Objective
Metabolism generates vast quantities of acid, which exerts broad-spectrum biological effects because protein protonation is a powerful post-translational modification. Regulation of intracellular pH (pHi) is therefore a homeostatic priority, but carefully orchestrated proton dynamics are a versatile signal.
Extracellular acidity is an established chemical signature of tumours and has recently been proposed to convey a signal that shapes the phenotypic landscape of cancer. Cancers genetic instability yields diversity in acid handling and signalling, forming a substrate for selection under acid-stress. This is a plausible mechanism for disease progression and an analogy can be drawn to experimentally-verified hypoxic selection.
Current models of acid handling in cancer are, however, based on population-averages of observations made at the cell level. This fails to appreciate diversity and the complexity inherent in tissues. We will produce a more complete understanding of acid handling that accounts for diffusive transport across tissue compartments and the role of the tumour stroma. A systems-approach of characterising pH-regulatory processes cell-by-cell will identify which components are liable to vary, and thus are a substrate for acid-driven somatic evolution.
The long-term effects of proton signals on gene expression have not been tested, despite evidence for proton-sensing transcription factors. To address the mechanism for adaptation to acid-stress, proton-sensing transcription factors will be characterised from studies of gene expression under chemically and optogenetically operated pH stimuli.
The definition of a cells fitness to survive at a particular microenvironment pH and its relationship with stemness remain unclear. Phenotyping pHi-gated subpopulations in terms of growth, stemness and tumourigenicity will define pH-fitness and its role in aggressiveness. In evolving to survive metabolism, cancer cells may acquire the ability to thrive in new niches.
Fields of science (EuroSciVoc)
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques.
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques.
- natural sciencesbiological sciencesbiochemistrybiomoleculesproteins
- medical and health sciencesclinical medicineoncology
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Keywords
Programme(s)
Funding Scheme
ERC-COG - Consolidator GrantHost institution
OX1 2JD Oxford
United Kingdom