Background: Ovarian cancer (OC) is one of the most lethal gynecological
malignant neoplasms. The aim of this study was to use high-throughput sequencing
data to investigate the molecular and clinical characteristics of OC subtypes
related to lipid metabolism and glycolysis, thus providing a theoretical basis
for clinical decision-making. Methods: Molecular data and
clinicopathological characteristics of OC patients were extracted from the Cancer
Genome Atlas (TCGA), Genotype-Tissue Expression Project (GTEx), and the Gene
Expression Omnibus (GEO). Following analysis of genes involved in lipid
metabolism and glycolysis, OC was classified into subtypes by unsupervised
clustering. The molecular features and clinical outcomes of these subtypes were
then evaluated. Results: OC patients were divided into five subtypes
based on the analysis of nine genes of interest. Amongst these, patients in
subtype D had longer overall survival and more benign clinical features. Subtypes
B and E had shorter overall- and progression-free survival, respectively. Both
the B and E subtypes were closely related to lipid metabolism and to the
glycolytic process. Subtype D was positively correlated with the infiltration of
CD8