Identification of a Six-Gene Signature for Predicting the Overall Survival of Cervical Cancer Patients

Xiao Huo,1 Xiaoshuang Zhou,2,3 Peng Peng,2 Mei Yu,2 Ying Zhang,2 Jiaxin Yang,2 Dongyan Cao,2 Hengzi Sun,4 Keng Shen2 1Medical Research Center, Peking University Third Hospital, Beijing,, People’s Republic of China; 2Department of Obstetrics and Gynecology, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, People’s Republic of China; 3Department of Ultrasound, Sun Yat-Sen University Cancer Center, State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Beijing, People’s Republic of China; 4Department of Obstetrics and Gynecology, Beijing Chao-Yang Hospital, Capital Medical University, Beijing, People’s Republic of ChinaCorrespondence: Keng ShenDepartment of Obstetrics and Gynecology, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, No. 1 Shuaifuyuan, Dongcheng District, Beijing, 100730, People’s Republic of ChinaTel +86-10-69155200Email shenkengpumc@163.comCorrespondence: Hengzi SunDepartment of Obstetrics and Gynecology, Beijing Chao-Yang Hospital, Capital Medical University, No. 8 GongTiNan Road, Chaoyang District, Beijing, 100020, People’s Republic of ChinaTel +86 010 85231760Email Summerel1990@163.comBackground: Although the incidence of cervical cancer has decreased in recent decades with the development of human papillomavirus vaccines and cancer screening, cervical cancer remains one of the leading causes of cancer-related death worldwide. Identifying potential biomarkers for cervical cancer treatment and prognosis prediction is necessary.Methods: Samples with mRNA sequencing, copy number variant, single nucleotide polymorphism and clinical follow-up data were downloaded from The Cancer Genome Atlas database and randomly divided into a training dataset (N=146) and a test dataset (N=147). We selected and identified a prognostic gen