Unravelingthe molecular mechanism behind metabolic reprogramming caused by alterations of the enzyme PI3-kinase

• Main Author: Patel, Angana Heet
• Format: Others
• Language: English
• Published: Högskolan i Skövde, Institutionen för biovetenskap 2019
• Subjects: Medical Bioscience; Medicinsk biovetenskap
• Online Access: http://urn.kb.se/resolve?urn=urn:nbn:se:his:diva-17410

Oncogenes and tumor suppressor genes play a key role in cancer induction and progression. They directly or indirectly regulate critical metabolic pathways, phosphatidylinositol-3 kinase pathway being frequently activated pathway in cancer. The catalytic subunit of phosphatidylinositol-4,5-bisphosphate 3-kinase (PI3K), p110α, is the most frequently mutated kinase in human cancer, E542K, E545K, and H1047R mutations being the most common. Expression of hepatic E545K and H1047R p110α mutants in vivo shows marked and rapid increase in hepatic lipid and glycogen accumulation in mice with developmental (chronic) liver-specific deletion of p110α, which was not seen in mice when wildtype p110α is overexpressed. To investigate the logical pathways that could explain the lipid accumulation in mutant expressing mice, RNA sequencing from wildtype, knockout and mutated mouse livers was performed. Read alignment and count quantification was done using the Rsubread package and the statistical analyses are performed using the DeSeq2 package. Differentially expressed genes were identified with adjusted p-value of 0.05. Gene ontology analysis was performed on the differentially expressed genes using clusterProfiler, an R package to identify several key pathways which were upregulated and downregulated among the different sample groups. Signaling pathways related to cell cycle processes were mainly upregulated in the mutated samples when compared with the wildtype as well as knockout samples while signaling pathways related to many metabolic processes seem to be downregulated in mutated samples, even though these mutants showed upregulated metabolism by accumulation of lipids and glycogen physiologically. To confirm the results of gene expression data the results have to be cross validated with the gold standard quantitative Real Time Polymerase Chain Reaction.