Acetylation mediated by the p300/CBP-associated factor determines cellular energy metabolic pathways in cancer

Abstract

Abstract. Normal cells produce energy either through OXPHOS in the presence of oxygen or glycolysis in its absence. Cancer cells produce energy preferably through glycolysis even in the presence of oxygen, thereby, acquiring survival and proliferative advantages. Oncogenes and tumour suppressors control these metabolic pathways by regulating the expression of their target genes involved in these processes. During hypoxia, HIF-1 favours high glycolytic flux by upregulating glycolytic enzymes. Conversely, p53 inhibits glycolysis and increases OXPHOS expression through TIGAR and SCO2 gene expression, respectively. We hypothesise that the p300/ CBP-associated factor (PCAF) as a common co-factor shared between p53 and HIF-1 plays an important role in the regulation of energy production by modulating SCO2 and TIGAR gene expression mediated by these two transcription factors. The possible involvement of HIF-1 in the regulation of SCO2 and TIGAR gene expression was investigated in cells with different p53 status in normoxia-and hypoxia-mimicking conditions. Putative hypoxia response elements (HREs) were identified in the regulatory region of SCO2 and TIGAR gene promoters. Chromatin immunoprecipitation experiments suggested that HIF-1 was recruited to the putative HREs present in the SCO2 and TIGAR promoters in a cell type-dependent manner. Transcriptional assays endorsed the notion that PCAF may be involved in the determination of the SCO2 and TIGAR cellular levels, thereby, regulating cellular energy metabolism, a view supported by assays measuring lactic acid production and oxygen consumption in cells ectopically expressing PCAF. The present study identified HIF-1 as a potential regulator of SCO2 and TIGAR gene expression. Furthermore, evidence to suggest that PCAF is involved in the regulation of cellular energy production pathways in hypoxia-mimicking conditions is presented. This effect of PCAF is exerted by orchestrating differential recruitment of HIF-1α and p53 to the promoter of TIGAR and/or SCO2 genes, thereby, tailoring physiological needs and environmental conditions to SCO2 and TIGAR gene expression.

Cardioprotective effect of miRNA-22 on hypoxia/reoxygenation induced cardiomyocyte injury in neonatal rats

“…CBP as an important transcription co-activator not only regulates transcriptional factor DNA binding, but also can intervene their transcriptional activity (Goodman et al, 2000;Arany et al, 1994). At last, many various transcriptional factors competition for limiting amounts of CBP (Zhao et al, 2011;Ramos et al, 2010;Tsai et al, 2008;Du et al, 2014;Rajendran et al, 2013), which is still an important research problem.…”

Cytochrome P450 2E1 (CYP2E1) regulates the response to oxidative stress and migration of breast cancer cells

“…The pro-oxidant effects of p53 are mediated by another set of its target genes such as the p53-induced gene 3 (PIG3) [54] the p66Shc [55] and the Bcl2 family members bax and PUMA [50,56]. The mechanisms directing the p53 target selectivity to antioxidant or pro-oxidant transcriptional target genes, thereby determining the final outcome of the p53-mediated cellular redox state, include posttranslational modifications and recognition of specific DNA binding sites in the regulatory regions of the promoters of pro-oxidant subsets of genes by domains different than the p53 DNA binding domain (proline-rich domain) [50,54,57] and the affinity of p53 binding to the promoter of its diverse transcriptional targets follows a hierarchical order that is dependent on the type of stress [22,58,59]. In these terms, the amount of CYP2E1-mediated ROS generation could induce either antioxidant or pro-oxidant p53 outcomes in a tissue and cell-type-dependent manner.…”

Therapeutic Targeting of the Warburg Effect in Pancreatic Cancer Relies on an Absence of p53 Function

“…Human PGK1 and murine β-actin were used as housekeeping genes. The primer sequences used for huTIGAR are Forward 5 ′ -ATGGAATTTTGGAGAGAA-3 ′ Reverse 5 ′ -CCATGGCCCTCAGCTCAC-3 ′ (28). Relative expression of the mRNA was estimated using the 2 −ΔΔ CT method.…”