Jian-Guo Zhou1, He-Tong Zhao2, Su-Han Jin3, Xu Tian4, Hu Ma5. 1. Department of Oncology, Affiliated Hospital of Zunyi Medical University, Zunyi, China. Electronic address: jianguo.zhou@fau.de. 2. Department of Traditional Chinese Medicine, Changhai Hospital, Second Military Medical University, Shanghai, China. 3. Department of Orthodontics, Affiliated Stomatological Hospital of Zunyi Medical University, Zunyi, China. 4. Chongqing University Cancer Hospital; Chongqing Cancer Hospital and Institute, Chongqing, China. 5. Department of Oncology, Affiliated Hospital of Zunyi Medical University, Zunyi, China. Electronic address: mahuab@163.com.
Abstract
OBJECTIVE: Uterine sarcoma (US) is a highly malignant cancer with poor prognosis and high mortality. This study focused on the identification of a RNA-Seq expression signature for prognosis prediction in uterine sarcoma. METHODS: We obtained RNA-Seq expression profiles from The Cancer Genome Atlas database, and differentially expressed genes were identified between US tissues and normal tissues. Univariate Cox proportional hazards regression analysis and LASSO Cox model were performed to identify and construct the prognostic gene signature. Time-dependent receiver operating characteristic, Kaplan-Meier curve and multivariate Cox regression analysis were used to assess the prognostic capacity of the six-gene signature. The nomogram was developed including prognostic signature and independent clinical factors to predict the overall survival (OS) of US patients. The functional enrichment and somatic mutation analysis were also analyzed by bioinformatics to understand the molecular mechanisms. RESULTS: This study identified a prognostic signature based on 6 genes: FGF23, TLX2, TIFAB, RNF223, HIST1H3A and AADACL4. In the training group, the median OS in the high- and low-risk groups was 19.6 vs 88.1 months (HR, 0.1412, 95% CI: 0.03295 - 0.6054; P = 0.002), respectively. In the testing group, the median OS in the high- and low-risk groups were 30 vs NR (not reach) months (HR, <0.0001, 95% CI: 0 - inf; P = 0.03). In all of patients, the low-risk group showed significant better survival compared with the high-risk group in OS, PFI, DSS and DFI. The nomogram based on the gene signature and radiation therapy was developed and successfully predicted the OS of US patients. The patients in the high-risk group displayed distinct mutation signatures comparing to patients in the low-risk group. Functional enrichment analysis indicated that the signature can play a vital role in cancer-related biological processes. CONCLUSION: Our study established a novel 6-gene signature and nomogram which could improve prognosis prediction in patients with US.
OBJECTIVE: Uterine sarcoma (US) is a highly malignant cancer with poor prognosis and high mortality. This study focused on the identification of a RNA-Seq expression signature for prognosis prediction in uterine sarcoma. METHODS: We obtained RNA-Seq expression profiles from The Cancer Genome Atlas database, and differentially expressed genes were identified between US tissues and normal tissues. Univariate Cox proportional hazards regression analysis and LASSO Cox model were performed to identify and construct the prognostic gene signature. Time-dependent receiver operating characteristic, Kaplan-Meier curve and multivariate Cox regression analysis were used to assess the prognostic capacity of the six-gene signature. The nomogram was developed including prognostic signature and independent clinical factors to predict the overall survival (OS) of US patients. The functional enrichment and somatic mutation analysis were also analyzed by bioinformatics to understand the molecular mechanisms. RESULTS: This study identified a prognostic signature based on 6 genes: FGF23, TLX2, TIFAB, RNF223, HIST1H3A and AADACL4. In the training group, the median OS in the high- and low-risk groups was 19.6 vs 88.1 months (HR, 0.1412, 95% CI: 0.03295 - 0.6054; P = 0.002), respectively. In the testing group, the median OS in the high- and low-risk groups were 30 vs NR (not reach) months (HR, <0.0001, 95% CI: 0 - inf; P = 0.03). In all of patients, the low-risk group showed significant better survival compared with the high-risk group in OS, PFI, DSS and DFI. The nomogram based on the gene signature and radiation therapy was developed and successfully predicted the OS of US patients. The patients in the high-risk group displayed distinct mutation signatures comparing to patients in the low-risk group. Functional enrichment analysis indicated that the signature can play a vital role in cancer-related biological processes. CONCLUSION: Our study established a novel 6-gene signature and nomogram which could improve prognosis prediction in patients with US.
Authors: Jian-Guo Zhou; Anna-Jasmina Donaubauer; Udo Gaipl; Markus Hecht; Benjamin Frey; Ina Becker; Sandra Rutzner; Markus Eckstein; Roger Sun; Hu Ma; Philipp Schubert; Claudia Schweizer; Rainer Fietkau; Eric Deutsch Journal: J Immunother Cancer Date: 2021-02 Impact factor: 13.751
Authors: Dong Soo Suh; Yong Jung Song; Hyun-Jin Roh; Sang Hun Lee; Dae Hoon Jeong; Tae Hwa Lee; Kyung Un Choi; Ki Hyung Kim Journal: Cancer Manag Res Date: 2021-06-24 Impact factor: 3.989