Decoding mutational signatures in breast cancer: Insights from a multi-cohort study
Purpose: Diagnosis and treatment decisions of hormonal breast cancers (BC) are now guided by genomic mutations determination, combined into mutational signatures, and provide insight into the patients’ genomic landscape. This work aims to compare genomic data and signatures extracted from tissue sam...
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| Format: | Article |
| Language: | English |
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Elsevier
2025-03-01
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| Series: | Translational Oncology |
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| Online Access: | http://www.sciencedirect.com/science/article/pii/S1936523325000464 |
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| author | Margaux Betz Andréa Witz Julie Dardare Cassandra Michel Vincent Massard Romain Boidot Pauline Gilson Jean-Louis Merlin Alexandre Harlé |
| author_facet | Margaux Betz Andréa Witz Julie Dardare Cassandra Michel Vincent Massard Romain Boidot Pauline Gilson Jean-Louis Merlin Alexandre Harlé |
| author_sort | Margaux Betz |
| collection | DOAJ |
| description | Purpose: Diagnosis and treatment decisions of hormonal breast cancers (BC) are now guided by genomic mutations determination, combined into mutational signatures, and provide insight into the patients’ genomic landscape. This work aims to compare genomic data and signatures extracted from tissue samples collected in the CICLADES study to existing cohorts. Ultimately, the goal is to prove the accuracy of smaller cohorts and provide new relevant data. Materials and methods: DNA from patients of the CICLADES cohort was extracted, sequenced, and custom filtering was applied to the resulting files. Genomic data was pulled from 6 BC cohorts available on cBioPortal.com. In total, 2303 samples were analyzed. Mutational signatures were extracted and matched to known signatures of the Catalogue of Somatic Mutations in Cancer (COSMIC). Tumor Mutation Burden (TMB) and hypermutation were estimated and compared between samples. Results: PIK3CA and TP53 represented the two genes highly mutated across all cohorts. TMB was similar between the CICLADES and CBSM groups, however the MSKCC population showed a significantly higher TMB than both. Nine signatures were extracted, with recurring Single Base Substitutions (SBS) signatures like SBS1, SBS2 and SBS5. The presence of APOBEC-specific signatures was concordant with cohorts presenting APOBEC enrichment. The mean number of mutations was significantly higher in enriched samples for each analyzed cohort. Conclusion: The use of comprehensive genomic profiling provided accurate evaluation of the TMB and extraction of signatures consistent with published literature. The genomic analysis of the tissue samples of the CICLADES cohort brings new and relevant data, comparable to results found in bigger cohorts. |
| format | Article |
| id | doaj-art-6368a0c471ed4e7ea71fd0027e6c064b |
| institution | Kabale University |
| issn | 1936-5233 |
| language | English |
| publishDate | 2025-03-01 |
| publisher | Elsevier |
| record_format | Article |
| series | Translational Oncology |
| spelling | doaj-art-6368a0c471ed4e7ea71fd0027e6c064b2025-02-06T05:11:29ZengElsevierTranslational Oncology1936-52332025-03-0153102315Decoding mutational signatures in breast cancer: Insights from a multi-cohort studyMargaux Betz0Andréa Witz1Julie Dardare2Cassandra Michel3Vincent Massard4Romain Boidot5Pauline Gilson6Jean-Louis Merlin7Alexandre Harlé8Service de Biopathologie, Institut de Cancérologie de Lorraine, Université de Lorraine, CNRS UMR 7039 CRAN, 54519 Vandœuvre-lès-Nancy, France; Corresponding author.Service de Biopathologie, Institut de Cancérologie de Lorraine, Université de Lorraine, CNRS UMR 7039 CRAN, 54519 Vandœuvre-lès-Nancy, FranceService de Biopathologie, Institut de Cancérologie de Lorraine, 54519 Vandœuvre-lès-Nancy, FranceService de Biopathologie, Institut de Cancérologie de Lorraine, Université de Lorraine, CNRS UMR 7039 CRAN, 54519 Vandœuvre-lès-Nancy, FranceDépartement d'Oncologie Médicale, Institut de cancérologie de Lorraine, 54519 Vandoeuvre-lès-Nancy, FranceResearch Platform in Biological Oncology, Center GF Leclerc, Dijon, FranceService de Biopathologie, Institut de Cancérologie de Lorraine, Université de Lorraine, CNRS UMR 7039 CRAN, 54519 Vandœuvre-lès-Nancy, FranceService de Biopathologie, Institut de Cancérologie de Lorraine, Université de Lorraine, CNRS UMR 7039 CRAN, 54519 Vandœuvre-lès-Nancy, FranceService de Biopathologie, Institut de Cancérologie de Lorraine, Université de Lorraine, CNRS UMR 7039 CRAN, 54519 Vandœuvre-lès-Nancy, FrancePurpose: Diagnosis and treatment decisions of hormonal breast cancers (BC) are now guided by genomic mutations determination, combined into mutational signatures, and provide insight into the patients’ genomic landscape. This work aims to compare genomic data and signatures extracted from tissue samples collected in the CICLADES study to existing cohorts. Ultimately, the goal is to prove the accuracy of smaller cohorts and provide new relevant data. Materials and methods: DNA from patients of the CICLADES cohort was extracted, sequenced, and custom filtering was applied to the resulting files. Genomic data was pulled from 6 BC cohorts available on cBioPortal.com. In total, 2303 samples were analyzed. Mutational signatures were extracted and matched to known signatures of the Catalogue of Somatic Mutations in Cancer (COSMIC). Tumor Mutation Burden (TMB) and hypermutation were estimated and compared between samples. Results: PIK3CA and TP53 represented the two genes highly mutated across all cohorts. TMB was similar between the CICLADES and CBSM groups, however the MSKCC population showed a significantly higher TMB than both. Nine signatures were extracted, with recurring Single Base Substitutions (SBS) signatures like SBS1, SBS2 and SBS5. The presence of APOBEC-specific signatures was concordant with cohorts presenting APOBEC enrichment. The mean number of mutations was significantly higher in enriched samples for each analyzed cohort. Conclusion: The use of comprehensive genomic profiling provided accurate evaluation of the TMB and extraction of signatures consistent with published literature. The genomic analysis of the tissue samples of the CICLADES cohort brings new and relevant data, comparable to results found in bigger cohorts.http://www.sciencedirect.com/science/article/pii/S1936523325000464Mutational signatureBreast cancerNext generation sequencingGenomic database |
| spellingShingle | Margaux Betz Andréa Witz Julie Dardare Cassandra Michel Vincent Massard Romain Boidot Pauline Gilson Jean-Louis Merlin Alexandre Harlé Decoding mutational signatures in breast cancer: Insights from a multi-cohort study Translational Oncology Mutational signature Breast cancer Next generation sequencing Genomic database |
| title | Decoding mutational signatures in breast cancer: Insights from a multi-cohort study |
| title_full | Decoding mutational signatures in breast cancer: Insights from a multi-cohort study |
| title_fullStr | Decoding mutational signatures in breast cancer: Insights from a multi-cohort study |
| title_full_unstemmed | Decoding mutational signatures in breast cancer: Insights from a multi-cohort study |
| title_short | Decoding mutational signatures in breast cancer: Insights from a multi-cohort study |
| title_sort | decoding mutational signatures in breast cancer insights from a multi cohort study |
| topic | Mutational signature Breast cancer Next generation sequencing Genomic database |
| url | http://www.sciencedirect.com/science/article/pii/S1936523325000464 |
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