Integrated multi-omics data analysis identifying novel drug sensitivity-associated molecular targets of hepatocellular carcinoma cells

Abstract

Hepatocellular carcinoma (HCC) is the most common type of liver cancer and the third-leading cause of malignancy-associated mortality worldwide. HCC cells are highly resistant to chemotherapeutic agents. Therefore, there are currently only two US Food and Drug Administration-approved drugs available for the treatment of HCC. The objective of the present study was to analyze the results of previously published high-throughput drug screening, and in vitro genomic and transcriptomic data from HCC cell lines, and to integrate the obtained results to define the underlying molecular mechanisms of drug sensitivity and resistance in HCC cells. The results of treatment with 225 different small molecules on 14 different HCC cell lines were retrieved from the Genomics of Drug Sensitivity in Cancer database and analyzed. Cluster analysis using the treatment results determined that HCC cell lines consist of two groups, according to their drug response profiles. Continued analyses of these two groups with Gene Set Enrichment Analysis method revealed 6 treatment-sensitive molecular targets (epidermal growth factor receptor, mechanistic target of rapamycin, deoxyribonucleic acid-dependent protein kinase, the Aurora kinases, Bruton's tyrosine kinase and phosphoinositide 3-kinase; all P<0.05) and partially effective drugs. Genetic and genome-wide gene expression data analyses of the determined targets and their known biological partners revealed 2 somatically mutated and 13 differentially expressed genes, which differed between drug-resistant and drug-sensitive HCC cells. Integration of the obtained data into a short molecular pathway revealed a drug treatment-sensitive signaling axis in HCC cells. In conclusion, the results of the present study provide novel drug sensitivity-associated molecular targets for the development of novel personalized and targeted molecular therapies against HCC.

Keywords: bioinformatics analysis; drug sensitivity; drug target; liver cancer; targeted therapy.

Figure 1.

Results of cluster analysis for 225 drug treatments in 14 HCC cell lines. A heatmap was generated using drug treatment Z-score values of HCC cell lines. Unsupervised clustering of small molecules and samples resulted in two main sample clusters, Group A and Group B. Each group comprises 7 cell lines. Red, resistant; green, sensitive; grey, missing value; HCC, hepatocellular carcinoma.

Figure 2.

Integrated molecular pathway of small molecule sensitivity in Group A HCC cell lines. Effective drugs (in blue color), enriched drug targets (Table III), target-associated somatically mutant genes (Table IV) and differentially expressed genes (Table V) in HCC cell lines were integrated into one pathway and visualized. Gene expression levels are depicted in a color gradient between −5 (downregulated, color) and +5 (upregulated, red) by the software, as indicated by the color bar. Gene Symbols were retrieved from Human Genome Organisation Gene Nomenclature Committee (71) using the software. PIP3, phosphatidylinositol (3,4,5)-trisphosphate; PIP2, phosphatidylinositol (4,5)-bisphosphate; IP3, inositol trisphosphate; DAG, diacylglycerol; cAMP, cyclic adenosine monophosphate; ER, endoplasmic reticulum; HCC, hepatocellular carcinoma.