Clinical Impact of Genomic Diversity From Early to Advanced Hepatocellular Carcinoma.

To date, genomic analyses of hepatocellular carcinoma (HCC) have been limited to early stages obtained from liver resection. We aim to describe the genomic profiling of HCC from early to advanced stages. We analyzed 801 HCC from 720 patients (410 resections, 137 transplantations, 122 percutaneous ablations, and 52 noncurative) for 190 gene expressions and for 31 gene mutations. Forty-one advanced HCC and 156 whole exome of Barcelona Clinic Liver Cancer (BCLC) 0/A were analyzed by whole-exome sequencing. Genomic profiling was correlated with tumor stages, clinical features, and survival. Our cohort included patients classified in BCLC stage 0 (9.4%), A (59.5%), B (16.2%), and C (14.9%). Among the overall 801 HCC, the most frequently mutated genes were telomerase reverse transcriptase (TERT) (58.1%), catenin beta 1 (CTNNB1) (30.7%), tumor protein 53 (TP53; 18.7%), AT-rich interaction domain 1A (ARID1A) (13%), albumin (11.4%), apolipoprotein B (APOB) (9.4%), and AXIN1 (9.2%). Advanced-stage HCC (BCLC B/C) showed higher frequencies of splicing factor 3b subunit 1 (SF3B1) (P = 0.0003), TP53 (P = 0.0006), and RB Transcriptional Corepressor 1 mutations (P = 0.03). G1-G6 transcriptomic classification and the molecular prognostic 5-gene score showed different distributions according to the stage of the disease and the type of treatment with an enrichment of G3 (P < 0.0001), poor prognostic score (P < 0.0001), and increased proliferation and dedifferentiation at the transcriptomic level in advanced HCC. The 5-gene score predicted survival in patients treated by resection (P < 0.0001) and ablation (P = 0.01) and in advanced HCC (P = 0.04). Twenty-two percent of advanced HCC harbored potentially druggable genetic alterations, and MET amplification was associated with complete tumor response in patients with advanced HCC treated by a specific MET inhibitor. Conclusion: Genomic analysis across the different stages of HCC revealed the mechanisms of tumor progression and helped to identify biomarkers of response to targeted therapies.