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Mutational signatures reveal the dynamic interplay of risk factors and cellular processes during liver tumorigenesis.

ABSTRACT: Genomic alterations driving tumorigenesis result from the interaction of environmental exposures and endogenous cellular processes. With a diversity of risk factors, liver cancer is an ideal model to study these interactions. Here, we analyze the whole genomes of 44 new and 264 published liver cancers and we identify 10 mutational and 6 structural rearrangement signatures showing distinct relationships with environmental exposures, replication, transcription, and driver genes. The liver cancer-specific signature 16, associated with alcohol, displays a unique feature of transcription-coupled damage and is the main source of CTNNB1 mutations. Flood of insertions/deletions (indels) are identified in very highly expressed hepato-specific genes, likely resulting from replication-transcription collisions. Reconstruction of sub-clonal architecture reveals mutational signature evolution during tumor development exemplified by the vanishing of aflatoxin B1 signature in African migrants. Finally, chromosome duplications occur late and may represent rate-limiting events in tumorigenesis. These findings shed new light on the natural history of liver cancers.

SUBMITTER: Letouze E

PROVIDER: S-EPMC5670220 | biostudies-literature | 2017 Nov

REPOSITORIES: biostudies-literature

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Mutational signatures reveal the dynamic interplay of risk factors and cellular processes during liver tumorigenesis.

Letouzé Eric E Shinde Jayendra J Renault Victor V Couchy Gabrielle G Blanc Jean-Frédéric JF Tubacher Emmanuel E Bayard Quentin Q Bacq Delphine D Meyer Vincent V Semhoun Jérémy J Bioulac-Sage Paulette P Prévôt Sophie S Azoulay Daniel D Paradis Valérie V Imbeaud Sandrine S Deleuze Jean-François JF Zucman-Rossi Jessica J

Nature communications 20171103 1

Genomic alterations driving tumorigenesis result from the interaction of environmental exposures and endogenous cellular processes. With a diversity of risk factors, liver cancer is an ideal model to study these interactions. Here, we analyze the whole genomes of 44 new and 264 published liver cancers and we identify 10 mutational and 6 structural rearrangement signatures showing distinct relationships with environmental exposures, replication, transcription, and driver genes. The liver cancer-s ...[more]

PMID: 29101368

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Project description:BackgroundWhile recent studies have separately explored mutational signatures and the tumor microenvironment (TME), there is limited research on the associations of both factors in a pan-cancer context.Materials and methodsWe performed a pan-cancer analysis of over 8,000 tumor samples from The Cancer Genome Atlas (TCGA) project. Machine learning methods were employed to systematically explore the relationship between mutational signatures and TME and develop a risk score based on TME-associated mutational signatures to predict patient survival outcomes. We also constructed an interaction model to explore how mutational signatures and TME interact and influence cancer prognosis.ResultsOur analysis revealed a varied association between mutational signatures and TME, with the Clock-like signature showing the most widespread influence. Risk scores based on mutational signatures mainly induced by Clock-like and AID/APOBEC activity exhibited strong pan-cancer survival stratification ability. We also propose a novel approach to predict transcriptome decomposed infiltration levels using genome-derived mutational signatures as an alternative approach for exploring TME cell types when transcriptome data are unavailable. Our comprehensive analysis revealed that certain mutational signatures and their interaction with immune cells significantly impact clinical outcomes in particular cancer types. For instance, T cell infiltration levels only served as a prognostic biomarker in melanoma patients with high ultraviolet radiation exposure, breast cancer patients with high homologous recombination deficiency signature, and lung adenocarcinoma patients with high tobacco-associated mutational signature.ConclusionOur study comprehensively explains the complex interplay between mutational signatures and immune infiltration in cancer. The results highlight the importance of considering both mutational signatures and immune phenotypes in cancer research and their significant implications for developing personalized cancer treatments and more effective immunotherapy.

Dataset Information

Mutational signatures reveal the dynamic interplay of risk factors and cellular processes during liver tumorigenesis.

Publications

Mutational signatures reveal the dynamic interplay of risk factors and cellular processes during liver tumorigenesis.

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