Y Wang1, L Lei, Y-G Chi, L-B Liu, B-P Yang. 1. Department of Gynecology, Chongqing Maternal and Child Health Hospital, Chongqing, P.R. China. gxingzhe116@hotmail.com.
Abstract
OBJECTIVE: Ovarian cancer is one of the most common causes of cancer-related deaths in women. Many studies show that dysregulated gene expression plays a key role in tumorigenesis and development. Therefore, a comprehensive understanding of ovarian serous cystadenocarcinoma survival prognosis is needed. PATIENTS AND METHODS: A large number of high-dimensional RNA-sequencing files and clinical datasets collected from the Genomic Data Commons Data Portal were utilized to identify novel potential biomarkers for determining the prognosis of patients with ovarian serous cystadenocarcinoma (OVSC). We adopted a new strategy to identify these biomarkers by integrating co-expression network analysis and the Kaplan-Meier estimation with a non-parametric bootstrapping procedure. RESULTS: Functional enrichment analysis of gene modules of interest revealed several dysregulated genes in OVSC, suggesting a close relationship between hormones and angiogenesis. In combination with this comprehensive approach, 14 genes, including ABCA10, DCX, LRRC30, ALX4, DKK4, SGCZ, ANKS4B, FHL5, SPRR2F, CHRNG, GABRR1, STMN2, CRHBP, and GSTM5, were shown to serve as candidate biomarkers for predicting the prognosis of patients with OVSC. CONCLUSIONS: The current study identified several valuable prognostic biomarkers and several potential therapeutic targets for treating OVSC.
OBJECTIVE:Ovarian cancer is one of the most common causes of cancer-related deaths in women. Many studies show that dysregulated gene expression plays a key role in tumorigenesis and development. Therefore, a comprehensive understanding of ovarian serous cystadenocarcinoma survival prognosis is needed. PATIENTS AND METHODS: A large number of high-dimensional RNA-sequencing files and clinical datasets collected from the Genomic Data Commons Data Portal were utilized to identify novel potential biomarkers for determining the prognosis of patients with ovarian serous cystadenocarcinoma (OVSC). We adopted a new strategy to identify these biomarkers by integrating co-expression network analysis and the Kaplan-Meier estimation with a non-parametric bootstrapping procedure. RESULTS: Functional enrichment analysis of gene modules of interest revealed several dysregulated genes in OVSC, suggesting a close relationship between hormones and angiogenesis. In combination with this comprehensive approach, 14 genes, including ABCA10, DCX, LRRC30, ALX4, DKK4, SGCZ, ANKS4B, FHL5, SPRR2F, CHRNG, GABRR1, STMN2, CRHBP, and GSTM5, were shown to serve as candidate biomarkers for predicting the prognosis of patients with OVSC. CONCLUSIONS: The current study identified several valuable prognostic biomarkers and several potential therapeutic targets for treating OVSC.
Authors: Helen S Mueller; Colin E Fowler; Simona Dalin; Enrico Moiso; Tee Udomlumleart; Salil Garg; Michael T Hemann; Jacqueline A Lees Journal: Proc Natl Acad Sci U S A Date: 2021-08-24 Impact factor: 11.205