Abstract PR04: Understanding tumor clonal evolution by single-cell transcriptomic analysis in liver cancer
Authors: Ma Lichun , Wang Limin , Chang Ching-Wen , Franck Sophia , Dominguez Dana , Forgues Marshonna , Candia Julian , Hernandez Maria O. , Kelly Michael , Zhao Yongmei , Tran Bao , Hernandez Jonathan M. , Davis Jeremy L. , Kleiner David E. , Wood Bradford J. , Greten Tim F. , Wang Xin Wei 
Published: December 2020

Tumor evolution is a key feature intrinsic to tumor biology and contributes to intratumor heterogeneity, escape of immune surveillance, treatment failure, and patients’ prognosis. The evolutionary process of tumor is driven by selecting favorable phenotypes in terms of their fitness and survival in a tumor ecosystem. While genomic alterations provide rich materials for tumor evolution, only a few can induce a recognizable phenotypic change with even fewer for a fitness advantage. Thus, transcriptomics, a major molecular feature reflecting functional activities, will be informative in modeling tumor heterogeneity and crucial in understanding tumor evolution. Here, we aim to study tumor clonal evolution by single-cell transcriptomic profiling of hepatocellular carcinoma and intrahepatic cholangiocarcinoma from 37 patients participating the immune checkpoint inhibition trials. By analyzing core biopsies before or after treatment, we determined the single-cell atlas of liver tumors and confidently separated malignant cells and non-malignant cells by inferring chromosomal copy number variations. We developed a consensus clustering model based on machine learning algorithms and statistical methods to identify functional clones from malignant cells within each tumor. We further determined the clonal relationship by constructing the phylogenetic tree of the clones from all tumors. The clonal relationship within each tumor was independently assessed by manifold based single-cell trajectory and RNA-velocity based cell lineage. The analyses revealed a tumor branching evolutionary architecture of the clones. Noticeably, tumor branching evolution was associated with patient outcomes, which was also validated by using bulk transcriptomic data from 765 liver tumors. We found tumors in the poor prognosis branch were enriched in the pathways of hypoxia, epithelial-mesenchymal transition and angiogenesis. Remarkably, the functional role of the clones within a tumor varied, indicating a cooperative tumor cell community. We found a polarization of immune landscape associated with tumor branching evolution driven by tumor cell-specific cytokines. Our results offer insight into the collective behavior of tumor cell communities in liver cancer as well as potential drivers for tumor evolution in response to immunotherapy.

Citation Format: Lichun Ma, Limin Wang, Ching-Wen Chang, Sophia Franck, Dana Dominguez, Marshonna Forgues, Julian Candia, Maria O. Hernandez, Michael Kelly, Yongmei Zhao, Bao Tran, Jonathan M. Hernandez, Jeremy L. Davis, David E. Kleiner, Bradford J. Wood, Tim F. Greten, Xin Wei Wang. Understanding tumor clonal evolution by single-cell transcriptomic analysis in liver cancer [abstract]. In: Proceedings of the AACR Virtual Special Conference on Tumor Heterogeneity: From Single Cells to Clinical Impact; 2020 Sep 17-18. Philadelphia (PA): AACR; Cancer Res 2020;80(21 Suppl):Abstract nr PR04.