Introduction/Background*Epithelial ovarian carcinoma (EOC) is associated with the highest mortality among gynecological carcinomas. High mortality is due to the diagnosis at advanced stages and development of resistance to anticancer therapy regimens based on taxanes and platinum derivatives. In effort to overcome the problem of resistance, novel therapeutic drugs are synthetized and new potential therapeutic targets are under study.
Resistance of cancer cells is a multifactorial process, where deregulation of transcriptome may play important role. In addition, long non-coding RNAs (lncRNAs) with recognized regulatory functions may modulate transcriptome profile and its association with resistance and therapy response. The aim of this study was to analyze transcriptome profile of EOC patients and decipher interactions between protein-coding genes and lncRNAs, which may help to reveal new potential therapeutic targets of EOC.
Methodology Set of 60 EOC patients with different sensitivity to the adjuvant chemotherapy was divided into two groups based on their platinum-free interval (PFI) after adjuvant chemotherapy by platinum derivatives in combination with paclitaxel. Together 37 patients had PFI > 12 months (sensitive; 27 ±24 months) and 23 patients had PFI < 12 months (resistant; 5 ±3 months). We have performed transcriptome profiling using 3´mRNA QuantSeq FWD kit (Lexogen) with sequencing on the NextSeq500 platform (Illumina). Bioinformatics analysis was carried out by in-house pipeline with final differential expression analysis.
Result(s)*Bioinformatics analysis of transcriptome profile revealed significant differences in the expression profile of EOC patients with different sensitivity to adjuvant chemotherapy. We observed twelve differentially expressed protein coding genes (after false discovery rate correction) – MYH11, JAK2, SETDB2, SUCNR1, IRAG2, CCN5, FOXP2, GCNT3, KCNN3, LGI4, EGFLAM, HPGDS and four lncRNAs (LINC-HOXD1-1, LINC-MLN-5, LINC-RPIA-2, LINC-LY86-4). For JAK2 and KCNN3 genes, we found in literature the evidence of their potential role in resistance of ovarian cancer.
Conclusion*On the basis of transcriptome profile, we discovered till unknown associations of gene expression levels with response in ovarian carcinoma patients (MYH11, SETDB2, IRAG2, FOXP2 and LGI4) together with four lncRNAs (LINC-HOXD1-1, LINC-MLN-5, LINC-RPIA-2, LINC-LY86-4) with potential role in therapy resistance in ovarian carcinoma patients.
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