Immune-Related Long Non-coding RNA Constructs a Prognostic Signature of Ovarian Cancer

Biological Procedures Online

Xiaobin Wang¹  Shan Li²  Miao He³  Xiaoyu Sun³  Yuanyuan Yan³  Xuemei Lv³  Minjie Wei⁴ 

[1] Center of Reproductive Medicine, Shengjing Hospital of China Medical University, Shenyang, China;Department of Breast Surgery, The First Affiliated Hospital of China Medical University, Shenyang, Liaoning Province, China;Department of Pharmacology, School of Pharmacy, China Medical University, Shenyang, Liaoning Province, China;Liaoning Key Laboratory of Molecular Targeted Anti-tumor Drug Development and Evaluation, Liaoning Cancer Immune Peptide Drug Engineering Technology Research Center, Key Laboratory of Precision Diagnosis and Treatment of Gastrointestinal Tumors (China Medical University), Ministry of Education, Shenyang, Liaoning Province, China;Department of Pharmacology, School of Pharmacy, China Medical University, Shenyang, Liaoning Province, China;Liaoning Key Laboratory of Molecular Targeted Anti-tumor Drug Development and Evaluation, Liaoning Cancer Immune Peptide Drug Engineering Technology Research Center, Key Laboratory of Precision Diagnosis and Treatment of Gastrointestinal Tumors (China Medical University), Ministry of Education, Shenyang, Liaoning Province, China;Shenyang Kangwei Medical Laboratory Analysis Co. LTD, Shenyang, Liaoning Province, China;

关键词: Ovarian cancer;    Long non-coding RNA;    Immune infiltration;    Signature;    Chemo-sensitivity;   

DOI  :  10.1186/s12575-021-00161-9

来源: Springer

【 摘 要 】

BackgroundSince ovarian cancer leads to the poor prognosis in women all over the world, we aim to construct an immune-related lncRNAs signature to improve the survival of ovarian cancer patients.MethodsNormal and cancer patient samples and corresponding clinical data of ovarian were obtained from The Genotype-Tissue Expression (GTEx) portal and The Cancer Genome Atlas (TCGA) database. The predictive signature was constructed by the lasso penalty Cox proportional hazard regression model. The division of different risk groups was accounting for the optimal critical value of the time-dependent Receiver Operating Characteristic (ROC) curve. Finally, we validated and evaluated the application of this prognostic signature based on the clinical factors, chemo-sensitivity and immune status of different risk groups.ResultsThe signature was established from 145 DEirlncRNAs and can be shown as an independent prognostic risk factor with accurate prediction on overall survival in ovarian cancer patients. Further analysis on the application of the prognostic signature showed that patients with low-risk had a better sensitivity to chemotherapy and a higher immunogenicity.ConclusionWe constructed and verified an effective signature based on DEirlncRNA pairs, which could predict the prognosis, drug sensitivity and immune status of ovarian cancer patients and promote the prognostic estimation and individualized treatment.

【 授权许可】

CC BY