Metabolic pathways of potential miRNA biomarkers derived from liquid biopsy in epithelial ovarian cancer.

Epithelial ovarian cancer (EOC) is the type of OC with the highest mortality rate. Due to the asymptomatic nature of the disease and few available diagnostic tests, it is mostly diagnosed at the advanced stage. Therefore, the present study aimed to discover predictive and/or early diagnostic novel circulating microRNAs (miRNAs or miRs) for EOC. Firstly, microarray analysis of miRNA expression levels was performed on 32 samples of female individuals: Eight plasma samples from patients with pathologically confirmed EOC (mean age, 45 (30-54) years), eight plasma samples from matched healthy individuals (HIs) (mean age, 44 (30-65) years), eight EOC tissue samples (mean age, 45 (30-54) years) and eight benign ovarian (mean age, 35 (17-70) years) neoplastic tissue samples A total of 31 significantly dysregulated miRNAs in serum and three miRNAs in tissue were identified by microarray. The results were validated using reverse transcription-quantitative PCR on samples from 10 patients with pathologically confirmed EOC (mean age, 47(30-54) years), 10 matched His (mean age, 40(26-65) years], 10 EOC tissue samples (mean age, 47(30-54) years) and 10 benign ovarian neoplastic tissue samples (mean age, 40(17-70) years). The 'Kyoto Encyclopedia of Genes and Genomes' (KEGG) database was used for target gene and pathway analysis. A total of three miRNAs from EOC serum (hsa-miR-1909-5p, hsa-miR-885-5p and hsa-let-7d-3p) and one microRNA from tissue samples (hsa-miR-200c-3p) were validated as significant to distinguish patients with EOC from HIs. KEGG pathway enrichment analysis showed seven significant pathways, which included 'prion diseases', 'proteoglycans in cancer', 'oxytocin signaling pathway', 'hippo signaling pathway', 'adrenergic signaling in cardiomyocytes', 'oocyte meiosis' and 'thyroid hormone signaling pathway', in which the validated miRNAs served a role. This supports the hypothesis that four validated miRNAs, have the potential to be a biomarker of EOC diagnosis and target for treatment.

Quiescent Ovarian Cancer Cells Secrete Follistatin to Induce Chemotherapy Resistance in Surrounding Cells in Response to Chemotherapy.

PURPOSE: We recently reported that the transcription factor NFATC4, in response to chemotherapy, drives cellular quiescence to increase ovarian cancer chemoresistance. The goal of this work was to better understand the mechanisms of NFATC4-driven ovarian cancer chemoresistance. EXPERIMENTAL DESIGN: We used RNA sequencing to identify NFATC4-mediated differential gene expression. CRISPR-Cas9 and FST (follistatin)-neutralizing antibodies were used to assess impact of loss of FST function on cell proliferation and chemoresistance. ELISA was used to quantify FST induction in patient samples and in vitro in response to chemotherapy. RESULTS: We found that NFATC4 upregulates FST mRNA and protein expression predominantly in quiescent cells and FST is further upregulated following chemotherapy treatment. FST acts in at least a paracrine manner to induce a p-ATF2-dependent quiescent phenotype and chemoresistance in non-quiescent cells. Consistent with this, CRISPR knockout (KO) of FST in ovarian cancer cells or antibody-mediated neutralization of FST sensitizes ovarian cancer cells to chemotherapy treatment. Similarly, CRISPR KO of FST in tumors increased chemotherapy-mediated tumor eradication in an otherwise chemotherapy-resistant tumor model. Suggesting a role for FST in chemoresistance in patients, FST protein in the abdominal fluid of patients with ovarian cancer significantly increases within 24 hours of chemotherapy exposure. FST levels decline to baseline levels in patients no longer receiving chemotherapy with no evidence of disease. Furthermore, elevated FST expression in patient tumors is correlated with poor progression-free, post-progression-free, and overall survival. CONCLUSIONS: FST is a novel therapeutic target to improve ovarian cancer response to chemotherapy and potentially reduce recurrence rates.

Different perspectives on translational genomics in personalized medicine

Personalized medicine is a relatively new and interesting concept in the medical and healthcare industries. New approaches in current research have supported the search for biomarkers, based on the genomic, epigenomic and proteomic profile of individuals, using new technological tools. This perspective involves the potential to determine optimal medical interventions and provide the optimal benefit-risk balance for treatment, whilst it also takes a patient's personal situation into consideration. Translational genomics, a subfield of personalized medicine, is changing medical practice, by facilitating clinical or non-clinical screening tests, informing diagnoses and therapeutics, and routinely offering personalized health-risk assessments and personalized treatments. Further research into translational genomics will play a critical role in creating a new approach to cancer, pharmacogenomics, and women's health. Our current knowledge may be used to develop new solutions that can be used to minimize, improve, manage, and delay the symptoms of diseases in real-time and maintain a healthy lifestyle. In this review, we define and discuss the current status of translational genomics in some special areas including integration into research and health care.