Developing a 5-gene prognostic signature for cervical cancer by integrating mRNA and copy number variations

BMC Cancer

Wenxin Liu¹  Qiuying Jiang²  ShiHao Liu³  Dongfang Wu⁴  Zhikun Zhao⁴  Chao Sun⁴ 

[1] Department of Gynecological Oncology, Tianjin Medical Cancer Institute and Hospital, National Clinical Research Center for Cancer, Key Laboratory of Cancer Prevention and Therapy,Tianjin, Tianjin’s Clinical Research Center for Cancer, West Huan-Hu Rd, Ti Yuan Bei, Hexi District, 300060, Tianjin, China;Department of Internal Medicine, Second Affiliated College of Harbin Medical University, 246 Xuefu Road, Nangang District, 230100, Harbin City, Heilongjiang Province, China;Department of Obstetrics and Gynecology, The Fourth Hospital of Hebei Medical University, NO.12, JianKang Road, 130100, Shijiazhuang, Hebei Province, China;YuceBio Technology Co., Ltd, 4th floor, phase I, dabaihui center, no.2002, Shenyan Road, Haishan street, Yantian District, 440300, Shenzhen City, Guangdong Province, China;

关键词: Cervical cancer;    Copy number variations;    Differential expressed genes;    Prognostic signature;    Bioinformatics;   

DOI  :  10.1186/s12885-022-09291-z

来源: Springer

【 摘 要 】

BackgroundCervical cancer is frequently detected gynecological cancer all over the world. This study was designed to develop a prognostic signature for an effective prediction of cervical cancer prognosis.MethodsDifferentially expressed genes (DEGs) were identified based on copy number variation (CNV) data and expression profiles from different databases. A prognostic model was constructed and further optimized by stepwise Akaike information criterion (stepAIC). The model was then evaluated in three groups (training group, test group and validation group). Functional analysis and immune analysis were used to assess the difference between high-risk and low-risk groups.ResultsThe study developed a 5-gene prognostic model that could accurately classify cervical cancer samples into high-risk and low-risk groups with distinctly different prognosis. Low-risk group exhibited more favorable prognosis and higher immune infiltration than high-risk group. Both univariate and multivariate Cox regression analysis showed that the risk score was an independent risk factor for cervical cancer.ConclusionsThe 5-gene prognostic signature could serve as a predictor for identifying high-risk cervical cancer patients, and provided potential direction for studying the mechanism or drug targets of cervical cancer. The integrated analysis of CNV and mRNA expanded a new perspective for exploring prognostic signatures in cervical cancer.

【 授权许可】

CC BY