Unique Metabolic Contexts Sensitize Cancer Cells and Discriminate between Glycolytic Tumor Types

Abstract

Cancer cells utilize variable metabolic programs in order to maintain homeostasis in response to environmental challenges. To interrogate cancer cell reliance on glycolytic programs under different nutrient availabilities, we analyzed a gene panel containing all glycolytic genes as well as pathways associated with glycolysis. Using this gene panel, we analyzed the impact of an siRNA library on cellular viability in cells containing only glucose or only pyruvate as the major bioenergetic nutrient source. From these panels, we aimed to identify genes that elicited conserved and glycolysis-dependent changes in cellular bioenergetics across glycolysis-promoting and OXPHOS-promoting conditions. To further characterize gene sets within this panel and identify similarities and differences amongst glycolytic tumor RNA-seq profiles across a pan-cancer cohort, we then used unsupervised statistical classification of RNA-seq profiles for glycolytic cancers and non-glycolytic cancer types. Here, Kidney renal clear cell carcinoma (KIRC); Head and Neck squamous cell carcinoma (HNSC); and Lung squamous cell carcinoma (LUSC) defined the glycolytic cancer group, while Prostate adenocarcinoma (PRAD), Thyroid carcinoma (THCA), and Thymoma (THYM) defined the non-glycolytic cancer group. These groups were defined based on glycolysis scoring from previous studies, where KIRC, HNSC, and LUSC had the highest glycolysis scores, meanwhile, PRAD, THCA, and THYM had the lowest. Collectively, these results aimed to identify multi-omic profiles across cancer types with demonstrated variably glycolytic rates. Our analyses provide further support for strategies aiming to classify tumors by metabolic phenotypes in order to therapeutically target tumor-specific vulnerabilities.