Introduction: Sorafenib, an FDA-approved drug for advanced hepatocellular carcinoma (HCC) treatment, encounters resistance in many patients. Deciphering the mechanisms underlying sorafenib resistance is crucial for devising alternative strategies to overcome it.
Aim: This study aimed to investigate sorafenib resistance mechanisms using a diverse panel of HCC cell lines.
Methods: HCC cell lines were subjected to continuous sorafenib treatment, and stable cell lines (Huh 7.5 and Huh 7PX) exhibiting sustained growth in its presence were isolated. The investigation of drug resistance mechanisms involved a comparative analysis of drug-targeted signal transduction pathways (EGFR/RAF/MEK/ERK/Cyclin D), sorafenib uptake, and membrane expression of the drug uptake transporter.
Results: HCC cell lines (Huh 7.5 and Huh 7PX) with a higher IC50 (10μM) displayed a more frequent development of sorafenib resistance compared to those with a lower IC50 (2-4.8μM), indicating a potential impact of IC50 variation on initial treatment response. Our findings reveal that activated overexpression of Raf1 kinases and impaired sorafenib uptake, mediated by reduced membrane expression of organic cation transporter-1 (OCT1), contribute to sorafenib resistance in HCC cultures. Stable expression of the drug transporter OCT1 through cDNA transfection or adenoviral delivery of OCT1 mRNA increased sorafenib uptake and successfully overcame sorafenib resistance. Additionally, consistent with sorafenib resistance in HCC cultures, cirrhotic liver-associated human HCC tumors often exhibited impaired membrane expression of OCT1 and OCT3.
Conclusion: Intrinsic differences among HCC cell clones, affecting sorafenib sensitivity at the expression level of Raf kinases, drug uptake, and OCT1 transporters, were identified. This study underscores the potential of HCC tumor targeted OCT1 expression to enhance sorafenib treatment response.
Purpose: The patterns and risk factors of postsurgical recurrence of patient with hepatocellular carcinoma (HCC) with microvascular invasion (MVI) are not clarified. This study aimed to decipher and compare the postoperative recurrent patterns and the risk factors contributing to recurrence between MVI positive (MVI(+)) and MVI negative (MVI(-)) HCC after hepatectomy.
Patients and methods: Patients with HCC who underwent hepatectomy in three Chinese academic hospitals between January 1, 2009, and December 31, 2018, were enrolled. Recurrent patterns included early (≤2 years) or late (>2 years) recurrence, recurrent sites and number, and risk factors of recurrence were compared between the MVI(+)and MVI(-) groups by propensity score-matching (PSM).
Results: Of 1756 patients included, 581 (33.1%) were MVI(+), and 875 (49.8%) patients developed early recurrence. Compared with the MVI(-) group, the MVI(+) group had a higher 2-year recurrence rate in the PSM cohort (hazard ratio [HR], 1.82; 95% confidence interval [CI], 1.59-2.10; P < 0.001), and more patients with multiple tumor recurrence. Patients with early recurrence in the MVI(+) group had a worse overall survival (OS) than those in the MVI(-) group (HR, 1.24; 95% CI, 1.02-1.50; P = 0.034). Resection margin (RM) ≤1.0 cm is a surgical predictor of early recurrence for the MVI(+) group (HR, 0.68; 95% CI, 0.54-0.87; P = 0.002), but not for the MVI(-) group.
Conclusion: Compared to MVI(-) HCC, MVI(+) HCC tends to be early, multiple recurrence and lung and lymph node metastasis after resection. RM ≤1.0 cm is a surgical risk factor of early recurrence for patient with MVI.
Purpose: Hepatocellular carcinoma is the most common primary liver cancer, with poor prognosis. Complex immune microenvironment of the liver is linked to the development of HCC. PVALB is a calcium-binding protein which has been described as a cancer suppressor gene in thyroid cancer and glioma. Nevertheless, the role of PVALB in HCC is unknown.
Materials and methods: We obtained data from TCGA and GSE54236 datasets. MCP-counter, WGCNA and LASSO model were applied to identify PVALB. With UALCAN, MethSurv, and other websites, we probed the expression, methylation and survival of PVALB. LinkedOmics and GSEA were adopted for functional analysis, while TIMER, TISIDB, Kaplan-Meier plotter, TIDE databases were utilized to evaluate the relevance of PVALB to the tumor immune microenvironment and predict immunotherapy efficacy. TargetScan, DIANA, LncRNASNP2 databases and relevant experiments were employed to construct ceRNA network. Finally, molecular docking and drug sensitivity of PVALB were characterized by GeneMANIA, CTD, and so on.
Results: PVALB was recognized as a gene associated with HCC and NK cell. Its expression was down-regulated in HCC tissue, which lead to adverse prognosis. Besides, the hypomethylation of PVALB was related to its reduced expression. Notably, PVALB was tightly linked to immune, and its reduced expression attenuated the anticancer effect of NK cells via the Fas/FasL pathway, leading to a adverse outcome. The lnc-YY1AP1-3/hsa-miR-6735-5p/PVALB axis may regulate the PVALB expression. Finally, we found immunotherapy might be a viable treatment option.
Conclusion: In a word, PVALB is a prognostic indicator, whose low expression facilitates HCC progression by impacting NK cell infiltration.