123OMultiplatform analysis of HCC tumours. (24th November 2019)

• Record Type: Journal Article
• Authors: Lee, J-S; Yim, S; Lee, S
• Is Part Of: Annals of oncology. Volume 30(2019)Supplement 9
• Publication Date: 2019-11-24
• Subjects: Oncology -- Periodicals; 616.992
• DOI: 10.1093/annonc/mdz422.001
• Languages: English
• ISSNs: 0923-7534

Abstract

Abstract: Background: Reverse-phase protein array (RPPA) allows us to simultaneously measure multiple protein features, such as expression, modification of proteins, and interaction with ligands from the samples. To overcome current limitation of genomic studies, we generated genomic and proteomic data together from HCC tumors and performed integrated analysis of both data sets. Methods: We generated gene expression profile data and proteomic data from 300 HCC tumors by using expression microarrays and RPPA platform. Supervised and unsupervised approaches were applied to analyze proteomic data and multiple genomic data such as somatic mutations, mRNA expression, miRNA expression, and copy number alterations were integrated with proteomic data to uncover most correlated genomic alterations with functional products. Results: Integrative analysis of genomic and proteomic data uncovered three subtypes of HCC with substantial difference in clinical outcomes. Interestingly, one of HCC subtype has strong mesenchymal characteristics as reflected in low expression of epithelial marker like CDH1 and CTNNB1. When assessed clinical relevance, the overall survival rate of patients in mesenchymal subtype was significantly worse than those in other two subtypes (P = 0.001). For validation of clinical association, we collected additional genomic and proteomic data from independent cohort of patient. Poor clinical outcomes of mesenchymal subtype is validated in multiple independent cohorts (in total of > 500 patients). Gene network analysis with integrated genomic and proteomic data further revealed association of subtypes with currently available treatments of HCC such as sorafenib and immunotherapy. In addition, multiple in-depth analysis of integrated data identified potential therapeutic target candidates for each subtype. Functional validation with cell lines demonstrated that some of candidates are essential for growth and survival of HCC cells. Conclusions: HCC can be classified into distinct subtypes by analyzing integrated genomic and proteomic data. These analyses have identified potential therapeutic targets as well as biomarkers associated with therapeutic targets. Our study demonstrated merit of integrated analysis of proteomic data with genomic data to uncover potential driver genes of HCC development. Legal entity responsible for the study: The authors. Funding: MD Anderson Cancer Center. Disclosure: All authors have declared no conflicts of interest.