TMBcalc: a computational pipeline for identifying pan-cancer Tumor Mutational Burden gene signatures
Background:In the precision medicine era, identifying predictive factors to select patients most likely to benefit from treatment with immunological agents is a crucial and open challenge in oncology.Methods:This paper presents a pan-cancer analysis of Tumor Mutational Burden (TMB). We developed a n...
| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
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Frontiers Media S.A.
2024-04-01
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| Series: | Frontiers in Genetics |
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| Online Access: | https://www.frontiersin.org/articles/10.3389/fgene.2024.1285305/full |
| _version_ | 1827292785146855424 |
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| author | Grete Francesca Privitera Salvatore Alaimo Anna Caruso Alfredo Ferro Stefano Forte Alfredo Pulvirenti |
| author_facet | Grete Francesca Privitera Salvatore Alaimo Anna Caruso Alfredo Ferro Stefano Forte Alfredo Pulvirenti |
| author_sort | Grete Francesca Privitera |
| collection | DOAJ |
| description | Background:In the precision medicine era, identifying predictive factors to select patients most likely to benefit from treatment with immunological agents is a crucial and open challenge in oncology.Methods:This paper presents a pan-cancer analysis of Tumor Mutational Burden (TMB). We developed a novel computational pipeline, TMBcalc, to calculate the TMB. Our methodology can identify small and reliable gene signatures to estimate TMB from custom targeted-sequencing panels. For this purpose, our pipeline has been trained on top of 17 cancer types data obtained from TCGA.Results:Our results show that TMB, computed through the identified signature, strongly correlates with TMB obtained from whole-exome sequencing (WES).Conclusion:We have rigorously analyzed the effectiveness of our methodology on top of several independent datasets. In particular we conducted a comprehensive testing on: (i) 126 samples sourced from the TCGA database; few independent whole-exome sequencing (WES) datasets linked to colon, breast, and liver cancers, all acquired from the EGA and the ICGC Data Portal. This rigorous evaluation clearly highlights the robustness and practicality of our approach, positioning it as a promising avenue for driving substantial progress within the realm of clinical practice. |
| first_indexed | 2024-04-24T13:11:44Z |
| format | Article |
| id | doaj.art-6c66c76d46664a4a9817ec92c3d87ff3 |
| institution | Directory Open Access Journal |
| issn | 1664-8021 |
| language | English |
| last_indexed | 2024-04-24T13:11:44Z |
| publishDate | 2024-04-01 |
| publisher | Frontiers Media S.A. |
| record_format | Article |
| series | Frontiers in Genetics |
| spelling | doaj.art-6c66c76d46664a4a9817ec92c3d87ff32024-04-05T04:18:59ZengFrontiers Media S.A.Frontiers in Genetics1664-80212024-04-011510.3389/fgene.2024.12853051285305TMBcalc: a computational pipeline for identifying pan-cancer Tumor Mutational Burden gene signaturesGrete Francesca Privitera0Salvatore Alaimo1Anna Caruso2Alfredo Ferro3Stefano Forte4Alfredo Pulvirenti5Department of Clinical and Experimental Medicine, Bioinformatics Unit, University of Catania, Catania, ItalyDepartment of Clinical and Experimental Medicine, Bioinformatics Unit, University of Catania, Catania, ItalyDepartment of Physics and Astronomy, University of Catania, Catania, ItalyDepartment of Clinical and Experimental Medicine, Bioinformatics Unit, University of Catania, Catania, ItalyIstituto Oncologico del Mediterraneo (IOM) Ricerca, Viagrande, ItalyDepartment of Clinical and Experimental Medicine, Bioinformatics Unit, University of Catania, Catania, ItalyBackground:In the precision medicine era, identifying predictive factors to select patients most likely to benefit from treatment with immunological agents is a crucial and open challenge in oncology.Methods:This paper presents a pan-cancer analysis of Tumor Mutational Burden (TMB). We developed a novel computational pipeline, TMBcalc, to calculate the TMB. Our methodology can identify small and reliable gene signatures to estimate TMB from custom targeted-sequencing panels. For this purpose, our pipeline has been trained on top of 17 cancer types data obtained from TCGA.Results:Our results show that TMB, computed through the identified signature, strongly correlates with TMB obtained from whole-exome sequencing (WES).Conclusion:We have rigorously analyzed the effectiveness of our methodology on top of several independent datasets. In particular we conducted a comprehensive testing on: (i) 126 samples sourced from the TCGA database; few independent whole-exome sequencing (WES) datasets linked to colon, breast, and liver cancers, all acquired from the EGA and the ICGC Data Portal. This rigorous evaluation clearly highlights the robustness and practicality of our approach, positioning it as a promising avenue for driving substantial progress within the realm of clinical practice.https://www.frontiersin.org/articles/10.3389/fgene.2024.1285305/fullpersonalized medicineTumor Mutational BurdenDNA-seqanalysis pipelinepan-cancer |
| spellingShingle | Grete Francesca Privitera Salvatore Alaimo Anna Caruso Alfredo Ferro Stefano Forte Alfredo Pulvirenti TMBcalc: a computational pipeline for identifying pan-cancer Tumor Mutational Burden gene signatures Frontiers in Genetics personalized medicine Tumor Mutational Burden DNA-seq analysis pipeline pan-cancer |
| title | TMBcalc: a computational pipeline for identifying pan-cancer Tumor Mutational Burden gene signatures |
| title_full | TMBcalc: a computational pipeline for identifying pan-cancer Tumor Mutational Burden gene signatures |
| title_fullStr | TMBcalc: a computational pipeline for identifying pan-cancer Tumor Mutational Burden gene signatures |
| title_full_unstemmed | TMBcalc: a computational pipeline for identifying pan-cancer Tumor Mutational Burden gene signatures |
| title_short | TMBcalc: a computational pipeline for identifying pan-cancer Tumor Mutational Burden gene signatures |
| title_sort | tmbcalc a computational pipeline for identifying pan cancer tumor mutational burden gene signatures |
| topic | personalized medicine Tumor Mutational Burden DNA-seq analysis pipeline pan-cancer |
| url | https://www.frontiersin.org/articles/10.3389/fgene.2024.1285305/full |
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