全转录组分析揭示非编码 RNA 的竞争内源性基因对作为浆液性卵巢癌中新型基序形式。

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

机构信息

Shenzhen People's Hospital, The Second Clinical Medical College of Jinan University, The First Affiliated Hospital of Southern University of Science and Technology, Shenzhen, China.

Shenzhen People's Hospital, The Second Clinical Medical College of Jinan University, The First Affiliated Hospital of Southern University of Science and Technology, Shenzhen, China; Department of Computer Science and Engineering, The Chinese University of Hong Kong, Hong Kong.

出版信息

Comput Biol Med. 2022 Sep;148:105881. doi: 10.1016/j.compbiomed.2022.105881. Epub 2022 Jul 20.

DOI:10.1016/j.compbiomed.2022.105881

PMID:35940161

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.

摘要

非编码 RNA（ncRNA）的调控似乎与复杂疾病的诊断和靶向治疗有关。竞争性内源 RNA（ceRNA）网络中的非编码 RNA 和基因的基序可能有助于准确预测浆液性卵巢癌（SOC）。我们进行了一项微阵列研究，对 8 个人类 SOC 和 8 个对照的全转录组进行了分析，并构建了一个包括 mRNAs、长 ncRNAs 和环状 RNA（circRNAs）的 ceRNA 网络。使用一种称为去个体化基因表达配对分析的噪声消除方法（deiPAGE），从 ceRNA 网络中识别出新型基序（mRNA-ncRNA-mRNA），并将其定义为非编码 RNA 的竞争性内源基因对（ceGPs）。从多个队列中鉴定了 18 个环状 RNA 的 ceGPs（cceGPs），并将其融合为 SOC 鉴别指标（SOC 指数），该指标在独立队列中具有较高的预测能力。SOC 指数与肿瘤浸润中的 CD8+/CD4+比值呈负相关，反映了卵巢癌进展中肿瘤细胞的迁移和生长。此外，SOC 指数中大多数经实验验证的 RNA 均参与卵巢癌的发生发展。我们的研究结果阐明了 SOC 指数的鉴别能力，并表明新型竞争性内源基序在表达调控中发挥重要作用，可能成为研究卵巢癌机制或治疗方法的潜在靶点。