Differential Gene Set Enrichment Analysis of AKT-Expressing Primary Tumors from the Cancer Genome Atlas | AIChE

Differential Gene Set Enrichment Analysis of AKT-Expressing Primary Tumors from the Cancer Genome Atlas

Authors 

Jeon, P. J. - Presenter, University of Southern California
Sussman, J. H., University of Southern California
Graham, N., University of Southern California
Oncogenes can impose various alterations in tumor cell metabolism. For instance, many cancers primarily use glycolysis to support their continual proliferation and survival. Such chemical dependencies and overregulation of pathways can also leave cancer cells vulnerable to metabolic disruptions. One such oncogene is the Protein Kinase B, also known as AKT, which our previous investigation demonstrated that AKT-expressing model human mammary epithelial and clinical breast cancer cell lines experience reactive oxygen species-induced death under environments that force the use of oxidative metabolism. During the investigation, an analysis tool called Gene Set Enrichment Analysis (GSEA) revealed the upregulation of glutathione metabolism in the AKT-expressing cells.

Differential Gene Set Enrichment Analysis (DGSEA), a recently developed adaptation of GSEA, identifies the enrichment of combinations of pathways rather than individual pathways, which provides a novel approach to observing metabolic regulations in cancer. To further explore the oncogenic effect on cancer metabolism, transcriptomic data of primary tumor samples from the publicly available The Cancer Genome Atlas (TCGA) Program was curated in groups with the highest and lowest signature scores related to the AKT/PI3K/mTOR signaling pathway. Transcriptomic data processed using RNA-seq differential expression algorithms and DGSEA revealed differential regulations of several core cellular metabolic pathways that may demonstrate a trade-off relationship with glycolysis. Combining DGSEA results with individual genomic data and investigation on the identified pathways can expand our understanding of cancer metabolism and may provide insight to novel therapies for personalized cancer treatment.