Metabolomics integrated genomics approach: Understanding multidrug resistance phenotype in MCF-7 breast cancer cells exposed to doxorubicin and ABCA1/EGFR/PI3k/PTEN crosstalk

Abstract

Resistance of cancer cells, especially breast cancer, to therapeutic medicines represents a major clinical obstacle that impedes the stages of treatment. Carcinoma cells that acquire resistance to therapeutic drugs can reprogram their own metabolic processes as a way to overcome the effectiveness of treatment and continue their reproduction processes. Despite the recent developments in medical research in the field of drug resistance, which showed some explanations for this phenomenon, the real explanation, along with the ability to precisely predict the possibility of its occurrence in breast cancer cells, still necessitates a deep consideration of the dynamics of the tumor's response to treatment. For this purpose the current study, combined both in vitro metabolomics and in vivo genomics analysis as the most advanced omics technologies that can provide a potential en route for inventing novel strategies to perform prospective, prognostic and diagnostic biomarkers for drug resistance phenomena in mammary cancer. Doxorubicin is the currently available breast cancer chemotherapeutic medication nevertheless; it was demonstrated to cause drug resistance, which impairs patient survival and prognosis by prompting proliferation, cell cycle progression, and preventing apoptosis, interactions between signaling pathways triggered drug resistance. In this research, in vitro metabolomics analysis based on GC-MS coupled with multivariable analysis was performed on MCF-7 and DOX resistant cell lines; MCF-7/adr cultured cells in addition to, further in vivo confirmation via inducing mammary cancer in rats via two doses of 7,12-dimethylbenz(a) anthracene (DMBA) (50 mg/kg and 25 mg/kg) proceeded by doxorubicin (5 mg/kg) treatment for one month. The metabolomics in vitro results pointed out that mannitol, myoinositol, glycine, α-linolenic acid, oleic acid and stearic acid have AUC values: 0.14, 0.5, 0.7, 0.1, 0.02, −0.02 (1, 1) respectively. Glycine and myoinositol metabolites provided the best discriminative power in the wild and resistance MCF-7 phenotypes. Meanwhile, in vivo results revealed a significant crosstalk between the alternation in oxidative stress biomarkers as well as Arginase II tumor biomarker and the molecular assessment of ABCA1 and P53 gene expression that displayed a marked reduction in addition to, the obvious elevation in resistance and apoptotic biomarkers EGFR/PI3k/AKT/PTEN signaling pathway upon DMBA administration. Data revealed a significant alternation in signaling pathways related to resistance upon doxorubicin administration that affect lipid metabolism in breast cancer. In conclusion, Metabolomics integrated genomics analysis may be promising in understanding multidrug resistance phenotype in MCF-7 breast cancer cells exposed to doxorubicin through modulating ABCA1/EGFR/P53/PI3k/PTEN signaling pathway thus metabolic biomarkers in addition to molecular biomarkers elucidate the challenges fronting profitable therapy of mammary cancer and an pioneering approaches that metabolomics compromises to improve recognizing drug resistance in breast carcinoma.