One of the major limitations associated with platinum use is the resistance that almost invariably develops in different tumor types. In the current study, we sought to identify epigenetically regulated microRNAs as novel biomarkers of platinum resistance in lung and ovarian cancers, the ones with highest ratios of associated chemo-resistance.Methods: We combined transcriptomic data from microRNA and mRNA under the influence of an epigenetic reactivation treatment in a panel of four paired cisplatin -sensitive and -resistant cell lines, followed by real-time expression and epigenetic validations for accurate candidate selection in 19 human cancer cell lines. To identify specific candidate genes under miRNA regulation, we assembled “in silico” miRNAs and mRNAs sequences by using ten different algorithms followed by qRT-PCR validation. Functional assays of site-directed mutagenesis and luciferase activity, miRNAs precursor overexpression, silencing by antago-miR and cell viability were performed to confirm their specificity in gene regulation. Results were further explored in 187 primary samples obtained from ovarian tumors and controls.Results: We identified 4 candidates, miR-7, miR-132, miR-335 and miR-148a, which deregulation seems to be a common event in the development of resistance to cisplatin in both tumor types. miR-7 presented specific methylation in resistant cell lines, and was associated with poorer prognosis in ovarian cancer patients. Our experimental results strongly support the direct regulation of MAFG through miR-7 and their involvement in the development of CDDP resistance in human tumor cells.Conclusion: The basal methylation status of miR-7 before treatment may be a potential clinical epigenetic biomarker, predictor of the chemotherapy outcome to CDDP in ovarian cancer patients. To the best of our knowledge, this is the first report linking the regulation of MAFG by miRNA-7 and its role in chemotherapy response to CDDP. Furthermore, this data highlights the possible role of MAFG as a novel therapeutic target for platinum resistant tumors.
Our findings indicate that proliferation could be an important factor in evaluating nodal PTCL outcome and may help to define a more aggressive phenotype.
In recent years, high-throughput next-generation sequencing technology has allowed a rapid increase in diagnostic capacity and precision through different bioinformatics processing algorithms, tools, and pipelines. The identification, annotation, and classification of sequence variants within different target regions are now considered a gold standard in clinical genetic diagnosis. However, this procedure lacks the ability to link regulatory events such as differential splicing to diseases. RNA-seq is necessary in clinical routine in order to interpret and detect among others splicing events and splicing variants, as it would increase the diagnostic rate by up to 10–35%. The transcriptome has a very dynamic nature, varying according to tissue type, cellular conditions, and environmental factors that may affect regulatory events such as splicing and the expression of genes or their isoforms. RNA-seq offers a robust technical analysis of this complexity, but it requires a profound knowledge of computational/statistical tools that may need to be adjusted depending on the disease under study. In this article we will cover RNA-seq analyses best practices applied to clinical routine, bioinformatics procedures, and present challenges of this approach.
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