Sorafenib is an oral multikinase inhibitor that suppresses tumor cell proliferation and angiogenesis and promotes tumor cell apoptosis. It was approved by the FDA for the treatment of advanced renal cell carcinoma in 2006, and as a unique target drug for advanced hepatocellular carcinoma (HCC) in 2007. Sorafenib can significantly extend the median survival time of patients but only by 3–5 months. Moreover, it is associated with serious adverse side effects, and drug resistance often develops. Therefore, it is of great importance to explore the mechanisms underlying sorafenib resistance and to develop individualized therapeutic strategies for coping with these problems. Recent studies have revealed that in addition to the primary resistance, several mechanisms are underlying the acquired resistance to sorafenib, such as crosstalk involving PI3K/Akt and JAK-STAT pathways, the activation of hypoxia-inducible pathways, and epithelial-mesenchymal transition. Here, we briefly describe the function of sorafenib, its clinical application, and the molecular mechanisms for drug resistance, especially for HCC patients.

Spatial transcriptome technique was applied to decipher the spatial architecture and TME characteristics of liver cancers.

Hepatocellular carcinoma (HCC) is highly heterogeneous in nature and has been one of the most common cancer types worldwide. To ensure repeatability of identified gene expression patterns and comprehensively annotate the transcriptomes of HCC, we carefully curated 15 public HCC expression datasets that cover around 4000 clinical samples and developed the database HCCDB to serve as a one-stop online resource for exploring HCC gene expression with user-friendly interfaces. The global differential gene expression landscape of HCC was established by analyzing the consistently differentially expressed genes across multiple datasets. Moreover, a 4D metric was proposed to fully characterize the expression pattern of each gene by integrating data from The Cancer Genome Atlas (TCGA) and Genotype-Tissue Expression (GTEx). To facilitate a comprehensive understanding of gene expression patterns in HCC, HCCDB also provides links to third-party databases on drug, proteomics, and literatures, and graphically displays the results from computational analyses, including differential expression analysis, tissue-specific and tumor-specific expression analysis, survival analysis, and co-expression analysis. HCCDB is freely accessible at http://lifeome.net/database/hccdb.

Objective: The lack of highly sensitive and specific diagnostic biomarkers is a major contributor to the poor outcomes of patients with hepatocellular carcinoma (HCC). We sought to develop a non-invasive diagnostic approach using circulating cell-free DNA (cfDNA) for the early detection of HCC. Design: Applying the 5hmC-Seal technique, we obtained genome-wide 5-hydroxymethylcytosines (5hmC) in cfDNA samples from 2554 Chinese subjects: 1204 patients with HCC, 392 patients with chronic hepatitis B virus infection (CHB) or liver cirrhosis (LC) and 958 healthy individuals and patients with benign liver lesions. A diagnostic model for early HCC was developed through case-control analyses using the elastic net regularisation for feature selection. Results: The 5hmC-Seal data from patients with HCC showed a genome-wide distribution enriched with liver-derived enhancer marks. We developed a 32-gene diagnostic model that accurately distinguished early HCC (stage 0/A) based on the Barcelona Clinic Liver Cancer staging system from non-HCC (validation set: area under curve (AUC)=88.4%; (95% CI 85.8% to 91.1%)), showing superior performance over α-fetoprotein (AFP). Besides detecting patients with early stage or small tumours (eg, ≤2.0 cm) from non-HCC, the 5hmC model showed high capacity for distinguishing early HCC from high risk subjects with CHB or LC history (validation set: AUC=84.6%; (95% CI 80.6% to 88.7%)), also significantly outperforming AFP. Furthermore, the 5hmC diagnostic model appeared to be independent from potential confounders (eg, smoking/alcohol intake history). Conclusion: We have developed and validated a non-invasive approach with clinical application potential for the early detection of HCC that are still surgically resectable in high risk individuals.

Lenvatinib, a multi-target tyrosine kinase inhibitor (TKI), is an emerging first-line therapy for hepatocellular carcinoma (HCC). Its application has changed the status of sorafenib as the only first-line TKI treatment for HCC for more than a decade. Evidence has shown that lenvatinib possesses antitumor proliferation and immunomodulatory activity in preclinical studies. In comparison, lenvatinib was non-inferior to sorafenib in overall survival (OS), and even shows superiority with regard to all the secondary efficacy endpoints. Immune-checkpoint inhibitors(ICIs)are now being incorporated into HCC treatment. Positive outcomes have been achieved in the combination of lenvatinib plus ICIs, bringing broader prospects for HCC. This review presents an overview on the therapeutic mechanisms and clinical efficacy of lenvatinib in HCC, and we discuss the future perspectives of lenvatinib in HCC management with focus on biomarker-guided precision medicine.

Circular RNA (circRNA) possesses great pre-clinical diagnostic and therapeutic potentials in multiple cancers. It has been reported playing roles in multiple malignant behaviors including proliferation, migration, metastasis and chemoresistance. However, the underlying correlation between circRNAs and cancer stem cells (CSCs) has not been reported yet.