lam Song Wu David J.H. Shih Jason W.H. Wong |
| author_facet | Hu Fang Johanna Bertl Xiaoqiang Zhu Tai Chung Lam Song Wu David J.H. Shih Jason W.H. Wong |
| author_sort | Hu Fang |
| collection | DOAJ |
| description | Background: Tumour mutational burden (TMB) has emerged as a predictive marker for responsiveness to immune checkpoint inhibitors (ICI) in multiple tumour types. It can be calculated from somatic mutations detected from whole exome or targeted panel sequencing data. As mutations are unevenly distributed across the cancer genome, the clinical implications from TMB calculated using different genomic regions are not clear. Methods: Pan-cancer data of 10,179 samples were collected from The Cancer Genome Atlas cohort and 6,831 cancer patients with either ICI or non-ICI treatment outcomes were derived from published papers. TMB was calculated as the count of non-synonymous mutations and normalised by the size of genomic regions. Dirichlet method, linear regression and Poisson calibration models are used to unify TMB from different gene panels. Results: We found that panels based on cancer genes usually overestimate TMB compared to whole exome, potentially leading to misclassification of patients to receive ICI. The overestimation is caused by positive selection for mutations in cancer genes and cannot be completely addressed by the removal of mutational hotspots. We compared different approaches to address this discrepancy and developed a generalised statistical model capable of interconverting TMB derived from whole exome and different panel sequencing data, enabling TMB correction for patient stratification for ICI treatment. We show that in a cohort of lung cancer patients treated with ICI, when using a TMB cutoff of 10 mut/Mb, our corrected TMB outperforms the original panel-based TMB. Conclusion: Cancer gene-based panels usually overestimate TMB, and these findings will be valuable for unifying TMB calculations across cancer gene panels in clinical practice. |
| first_indexed | 2024-04-10T05:53:14Z |
| format | Article |
| id | doaj.art-c1a82c0bc35b4094904ae14b4fc489ba |
| institution | Directory Open Access Journal |
| issn | 2667-0054 |
| language | English |
| last_indexed | 2024-04-10T05:53:14Z |
| publishDate | 2023-03-01 |
| publisher | Elsevier |
| record_format | Article |
| series | Journal of the National Cancer Center |
| spelling | doaj.art-c1a82c0bc35b4094904ae14b4fc489ba2023-03-04T04:24:04ZengElsevierJournal of the National Cancer Center2667-00542023-03-01315664Tumour mutational burden is overestimated by target cancer gene panelsHu Fang0Johanna Bertl1Xiaoqiang Zhu2Tai Chung Lam3Song Wu4David J.H. Shih5Jason W.H. Wong6School of Biomedical Sciences, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong, China; South China Hospital, Health Science Center, Shenzhen University, Shenzhen, ChinaDepartment of Mathematics, Aarhus University, Aarhus, DenmarkSchool of Biomedical Sciences, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong, ChinaDepartment of Clinical Oncology, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong, ChinaSouth China Hospital, Health Science Center, Shenzhen University, Shenzhen, ChinaSchool of Biomedical Sciences, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong, China; Corresponding authors.School of Biomedical Sciences, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong, China; Corresponding authors.Background: Tumour mutational burden (TMB) has emerged as a predictive marker for responsiveness to immune checkpoint inhibitors (ICI) in multiple tumour types. It can be calculated from somatic mutations detected from whole exome or targeted panel sequencing data. As mutations are unevenly distributed across the cancer genome, the clinical implications from TMB calculated using different genomic regions are not clear. Methods: Pan-cancer data of 10,179 samples were collected from The Cancer Genome Atlas cohort and 6,831 cancer patients with either ICI or non-ICI treatment outcomes were derived from published papers. TMB was calculated as the count of non-synonymous mutations and normalised by the size of genomic regions. Dirichlet method, linear regression and Poisson calibration models are used to unify TMB from different gene panels. Results: We found that panels based on cancer genes usually overestimate TMB compared to whole exome, potentially leading to misclassification of patients to receive ICI. The overestimation is caused by positive selection for mutations in cancer genes and cannot be completely addressed by the removal of mutational hotspots. We compared different approaches to address this discrepancy and developed a generalised statistical model capable of interconverting TMB derived from whole exome and different panel sequencing data, enabling TMB correction for patient stratification for ICI treatment. We show that in a cohort of lung cancer patients treated with ICI, when using a TMB cutoff of 10 mut/Mb, our corrected TMB outperforms the original panel-based TMB. Conclusion: Cancer gene-based panels usually overestimate TMB, and these findings will be valuable for unifying TMB calculations across cancer gene panels in clinical practice.http://www.sciencedirect.com/science/article/pii/S2667005422000801Tumour mutational burdenImmune checkpoint inhibitorImmune responseBiomarker |
| spellingShingle | Hu Fang Johanna Bertl Xiaoqiang Zhu Tai Chung Lam Song Wu David J.H. Shih Jason W.H. Wong Tumour mutational burden is overestimated by target cancer gene panels Journal of the National Cancer Center Tumour mutational burden Immune checkpoint inhibitor Immune response Biomarker |
| title | Tumour mutational burden is overestimated by target cancer gene panels |
| title_full | Tumour mutational burden is overestimated by target cancer gene panels |
| title_fullStr | Tumour mutational burden is overestimated by target cancer gene panels |
| title_full_unstemmed | Tumour mutational burden is overestimated by target cancer gene panels |
| title_short | Tumour mutational burden is overestimated by target cancer gene panels |
| title_sort | tumour mutational burden is overestimated by target cancer gene panels |
| topic | Tumour mutational burden Immune checkpoint inhibitor Immune response Biomarker |
| url | http://www.sciencedirect.com/science/article/pii/S2667005422000801 |
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