Improvement in the Current Therapies for Hepatocellular Carcinoma Using a Systems Medicine Approach
Review article, 2020

Hepatocellular carcinoma (HCC) is one of the leading causes of cancer-related death primarily due to the lack of effective targeted therapies. Despite the distinct morphological and phenotypic patterns of HCC, treatment strategies are restricted to relatively homogeneous therapies, including multitargeted tyrosine kinase inhibitors and immune checkpoint inhibitors. Therefore, more effective therapy options are needed to target dysregulated metabolic and molecular pathways in HCC. Integrative genomic profiling of HCC patients provides insight into the most frequently mutated genes and molecular targets, including telomerase reverse transcriptase, the TP53 gene, and the Wnt/beta-catenin signaling pathway oncogene (CTNNB1). Moreover, emerging techniques, such as genome-scale metabolic models may elucidate the underlying cancer-specific metabolism, which allows for the discovery of potential drug targets and identification of biomarkers. De novo lipogenesis has been revealed as consistently upregulated since it is required for cell proliferation in all HCC patients. The metabolic network-driven stratification of HCC patients in terms of redox responses, utilization of metabolites, and subtype-specific pathways may have clinical implications to drive the development of personalized medicine. In this review, the current and emerging therapeutic targets in light of molecular approaches and metabolic network-based strategies are summarized, prompting effective treatment of HCC patients.

hepatocellular carcinoma

network-driven stratification

genome scale metabolic models

systemic therapies

molecular-targeted therapies


Mehmet Ozcan

Royal Institute of Technology (KTH)

Hacettepe University

Ozlem Altay

Royal Institute of Technology (KTH)

Simon Lam

King's College London

Hasan Turkez

Atatürk University

Yasemin Aksoy

Hacettepe University

Jens B Nielsen

Chalmers, Biology and Biological Engineering, Systems and Synthetic Biology

Mathias Uhlen

Royal Institute of Technology (KTH)

Jan Boren

University of Gothenburg

Adil Mardinoglu

Chalmers, Biology and Biological Engineering, Systems and Synthetic Biology


2366-7478 (eISSN)

Vol. 4 6 2000030

Subject Categories


Medical Genetics

Cancer and Oncology





More information

Latest update