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Vemurafenib, a BRAF V600E inhibitor, provides therapeutic benefits for patients with melanoma, but the frequent emergence of drug resistance remains a challenge. An understanding of the mechanisms underlying vemurafenib resistance may generate novel therapeutic strategies for patients with melanoma. Here, we showed that eIF3a, a translational regulatory protein, was an important mediator involved in vemurafenib resistance. eIF3a was expressed at significantly lower levels in vemurafenib-resistant A375 melanoma cells (A375R) than in parental A375 cells. Overexpression of eIF3a enhanced the sensitivity to BRAF inhibitors by reducing p-ERK levels. Furthermore, eIF3a controlled ERK activity by regulating the expression of the phosphatase PPP2R1B via a translation mechanism, thus determining the sensitivity of melanoma cells to vemurafenib. In addition, a positive correlation between eIF3a and PPP2R1B expression was also observed in tumor samples from the Human Protein Atlas and TCGA databases. In conclusion, our studies reveal a previously unknown molecular mechanism of BRAF inhibitor resistance, which may provide a new strategy for predicting vemurafenib responses in clinical treatment.

Background Seizures are a common symptom in glioma patients, and they can cause brain dysfunction. However, the mechanism by which glioma-related epilepsy (GRE) causes alterations in brain networks remains elusive. Objective To investigate the potential pathogenic mechanism of GRE by analyzing the dynamic expression profiles of microRNA/ mRNA/ lncRNA in brain tissues of glioma patients. Methods Brain tissues of 16 patients with GRE and 9 patients with glioma without epilepsy (GNE) were collected. The total RNA was dephosphorylated, labeled, and hybridized to the Agilent Human miRNA Microarray, Release 19.0, 8 × 60 K. The cDNA was labeled and hybridized to the Agilent LncRNA + mRNA Human Gene Expression Microarray V3.0, 4 × 180 K. The raw data was extracted from hybridized images using Agilent Feature Extraction, and quantile normalization was performed using the Agilent GeneSpring. P-value < 0.05 and absolute fold change > 2 were considered the threshold of differential expression data. Data analyses were performed using R and Bioconductor. Results We found that 3 differentially expressed miRNAs (miR-10a-5p, miR-10b-5p, miR-629-3p), 6 differentially expressed lncRNAs (TTN-AS1, LINC00641, SNHG14, LINC00894, SNHG1, OIP5-AS1), and 49 differentially expressed mRNAs play a vitally critical role in developing GRE. The expression of GABARAPL1, GRAMD1B, and IQSEC3 were validated more than twofold higher in the GRE group than in the GNE group in the validation cohort. Pathways including ECM receptor interaction and long-term potentiation (LTP) may contribute to the disease’s progression. Meanwhile, We built a lncRNA-microRNA-Gene regulatory network with structural and functional significance. Conclusion These findings can offer a fresh perspective on GRE-induced brain network changes.