Four Types of RNA Modification Writer-Related lncRNAs Are Effective Predictors of Prognosis and Immunotherapy Response in Serous Ovarian Carcinoma

Frontiers in Immunology

Su Chen¹  Su-Ni Wu¹  Lele Ye²  Sangsang Tang²  Ruanmin Zou³  Yingying Hu⁴  Kan Pan⁵  Su Fang⁶  Xinyu Shi⁶  Dan Xiang⁶  Xiangyang Xue⁶  Shiyu Feng⁶  Xinya Tong⁶  Gangqiang Guo⁶  Nan Wang⁶  Haoke Zhang⁶ 

[1] Department of Gynecologic Oncology, Wenzhou Central Hospital, Wenzhou, China;Department of Gynecologic Oncology, Women’s Hospital, School of Medicine, Zhejiang University, Hangzhou, China;Department of Obstetrics and Gynecology, The First Affiliated Hospital, Wenzhou Medical University, Wenzhou, China;Department of Obstetrics and Gynecology, The Second Affiliated Hospital and Yuying Children’s Hospital of Wenzhou Medical University, Wenzhou, China;First Clinical College, Wenzhou Medical University, Wenzhou, China;Wenzhou Collaborative Innovation Center of Gastrointestinal Cancer in Basic Research and Precision Medicine, Wenzhou Key Laboratory of Cancer-related Pathogens and Immunity, Department of Microbiology and Immunology, Institute of Molecular Virology and Immunology, Institute of Tropical Medicine, School of Basic Medical Sciences, Wenzhou Medical University, Wenzhou, China;

关键词: serous ovarian carcinoma;    RNA modification writers;    lncRNA;    prognosis;    immune microenvironment;   

DOI  :  10.3389/fimmu.2022.863484

来源: DOAJ

【 摘 要 】

Serous ovarian carcinoma (SOC) is a gynecological malignancy with high mortality rates. Currently, there is a lack of reliable biomarkers for accurate SOC patient prognosis. Here, we analyzed SOC RNA-Seq data from The Cancer Genome Atlas (TCGA) to identify prognostic biomarkers. Through the pearson correlation analysis, univariate Cox regression analysis, and LASSO-penalized Cox regression analysis, we identified nine lncRNAs significantly associated with four types of RNA modification writers (m6A, m1A, APA, and A-I) and with the prognosis of SOC patients (P <0.05). Six writer-related lncRNAs were ultimately selected following multivariate Cox analysis. We established a risk prediction model based on these six lncRNAs and evaluated its prognostic value in multiple groups (training set, testing set, and entire set). Our risk prediction model could effectively predict the prognosis of SOC patients with different clinical characteristics and their responses to immunotherapy. Lastly, we validated the predictive reliability and sensitivity of the lncRNA-based model via a nomogram. This study explored the association between RNA modification writer-related lncRNAs and SOC prognosis, providing a potential complement for the clinical management of SOC patients.

【 授权许可】

Unknown