Background: Malignant tumors are heterogeneous diseases characterized by different metabolic phenotypes. These were revealed by Warburg effect and reverse Warburg effect phenotypes. However, the molecular mechanism remains largely unknown.
Methods: Isobaric tag for relative and absolute quantification (iTRAQ) proteomics was used to identify mitochondrial differentially expressed proteins (DEPs) of ovarian cancers relative to controls, followed by bioinformatic analysis. The molecular profiling of long non-coding RNAs (lncRNAs) was also investigated by searching the dataset of the Cancer Genome Atlas (TCGA) consisting of 419 ovarian cancer patients.
Results: A total of 1198 mitochondrial DEPs were identified by iTRAQ quantitative proteomics. Bioinformatic analysis of those DEPs showed that cancer cells exhibited an increased dependence on Kreb's cycle and oxidative phosphorylation, with some related upregulated proteins. Moreover, TCGA analysis showed lncRNA SNHG3 was not only related to ovarian cancer survival, but also energy metabolism. Interestingly, integrated analysis of the results of GSEA analysis and Starbase 2.0 found that SNHG3 was related to energy metabolism by regulating miRNAs and EIF4AIII, and those molecules had target sites with PKM, PDHB, IDH2, and UQCRH in the glycolysis, Kreb's cycle, and oxidative phosphorylation (OXPHOS) pathways. Furthermore, SNHG3 might be associated with drug resistance.
Conclusion: The results derived from TCGA data and mitochondrial DEPs data are consistent with the Warburg and reverse Warburg effects that cancer cells mainly rely on glycolysis and oxidative phosphorylation to produce energy. Also, this integrated lncRNA-miRNA-mRNA and lncRNA-binding protein-mRNA signatures might have important merit for insights into molecular mechanisms and clinical implications in ovarian cancer.
Keywords: Energy metabolism; Ovarian cancer; SNHG3; TCGA; iTRAQ.
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