Background. Epithelial ovarian cancer (EOC) is a heterogeneous disease, which has been recently classified into four molecular subtypes, of which the mesenchymal subtype exhibited the worst prognosis. We aimed to identify a microRNA- (miRNA-) based signature by incorporating the molecular modalities involved in the mesenchymal subtype for risk stratification, which would allow the identification of patients who might benefit from more rigorous treatments. Method. We characterized the regulatory mechanisms underlying the mesenchymal subtype using network analyses integrating gene and miRNA expression profiles from The Cancer Genome Atlas (TCGA) cohort to identify a miRNA signature for prognosis prediction. Results. We identified four miRNAs as the master regulators of the mesenchymal subtype and developed a risk score model. The 4-miRNA signature significantly predicted overall survival (OS) and progression-free survival (PFS) in discovery (p=0.004 and p=0.04) and two independent public datasets (GSE73582: OS, HR: 2.26 (1.26-4.05), p=0.005, PFS, HR: 2.03 (1.34-3.09), p<0.001; GSE25204: OS, HR: 3.07 (1.73-5.46), p<0.001, PFS, HR: 2.59 (1.72-3.88), p<0.001). Moreover, in multivariate analyses, the miRNA signature maintained as an independent prognostic predictor and achieved superior efficiency compared to the currently used clinical factors. Conclusions. In conclusion, our network analysis identified a 4-miRNA signature which has prognostic value superior to currently reported clinical covariates. This signature warrants further testing and validation for use in clinical practice.
Circular RNA (circRNA) circ_POLA2 is an oncogene in lung and cervical cancers. However, the role of circ_POLA2 in other types of cancer is unknown. The present study investigated the role of circ_POLA2 in endometrial cancer (EC). The mRNA expression levels of circ_POLA2 and microRNA (miR)-31 in EC and paired adjacent normal tissues were analyzed using reverse transcription-quantitative (RT-qPCR). Overexpression of circ_POLA2 was achieved in the EC cell lines, and its effects on miR-31 mRNA expression level and methylation were evaluated using RT-qPCR and methylation-specific PCR (MSP), respectively. Cell proliferation was assessed using a Cell Counting Kit-8 assay. The results indicated that circ_POLA2 was highly expressed in EC tissue and inversely correlated with miR-31 mRNA expression level. MSP analysis showed that circ_POLA2 overexpression increased miR-31 methylation and RT-qPCR analysis showed that circ_POLA2 overexpression decreased miR-31 mRNA expression level. Furthermore, circ_POLA2 overexpression also increased EC cell proliferation, while miR-31 overexpression decreased cell proliferation. Finally, circ_POLA2 overexpression reduced the effects of miR-31 overexpression. In conclusion, circ_POLA2 may increase miR-31 methylation of miR-31 in EC cells to promote cancer cell proliferation.
Background: Ovarian cancer (OC) is a highly heterogeneous disease, of which the mesenchymal subtype has the worst prognosis, is the most aggressive, and has the highest drug resistance. The cell cycle pathway plays a vital role in ovarian cancer development and progression. We aimed to screen the key cell cycle genes that regulated the mesenchymal subtype and construct a robust signature for ovarian cancer risk stratification.Methods: Network inference was conducted by integrating the differentially expressed cell cycle signature genes and target genes between the mesenchymal and non-mesenchymal subtypes of ovarian cancer and identifying the dominant cell cycle signature genes.Results: Network analysis revealed that two cell cycle signature genes (POLA2 and KIF20B) predominantly regulated the mesenchymal modalities of OC and used to construct a prognostic model, termed the Cell Cycle Prognostic Signature of Ovarian Cancer (CCPOC). The CCPOC-high patients showed an unfavorable prognosis in the GSE26712 cohort, consistent with the results in the seven public validation cohorts and one independent internal cohort (BL-OC cohort, qRT-PCR, n = 51). Functional analysis, drug-sensitive analysis, and survival analysis showed that CCPOC-low patients were related to strengthened tumor immunogenicity and sensitive to the anti-PD-1/PD-L1 response rate in pan-cancer (r = −0.47, OC excluded), which indicated that CCPOC-low patients may be more sensitive to anti-PD-1/PD-L1.Conclusion: We constructed and validated a subtype-specific, cell cycle-based prognostic signature for ovarian cancer, which has great potential for predicting the response of anti-PD-1/PD-L1.
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