Abstract
BackgroundCopy number variation (CNV) suggests genetic changes in malignant tumors. Abnormal expressions of long non-coding RNAs (lncRNAs) resulted from genomic and epigenetic abnormalities play a driving role in tumorigenesis of cervical cancer. However, the role of lncRNAs-related CNV in cervical cancer remained largely unclear.MethodsThe data of messenger RNAs (mRNAs), DNA methylation, and DNA copy number were collected from 292 cervical cancer specimens. The prognosis-related subtypes of cervical cancer were determined by multi-omics integration analysis, and protein-coding genes (PCGs) and lncRNAs with subtype-specific expressions were identified. The CNV pattern of the subtype-specific lncRNAs was analyzed to identify the subtype-specific lncRNAs. A prognostic risk model based on lncRNAs was established by least absolute shrinkage and selection operator (LASSO).ResultsMulti-omics integration analysis identified three molecular subtypes incorporating 617 differentially expressed lncRNAs and 1395 differentially expressed PCGs. The 617 lncRNAs were found to intersect with disease-related lncRNAs. Functional enrichment showed that 617 lncRNAs were mainly involved in tumor metabolism, immunity and other pathways, such as p53 and cAMP signaling pathways, which are closely related to the development of cervical cancer. Finally, according to CNV pattern consistent with differential expression analysis, we established a lncRNAs-based signature consisted of 8 lncRNAs, namely, RUSC1-AS1, LINC01990, LINC01411, LINC02099, H19, LINC00452, ADPGK-AS1, C1QTNF1-AS1. The interaction of the 8 lncRNAs showed a significantly poor prognosis of cervical cancer patients, which has also been verified in an independent dataset.ConclusionOur study expanded the network of CNVs and improved the understanding on the regulatory network of lncRNAs in cervical cancer, providing novel biomarkers for the prognosis management of cervical cancer patients.
Highlights
Copy number variation (CNV) suggests genetic changes in malignant tumors
Identification of prognostic molecular subtypes through comprehensive analysis of DNA methylation, CNVs and transcriptome To identify the prognostic molecular subtypes of cervical cancer, genes showing protein-coding genes (PCGs), CNV and methylation with prognostic significance were screened based on univariate Cox proportional risk model, with a threshold of p < 0.05
The results of multiomics clustering were compared with those obtained by separate hierarchical clustering (Fig. S1A), and the results showed that the three molecular subtypes determined by multi-omics clustering had some consistency with those obtained by single-omics clustering
Summary
Copy number variation (CNV) suggests genetic changes in malignant tumors. There are 500,000 newly diagnosed cases of cervical cancer and 300,000 deaths, and 80% of all the cervical cancer cases occur in developing regions [2]. The infection of high-risk HPV does not necessarily lead to cervical cancer, suggesting that HPV infection is a principal but not a decisive cause of cervical cancer [5]. Study found that cervical cancer could develop independently by genetic changes with altered expressions of oncogenes or tumor suppressor genes or together with HPV infection [6]. The five-year survival rate for cervical cancer patients with early detection of cervical cancer is 92% [4], but the chance drops sharply for patients with tumor spreading to surrounding tissues or other distant organs. The early detection of cervical cancer has a strong significance in cervical cancer intervention and treatment
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