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, TCRseq and SNP array data across multiple regions of liver cancer specimens to map spatio-temporal interactions between cancer and...

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Detalhes bibliográficos
Autores: Losic, B. (Bojan)|||/items/b94c4371-0c63-4d02-9baf-f537faf75dbf, Craig, A.J. (Amanda J.)|||/items/69831b32-a839-454b-8999-2298534ac823, Villacorta-Martin, C. (Carlos)|||/items/a853eab1-25e6-410f-b52b-dc1f42ab325a, Martins-Filho, S.N. (Sebastiao N.)|||/items/2bfc614a-52b7-487e-9755-6cd3c531c6e5, Akers, N. (Nicholas)|||/items/74687ba5-42fd-4217-aeaa-62084ab348ac, Chen, X. (Xintong)|||/items/0339226f-96c8-4408-91c0-a11b615873d4, Ahsen, M.E. (Mehmet E.)|||/items/1589fea0-fe22-434e-8229-f6cae93cd3c0, von-Felden, J. (Johann)|||/items/7f0993d2-31c8-4e4a-9e1d-d1348e64d9f0, Labgaa, I. (Ismail)|||/items/020300b4-742b-400a-a507-61e672fcc449, Allette, K. (Kimaada)|||/items/4cbae057-9d22-4d2b-b51d-39195c2a2bd0, Lira, S.A. (Sergio A.)|||/items/37fc26e9-8bd5-4b7f-9a56-eb56fd96a369, Furtado, G.C. (Glaucia C.)|||/items/3fdd2bb2-3868-4d1f-9090-59d08e17fc4b, Garcia-Lezana, T. (Teresa)|||/items/8f85a9cb-97a3-4298-8815-94381ca58c30, Restrepo, P. (Paula)|||/items/efe5bc94-15e5-43c6-b8e2-8ddee7b04b7e, Stueck, A. (Ashley)|||/items/bf060f94-691c-48cc-9db2-48ed257b3bab, Ward, S.C. (Stephen C.)|||/items/ac60296c-8d3b-4d13-84d4-b1cd9b2c1fd5, Fiel, M.I. (Maria I.)|||/items/2d5f8655-2532-45d8-bbe7-ca02107bbe3c, Hiotis, S.P. (Spiros P.)|||/items/e4d6fbfd-efc3-486f-8848-1aec965487a4, Gunasekaran, G. (Ganesh)|||/items/eb331a52-06eb-4250-81d5-b4a14b7bf60e, Sia, D. (Daniela)|||/items/1f64f911-29db-4561-954e-a8b87a745b6a, Schadt, E.E. (Eric E.)|||/items/00154b5c-27b8-41f6-92cd-de55efc1ac0a, Sebra, R. (Robert)|||/items/9351cf61-5fcc-472d-ad75-658828444539, Schwartz, M. (Myron)|||/items/0b58aa36-8b76-4633-85d0-721dbe9dd0ec, Llovet, J.M. (J. M.)|||/items/37dac41c-f0a9-401b-915f-00b6b5320f5e, Thung, S. (Swan)|||/items/b363cc67-1806-4739-b7e9-7c7b4a28ae49, Stolovitzky, G. (Gustavo)|||/items/5bef8319-aa2a-4d85-bb71-d60928d19073, Villanueva, A. (Augusto)|||/items/4c594307-781b-4229-a766-f4a45bde938f, D'Avola, D. (Delia)|||/items/c2bf1118-f768-493d-955c-d1ea525ed956
Formato: artículo
Fecha de publicación:2020
País:España
Recursos:Universidad de Navarra
Repositorio:Dadun. Depósito Académico Digital de la Universidad de Navarra
Idioma:inglés
OAI Identifier:oai:dadun.unav.edu:10171/66744
Acesso em linha:https://hdl.handle.net/10171/66744
Access Level:acceso abierto
Palavra-chave:Hepatología
Descrição
Resumo:Clonal evolution of a tumor ecosystem depends on different selection pressures that are principally immune and treatment mediated. We integrate RNA-seq, DNA sequencing, TCRseq 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 singlebiopsy 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