Intratumoral heterogeneity and clonal evolution in liver cancer

Clonal evolution of a tumor ecosystem depends on different selection pressures that are principally immune and treatment mediated. We integrate RNA-seq, DNA sequencing, TCR-seq and SNP array data across multiple regions of liver cancer specimens to map spatio-temporal interactions between cancer and...

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Detalles Bibliográficos
Autores: Losic, Bojan, Craig, Amanda J., Villacorta-Martin, Carlos, Martins-Filho, Sebastiao N., Akers, Nicholas, Chen, Xintong, Ahsen, Mehmet Eren, von Felden, Johann, Labgaa, Ismail, Avola, Delia D', Allette, Kimaada, Lira, Sergio A., Furtado, Glaucia C., Garcia-Lezana, Teresa, Restrepo, Paula, Stueck, Ashley, Ward, Stephen C., Fiel, Maria I., Hiotis, Spiros P., Gunasekaran, Ganesh, Sia, Daniela, Schadt, Eric E., Sebra, Robert, Schwartz, Myron, Llovet i Bayer, Josep Maria, Thung, Swan N., Stolovitzky, Gustavo, Villanueva, Augusto
Tipo de recurso: artículo
Estado:Versión publicada
Fecha de publicación:2020
País:España
Institución:Universidad de Barcelona
Repositorio:Dipòsit Digital de la UB
OAI Identifier:oai:diposit.ub.edu:2445/174195
Acceso en línea:https://hdl.handle.net/2445/174195
Access Level:acceso abierto
Palabra clave:Càncer de fetge
Genètica molecular humana
Liver cancer
Human molecular genetics
Descripción
Sumario:Clonal evolution of a tumor ecosystem depends on different selection pressures that are principally immune and treatment mediated. We integrate RNA-seq, DNA sequencing, TCR-seq and SNP array data across multiple regions of liver cancer specimens to map spatio-temporal interactions between cancer and immune cells. We investigate how these interactions reflect intra-tumor heterogeneity (ITH) by correlating regional neo-epitope and viral antigen burden with the regional adaptive immune response. Regional expression of passenger mutations dominantly recruits adaptive responses as opposed to hepatitis B virus and cancer-testis antigens. We detect different clonal expansion of the adaptive immune system in distant regions of the same tumor. An ITH-based gene signature improves single-biopsy patient survival predictions and an expression survey of 38,553 single cells across 7 regions of 2 patients further reveals heterogeneity in liver cancer. These data quantify transcriptomic ITH and how the different components of the HCC ecosystem interact during cancer evolution.

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