MicroRNAs (miRNAs) are small non-coding RNAs with a length of about 19–25 nt, which can regulate various target genes and are thus involved in the regulation of a variety of biological and pathological processes, including the formation and development of cancer. Drug resistance in cancer chemotherapy is one of the main obstacles to curing this malignant disease. Statistical data indicate that over 90% of the mortality of patients with cancer is related to drug resistance. Drug resistance of cancer chemotherapy can be caused by many mechanisms, such as decreased antitumor drug uptake, modified drug targets, altered cell cycle checkpoints, or increased DNA damage repair, among others. In recent years, many studies have shown that miRNAs are involved in the drug resistance of tumor cells by targeting drug-resistance-related genes or influencing genes related to cell proliferation, cell cycle, and apoptosis. A single miRNA often targets a number of genes, and its regulatory effect is tissue-specific. In this review, we emphasize the miRNAs that are involved in the regulation of drug resistance among different cancers and probe the mechanisms of the deregulated expression of miRNAs. The molecular targets of miRNAs and their underlying signaling pathways are also explored comprehensively. A holistic understanding of the functions of miRNAs in drug resistance will help us develop better strategies to regulate them efficiently and will finally pave the way toward better translation of miRNAs into clinics, developing them into a promising approach in cancer therapy.

Recently, increasing evidence has uncovered the roles of mRNA-miRNA-lncRNA network in multiple human cancers. However, a systematic mRNA-miRNA-lncRNA network linked to pancreatic cancer prognosis is still absent. Differentially expressed genes (DEGs) were first identified by mining GSE16515 and GSE15471 datasets. DAVID database was utilized to conduct functional enrichment analysis. Protein-protein interaction (PPI) network was built using STRING database, and hub genes were identified by Cytoscape plug-in CytoHubba. Upstream miRNAs and lncRNAs of mRNAs were predicted by miRTarBase and miRNet, respectively. Expression, survival and correlation analysis for genes, miRNAs and lncRNAs were performed via GEPIA, Kaplan-Meier plotter and starBase. 734 and 180 upregulated and downregulated significant DEGs were identified, respectively. Functional enrichment analysis revealed that they were significantly enriched in focal adhesion, pathways in cancer and metabolic pathways. According to node degree, hub genes in the PPI networks were screened, such as TGFB1 and ALB. Among the top 20 hub genes, 7 upregulated genes and 2 downregulated hub genes had significant prognostic values in pancreatic cancer. 33 miRNAs were predicted to target the 9 key genes. But only high expression of 8 miRNAs indicated favorable prognosis in pancreatic cancer. Then, 90 lncRNAs were predicted to potentially bind to the 8 miRNAs. SCAMP1, HCP5, MAL2 and LINC00511 were finally identified as key lncRNAs. By combination of results from expression, survival and correlation analysis demonstrated that MMP9/ITGB1-miR-29b-3p-HCP5 competing endogenous RNA (ceRNA) sub-network was linked to prognosis of pancreatic cancer. In a word, we established a novel mRNA-miRNA-lncRNA sub-network, among which each RNA may be utilized as a prognostic biomarker of pancreatic cancer.

Endocrine therapy has become one of most effective forms of targeted adjuvant therapy for hormone-sensitive breast cancer and may be given after surgery or radiotherapy, and also prior, or subsequent to chemotherapy. Current commonly used drugs for adjuvant endocrine therapy can be divided into following three classes: selective estrogen receptor modulators, aromatase inhibitors and selective estrogen receptor downregulators. Tumor cells can develop resistance to endocrine therapy, a major obstacle limiting the success of breast cancer treatment. The complicated crosstalk, both genomic and nongenomic, between estrogen receptors and growth factors was considered to be a crucial factor contributing to endocrine resistance. However, resistance to this therapy is thought to be a progressive, step-wise process, and the underlying mechanism remains unclear. In this review, we summarize the possible biological and molecular mechanisms that underlie endocrine resistance, and discuss some novel strategies to overc...

Drug resistance remains a major problem in the treatment of conventional chemotherapeutic agents in breast cancers. Owing to heterogeneity and complexity of chemoresistance mechanisms, most efforts that focus on a single pathway were unsuccessful, and exploring novel personalized therapeutics becomes urgent. By a system approach, we identified that microRNA-27b-3p (miR-27b), a miRNA deleted in breast cancer tissues and cell lines, has a master role in sensitizing breast cancer cells to a broad spectrum of anticancer drugs in vitro and in vivo. Mechanistic analysis indicated that miR-27b enhanced responses to PTX by directly targeting CBLB and GRB2 to inactivate both PI3K/Akt and MAPK/Erk signaling pathways. Further, miR-27b was identified as a promising molecular biomarker in chemoresistance, clinicopathological features, and prognosis for breast cancer patients. In conclusion, we propose that combinational use of miR-27b and chemotherapeutic agents might be a promising therapeutic strategy to increase long-term drug responses in breast cancers.

MicroRNAs in cancer metastasis and angiogenesis MicroRNAs in cancer metastasis and angiogenesis

Hepatitis B virus (HBV) is one of the major risk factors of hepatocellular carcinoma (HCC). Increasing evidence indicates that microRNA (miRNA)–mRNA axis is involved in HCC. However, a comprehensive miRNA–mRNA regulatory network in HBV-related HCC is still absent. This study aims to identify potential miRNA–mRNA regulatory pathways contributing to pathogenesis of HBV-related HCC. Microarray GSE69580 was downloaded from Gene Expression Omnibus (GEO) database. GEO2R and ‘R-limma’ were used to conduct differential expression analysis. The common miRNAs appeared in the two analytic sets were screened as potential differentially expressed miRNAs (DE-miRNAs). The prognostic roles of screened DE-miRNAs in HCC were further evaluated using Kaplan–Meier plotter database. Target genes of DE-miRNAs were predicted by miRNet. Then, protein–protein interaction (PPI) networks were established for these targets via the STRING database, after which hub genes in the networks were identified by Cytoscape. Functional annotation and pathway enrichment analyses for the target genes were performed through DAVID database. Three enriched pathways related to HBV-related HCC were selected for further analysis and potential target genes commonly appeared in all three pathways were screened. Cytoscape was employed to construct miRNA-hub gene network. The expression and correlation of potential miRNAs and targets were further detected in clinical HBV-related HCC samples by qRT-PCR. 7 upregulated and 9 downregulated DE-miRNAs were accessed. 5 of 7 upregulated DE-miRNAs and 5 of 7 downregulated DE-miRNAs indicated significant prognostic roles in HCC. 2312 and 1175 target genes were predicted for the upregulated and downregulated DE-miRNAs, respectively. TP53 was identified as the hub gene in the PPI networks. Pathway enrichment analysis suggested that these predicted targets were linked to hepatitis B, pathways in cancer, microRNAs in cancer and viral carcinogenesis. Further analysis of these pathways screened 20 and 16 target genes for upregulated and downregulated DE-miRNAs, respectively. By detecting the expression of 36 target genes, six candidate target genes were identified. Finally, a potential miRNA–mRNA regulatory network was established based on the results of qRT-PCR and expression correlation analysis. In the study, potential miRNA–mRNA regulatory pathways were identified, exploring the underlying pathogenesis and effective therapy strategy of HBV-related HCC.