Intratumoral heterogeneity and clonal evolution in liver cancer

Ahsen, M.E. (Mehmet E.); Akers, N. (Nicholas); Allette, K. (Kimaada); Chen, X. (Xintong); Craig, A.J. (Amanda J.); D?Avola, D. (Delia); Fiel, M.I. (Maria I.); Furtado, G.C. (Glaucia C.); Garcia-Lezana, T. (Teresa); Gunasekaran, G. (Ganesh); Hiotis, S.P. (Spiros P.); Labgaa, I. (Ismail); Lira, S.A. (Sergio A.); Llovet, J.M. (J. M.); Losic, B. (Bojan); Martins-Filho, S.N. (Sebastiao N.); Restrepo, P. (Paula); Schadt, E.E. (Eric E.); Schwartz, M. (Myron); Sebra, R. (Robert); Sia, D. (Daniela); Stolovitzky, G. (Gustavo); Stueck, A. (Ashley); Thung, S. (Swan); Villacorta-Martin, C. (Carlos); Villanueva, A. (Augusto); von-Felden, J. (Johann); Ward, S.C. (Stephen C.)

Abstract

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 evolutio

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Dadun, University of Navarra

oai:dadun.unav.edu:10171/66744

Last time updated on 05/08/2023