Abstract A14: TP53 missense mutations associate with different metabolic pathways

Background: Deleterious TP53 mutations are found in 99% of patients with high-grade serous ovarian cancer (HGSOC). TP53 missense mutations, found in two-thirds of HGSOC tumors, endow the mutant protein with new gain-of-function (GOF) activities leading to altered expression of genes involved in maintaining controlled cellular metabolism and the development of drug resistance. Identification of specific altered pathways could be exploited therapeutically. We investigated whether all missense mutations alter the same metabolic pathways. Methods: We used publicly available data from The Cancer Genome Atlas (TCGA) and the Australia Ovarian Cancer Study (AOCS). TCGA and AOCS gene expression datasets were downloaded from the Curated Ovarian Data, a resource of uniformly prepared microarray data from 23 studies with curated and documented clinical metadata. We merged gene expression data from TCGA (Affymetrix HT_HG-U133A) and AOCS (Affymetrix HG-U133Plus2), subset to 12,211 features common to both datasets and included non-missing values of invasive HGSOC. TP53 mutations were downloaded from TCGA and obtained for AOCS and merged with the curated datasets. The final datasets consisted of 295 patients in TCGA (N=184 with missense mutations with putative GOF activity, and N=111 nonsense mutations with putative loss of function (LOF) activity and 21 wild-type) and 142 patients in AOCS (N=83 missense mutations with putative GOF activity, N=59 nonsense mutations with putative LOF activity and N=13 wild-type). Gene expression values were normalized in each dataset separately by subtracting the mean value of each gene and dividing by the standard deviation. Mutations were categorized according to missense vs nonsense mutation class and also according to specific mutations. We evaluated all gene sets in KEGG but focused a priori on the association of Oxidative Phosphorylation (OXPHOS), Fatty Acid Metabolism (FA), Glycolysis and Gluconeogenesis (GLY), and the P53 pathway with overall (OS) and progression-free survival (PFS) using Cox regression models stratified by mutation class and adjusted for age and stage. Results: There were no significant differences between TP53 missense vs nonsense mutation class for gene set expressions for a priori pathways of interest in TCGA, and a nominal difference for the P53 gene set expression (P=0.07) in AOCS. Comparing TCGA, AOCS, and the combined datasets, differential gene set expressions by TP53 mutation class were observed in all three datasets at P Conclusions: Specific TP53 missense mutations are associated with different metabolic pathways and may lead to differences in survival. Citation Format: Linda E. Kelemen, James D. Brenton, David D. Bowtell, Brooke L. Fridley. TP53 missense mutations associate with different metabolic pathways. [abstract]. In: Proceedings of the AACR Conference: Addressing Critical Questions in Ovarian Cancer Research and Treatment; Oct 1-4, 2017; Pittsburgh, PA. Philadelphia (PA): AACR; Clin Cancer Res 2018;24(15_Suppl):Abstract nr A14.