Deciphering the complexities in oncogenesis: an integrative approach to understand its adaptive phenotypes

Abstract

Metabolic reprogramming is a hallmark of cancer. Changes in metabolism have been verified for their role in the progression of glioblastomas. Metabolic reprogramming allows the tumor cells to switch between phenotypes under changing growth condition that help these tumors to evolve and develop resistance against the therapeutic regimens. In the present thesis, the alternate routes of therapeutic escape, opportunistic mode of nutrient acquisition, and evolving metabolic routes to sustain oncogenic phenotypes under various growth conditions have been studied by formulating and analyzing computational and mathematical models. In order to gain a holistic perspective of the pathway behavior and condition specific changes in the metabolic network of glioblastoma, a constraint-based metabolic model was formulated and analyzed. Model simulations showed a major flux re-routing towards glutathione production. Cystine and glucose were observed to be the minimal essential nutrients that could sustain glioblastoma growth under limited nutrient availability. Glycine transporter in combination with the serine biosynthesis enzymes were proposed as potential therapeutic targets, as their knockout was observed to effectively reduce glioblastoma growth. To understand the changes in the redox and thiol status of the cells and the changes occurring in the oxidant-antioxidant balance during gliomagenesis, a dynamic ordinary differential equation model was formulated. Model analyses established that the changing dynamics of glutathione peroxidase, glutathione oxidoreductase and NADPH oxidase determines the oxidant-antioxidant balance during gliomagenesis. Parameters of non-intuitive reactions in the network like cystine reductase, glutathione synthase, and fructose-bisphosphate aldolase were observed to influence the ROS level and thiol ratio of the cells and were proposed to alter the ROS manipulative strategies in glioma treatment. The post-transcriptional regulation imposed by microRNAs on the metabolic genes was studied using graph theoretical approach. Using bipartite projection and backbone extraction techniques, the key regulatory microRNAs controlling central carbon, fatty acid, lipid, glycan, amino acid, and nucleotide metabolism were identified. Analysis showed that the central carbon metabolism, lipid, and amino acid metabolism were highly regulated by the microRNAs. The microRNA combinations (hsa-miR-15b-5p + hsamiR-500a-5p + hsa-miR-129-1-3p), (hsa-miR-15b-5p + hsa-miR-124-3p + hsa-miR-138-2-3p), (hsa-miR-7-5p + hsa-miR-128-3p + hsa-miR-485-5p), (hsa-miR-15b-5p + hsa-miR-23a-3p) and (hsa-miR-124-3p + hsa-miR-300-5p + hsa-miR-23a-3p) were proposed as target combinations regulating proliferation and growth, survival, cell migration and invasion, stemness and drug resistance in glioblastoma respectively, that could be used for miRNA-based therapeutic design.