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Whole transcriptome analysis reveals non-coding RNA's competing endogenous gene pairs as novel form of motifs in serous ovarian cancer. | LitMetric

AI Article Synopsis

  • Non-coding RNAs (ncRNAs) are linked to diagnosing and treating complex diseases, with particular relevance to serous ovarian carcinoma (SOC).
  • A microarray study identified a ceRNA network, revealing new motifs (mRNA-ncRNA-mRNA) that help predict SOC using a method called deiPAGE.
  • The study established an SOC index based on 18 circRNA's ceGPs, showing a strong ability to differentiate SOC and a correlation with tumor cell activity in ovarian cancer progression.

Article Abstract

The non-coding RNA (ncRNA) regulation appears to be associated to the diagnosis and targeted therapy of complex diseases. Motifs of non-coding RNAs and genes in the competing endogenous RNA (ceRNA) network would probably contribute to the accurate prediction of serous ovarian carcinoma (SOC). We conducted a microarray study profiling the whole transcriptomes of eight human SOCs and eight controls and constructed a ceRNA network including mRNAs, long ncRNAs, and circular RNAs (circRNAs). Novel form of motifs (mRNA-ncRNA-mRNA) were identified from the ceRNA network and defined as non-coding RNA's competing endogenous gene pairs (ceGPs), using a proposed method denoised individualized pair analysis of gene expression (deiPAGE). 18 cricRNA's ceGPs (cceGPs) were identified from multiple cohorts and were fused as an indicator (SOC index) for SOC discrimination, which carried a high predictive capacity in independent cohorts. SOC index was negatively correlated with the CD8+/CD4+ ratio in tumour-infiltration, reflecting the migration and growth of tumour cells in ovarian cancer progression. Moreover, most of the RNAs in SOC index were experimentally validated involved in ovarian cancer development. Our results elucidate the discriminative capability of SOC index and suggest that the novel competing endogenous motifs play important roles in expression regulation and could be potential target for investigating ovarian cancer mechanism or its therapy.

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Source
http://dx.doi.org/10.1016/j.compbiomed.2022.105881DOI Listing

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