Construction of a prognostic signature for serous ovarian cancer based on lactate metabolism-related genes

Abstract

Background:The key biochemical feature of malignant tumor is the conversion of energy metabolism from oxidative phosphorylation to glycolysis, which provides sufficient capacity and raw materials for tumor cell rapid growth. Our study aims to construct a prognostic signature for ovarian cancer based on lactate metabolism-related genes (LMRGs).Methods: Data of ovarian cancer and non-diseased ovarian data were downloaded from TCGA and the GTEx database, respectively. LMRGs were obtained from GeneCards and MSigDB databases, and the differentially expressed LMRGs were identified using limma and DESeq2 R packages. Cox regression analysis and LASSO were performed to determine the LMRGs associated with OS and develop the prognostic signature. Then, clinical significance of the prognostic signature in ovarian cancer was assessed.Results: A total of 485 differentially expressed LMRGs in ovarian tissue were selected for subsequent analysis, of which 324 were up-regulated and 161 were down regulated. We found that 22 LMRGs were most significantly associated with OS by using the univariate regression analysis. The prognostic scoring model was consisted of 12 LMRGs (SLCO1B3, ERBB4, SLC28A1, PDSS1, BDH1, AIFM1, TSFM, PPARGC1A, HGF, FGFR1, ABCC8, TH). Kaplan-Meier survival analysis indicated that poorer overall survival (OS) in the high-risk group patients (P<0.0001). This prognostic signature could be an independent prognostic indicator after adjusting to other clinical factors. The calibration curves of nomogram for the signature at 1, 2, and 3 years and the ROC curve demonstrated good agreement between the predicted and observed survival rates of ovarian cancer patients. Furthermore, the high-risk group patients have much lower expression level of immune checkpoint-TDO2 compared with the low-risk group (P=0.024). Conclusions:We established a prognostic signature based on LMRGs for ovarian cancer, and highlighted emerging evidence indicating that this Frontiers in Oncology frontiersin.org 01

Comprehensive profiling of endocrine metabolism identifies a novel signature with robust predictive value in ovarian cancer

“…For example, a study reporting extraction of metabolism‐related genes from TCGA database identified a prognostic signature comprised of PTGIS, AOC3 and IDO1 28 . Meng et al 29 . screened TCGA and GTEx databases for differentially expressed genes in high‐grade serous ovarian cancer and demonstrated that these genes are involved in multiple metabolic pathways.…”

Landscape of Metabolite-Protein Interaction Networks Reveals Prognostic Subtypes of Ovarian Cancer

“…Several systematic strati cation strategies have been developed to investigate OV metabolic heterogeneity [17,51,15,52,53,14]; however, they rarely consider MIPros. In this study, we not only rede ned and validated the OV subtypes based on the MPIscore in the TCGA-OV and GEO validation sets but also characterized the subtype-speci c clinical features, metabolism, genomic mutations, immune in ltration and regulations between the MPIscore groups, providing a comprehensive understanding of OV metabolism and guidelines for the precision diagnosis and treatment of OV.…”

Glutamine metabolism prognostic index predicts tumour microenvironment characteristics and therapeutic efficacy in ovarian cancer

“…(“Chen signature”), a prognostic model for platinum‐treated OC reported by Sabatier et al 25 . (“Sabatier signature”), a lactate metabolism‐related signature reported by Xiang et al 26 . (“Xiang signature”), a hematogenous and lymphatic metastasis signature reported by Yue et al 27 .…”

“…The proportional hazards (PH) assumption was verified with the Schoenfeld test. Additionally, the 3-and 5-year ROC values of the GMPI were compared with those of other published gene signatures for OC, including a prognosisrelated genes signature reported by Chen et al 24 ("Chen signature"), a prognostic model for platinum-treated OC reported by Sabatier et al 25 ("Sabatier signature"), a lactate metabolism-related signature reported by Xiang et al 26 ("Xiang signature"), a hematogenous and lymphatic metastasis signature reported by Yue et al 27 ("Yue signature"), and an omentum metastasis-related prognostic signature reported by Zhang et al 28 ("Zhang signature"). Finally, the precision and accuracy of nomogram was evaluated with ROC curves, the Concordance index (C index) and restricted mean survival (RMS) time curves.…”