Abstract Introduction: Liver cancer is the second cause of cancer-related mortality worldwide. Currently, there are only two systemic agents able to increase survival in patients at advanced stages (i.e. sorafenib and regorafenib). Median survival of these patients is still poor, which highlights the need for new therapies. Our aim is to identify key regulatory gene networks with oncogenic properties amenable for therapeutic intervention through 1) integration of gene expression and DNA methylation data from human HCC samples followed by 2) functional validation in mice using shRNA screens. Methods: DNA methylation (Illumina HM450) and mRNA expression (Affymetrix human genome U219) data of 215 human HCC samples (Villanueva, Hepatology 2015) were analyzed to identify key gene regulatory networks. A causality test interrogated the impact of cis and trans regulation of promoter methylation on gene expression (Yoo, PLoS Genet 2015). A key regulator gene was defined when it regulated a substantial number of downstream genes (more than 2 standard deviations from the mean predicted trans-regulated downstream genes). Data analysis includes differential gene expression, topological overlap clustering (hierarchical, non-negative factorization [NMF]), and gene annotation. The tumorigenic potential of candidate tumor suppressors was experimentally validated through a positive selection shRNA (short-hairpin RNA) screen in mice (6 shRNAs/gene, 48 shRNAs/pool, 5 mice/library). Results: We identified 116 potential HCC key regulator genes, predicted to regulate expression of between 1,484 and 3,511 downstream genes for each one. Among the key regulators, 60 were classified as potential tumor maintenance genes and 56 as potential tumor suppressors genes based on differential expression with non-tumoral tissue (FDR<0.05). Hierarchical clustering of downstream genes showed significant overlap among multiple key regulators, suggesting their function in co-regulatory networks. Gene annotation showed a majority of key regulators associated (FDR<0.05) with focal adhesion and matrix reorganization. Three clusters of patients emerged upon NMF clustering of the key regulator’s gene expression, one of which showed (n=69/215, 32% of patients) significant overlap with the previously described CTNNB1 subclass of HCC (Chiang, Cancer Res 2008). In mice, 2/6 shRNA libraries showed significant accelerated tumor growth when compared to control [median time to 400 cc of tumor volume were 29 (library #2) and 30 (library #3) versus 39 days in control, P<0.05], suggesting enrichment of bona fide tumor suppressors. Planned sequencing analysis will confirm the identity of these candidates. Conclusions: We have identified 116 putative key regulators of hepatocarcinogenesis by integrative analysis of gene expression and DNA methylation. Functional validation indicates enrichment of bona fide tumor suppressors. Citation Format: Amanda J. Craig, Seungyeul Yoo, Verónica Miguela, Delia D'Avola, Pedro Molina-Sánchez, Josep Llovet, Amaia Lujambio, Jun Zhu, Augusto Villanueva. Integrative molecular analysis of gene expression and methylation reveals 116 putative key regulator genes of human hepatocarcinogenesis [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2017; 2017 Apr 1-5; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2017;77(13 Suppl):Abstract nr 4393. doi:10.1158/1538-7445.AM2017-4393