Although the survivorship for breast cancer patients continues to improve (Yabroff et al 2012) due to in part to the increase in the ageing population and improved detection and treatment options and specificity. Increase in survivors also increases the economic burden as the length of time each patient receives treatment increases. The enormous economic burden posed by breast cancer alone, estimated at 28 billion Euros (27% of which is due to loss in productivity with the majority 46% from medical costs) is expected to increase significantly due to aging of the population and improvements in survival and diagnosis.
The treatment plan (surgery, radio/chemo or drug therapy) for breast cancer patients is based on the individual cases; based on histology analysis, physical examination, tumour grade, stage, levels of metastasis, and patient age/overall health and personal preferences. The discovery of new powerful predictive biomarkers and targets for improved treatment selection is of great importance to combat the ever- increasing rates of disease, economic and emotional burden. Not only will a selective treatment improve patient care, avoiding unnecessarily and costly treatments unlikely to have a favourable outcome, but targeted treatment with an increased likelihood of success would also reduce the economic burden for health care providers and reducing the decrease in economic costs due to loss of productivity.
Since 2014 when the first PARP1 inhibitor, olaparib (Lynparza) was approved for the treatment of ovarian cancer, initial clinical efforts focused on the exploitation of inducing synthetic lethality of cancer cells. However single-agent PARP1 inhibition has not been as successful as initially hypothesised, turning the focus now to the combinatorial treatment of disease with PARP1 with over 3000 patients enrolled in over 20 distinct clinical trials using PARP1 combination therapy in 2016 alone (Drean et al 2016). Combinatorial treatment in general has many advantages over single-agents; different mechanisms of action, varied normal tissue toxicity, reduced patient dosing therefore improved patient care.
We and other labs have spent significant effort to understand the complex mechanisms that control of cancer cell growth. We recently discovered a novel mechanism which feeds cancer cell growth where in the energy source for the cell: ATP is generated downstream of PARP1, by the enzyme NUDIX5. This process is exploited by cancer cells for growth and proliferation and hence provides a novel target for drug discovery. (Wright et al 2016).
The inhibition of NUDIX5 in combination with PARP1 has the potential to be superior to existing treatments for breast cancer and other indications given the potential cancer cell specificity of our NUDIX5 compound. Although NUDIX5 is expressed in all cells of the body, our NUDIX5 inhibitor compounds were identified using an in-silico screen for a unique active NUDIX5 3D structure, which we hypothesise is the form present in cancer cells and would therefore reduce potential side effects.
Research and clinical trials related to PARP1 combinatorial treatment for cancer is progressing rapidly. However, we have a competitive advantage over the current rationale. Current strategies aim to exploit one of the two main functions of PARP1; DNA damage or transcriptional regulation. Using combinations of drugs acting up or downstream of PARP1 in either one of these processes.
We have seen that not only is NUDIX5 required for transcriptional regulation mediated by PARP1 but also for cancer cell survival upon DNA damage (Wright et al Science 2016). Thus, combining inhibitors of activated NUDIX5 and PARP1 would interfere with both key pathways, and we have strong evidence that this would potentiate PARP1 inhibitors, reducing cancer cell growth and potential side effects. Together with the rise in PARP1 inhibitors, we consider the developers of such compounds not as competitors but rather as potential licensing partners.
Following the successful completion of this research project we have been able to;
1) Develop a novel hit specific compound for the inhibition of NUDT5 in cancer cells, validated and tested in vitro and in cellulo using 3D breast cancer cell cultures.
2) Validate in vivo the oncogenic signature driven by NUDT5.
3) Generate a predictive mechanism of action for aggressive cancer using artificial neural networks which may provide insight for future targets for therapeutics.
4) Validate the potential use of a NUDT5 antibody as a biomarker in cancer patient tissues.
5) Raised additional funding to further support the project and move one step closer to therapeutic use.
(Yabroff et al 2011 American Association for Cancer Research 20:2006-14.)
(Drean et al 2016 Critical Reviews in Oncology 108: 73-85.)
(Wright et al 2016 Science 352: 1221-5).
