Predictive biomarkers for systemic therapy of hepatocellular carcinoma

ABSTRACT

Introduction: Hepatocellular carcinoma (HCC) is the most common primary liver cancer and the third cancer-related cause of death worldwide. In recent years, several systemic therapy drugs including sorafenib, lenvatinib, regorafenib, cabozantinib, ramucicurab, nivilumab, and pembrolizumab have been approved by FDA for advanced HCC. However, their insufficient efficacy, toxicity, and drug resistance require clinically applicable and validated predictive biomarkers.

Areas covered: Our review covers the recent advancements in the identification of proteomic/genomic/epigenomic/transcriptomic biomarkers for predicting HCC treatment efficacy with the use of multi-kinase inhibitors (MKIs), CDK4/6 inhibitors, and immune checkpoint inhibitors (ICIs). Alpha-fetoprotein, des-carboxyprothrombin, vascular endothelial growth factor, angiopoietin-2, and dysregulated MTOR, VEGFR2, c-KIT, RAF1, PDGFRβ have the potential of proteomic/genomic biomarkers for sorafenib treatment. Alanine aminotransferase, aspartate aminotransferase, and albumin-bilirubin grade can predict the efficacy of other MKIs. Rb, p16, and Ki-67, and genes involved in cell cycle regulation, CDK1-4, CCND1, CDKN1A, and CDKN2A have been proposed for CD4/6 inhibitors, while dysregulated TERT, CTNNB1, TP53 FGF19, and TP53 are found to be predictors for ICI efficacy.

Expert opinion: There are still limited clinically applicable and validated predictive biomarkers to identify HCC patients who benefit from systemic therapy. Further prospective biomarker validation studies for HCC personalized systemic therapy are required.

KEYWORDS:

• Hepatocellular carcinoma
• genomics
• proteomics
• transcriptomics
• systemic therapy
• predictive biomarkers

Article Highlights

• High heterogeneity of HCC dictates proteomic, genomic/epigenomic, and transcriptomic profiling to identify individual variabilities in patients’ response to systemic treatment.

• Several proteomic biomarkers such as AFP, VEGF, Ang-2, AST, ALT, and ALBI score have been utilized in phase 2/3 clinical trials as predictors of MKI efficacy and safety.

• Alterations in the expression of actionable genes (VEGFR2, PDGFRβ, MTOR, FGFR1, TERT, CTNNB1, CDK1-4, CCND1, FGF19, OCT4, and TP53) can serve as predictors of HCC patients’ systemic treatment efficacy.

• Ras/Raf/MEK/ERK, PI3K/Akt/mTOR, and Wnt/β-catenin pathways associate with HCC patients’ response to MKIs, ICIs, and CDK4/6 inhibitors

• Regulatory networks of non-coding RNAs such as FOXD2-AS1/miR-150-5p/TMEM9, MALAT1/miR-140-5p/AURKA, and KCNQ1OT1/miR-506/CD274, etc. have been implicated in sorafenib-treated HCC patients’ outcome.

Declaration of interest

The authors have no relevant affiliations or financial involvement with any organization or entity with a financial interest in or financial conflict with the subject matter or materials discussed in the manuscript. This includes employment, consultancies, honoraria, stock ownership or options, expert testimony, grants or patents received or pending, or royalties.

Additional information

Funding

This work was supported by I.M. Sechenov First Moscow State Medical University Strategic Development Program under the Russian Academic Excellence Project 5-100