Exploring PARP biology and therapy response via metabolic flux analysis and a novel chemical proteomics workflow

Poly-ADP-ribose polymerases (PARPs) are NAD-dependent enzymes catalysing the formation
of ADP-ribose modifications on proteins and are critical for DNA damage response, chromatin
remodelling and with emerging roles in RNA splicing (Matveeva et al., 2016). Across the 17
PARPs currently identified we lack a detailed understanding of the subset of the proteome
preferentially modified by each enzyme partly due to the analytical challenge of defining the global
PARylome. PARP (I/II/III) inhibitors are synthetically lethal in HR-deficient cancer and are becoming
an important maintenance therapy in ovarian cancer. The efficacy of PARP inhibitors is closely linked
to the extent to which PARP is 'trapped' on damaged DNA (Murai et al., 2012). The NAD cofactor is
essential for PARP activity and removal of trapped PARP by autoPARylation; however the impact
of metabolic reprogramming in cancer cells and NAD availability on the PARylome or PARP
inhibitor response has not been systematically explored



We (Keun) have observed that KRAS mutant ovarian cancer cells are selectively sensitive to NAD
depletion via chemical inhibition (FK866) of the NAD salvage enzyme NAMPT (Figure 1). This is
consistent with KRAS-driven metabolic reprogramming leading to a classic Warburg state with a high
requirement for both NAD+ in the cytosol to maintain a high glycolytic rate and NADPH for
biosynthesis and antioxidant protection. We hypothesise that extra demands on NAD supply in
KRAS mutant ovarian cancer cells alter the global PARylome, and subsequently the downstream
function of PARylated proteins.






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Using a novel quantitative chemical proteomics workflow involving metabolic incorporation of multiple
clickable NAD+ precursors combined with TMT isobaric tagging developed in the DiMaggio lab (in
review, Nature Chemical Biology), we unexpectedly observed that RNA splicing factors showed the
greatest reduction in PARylation with PARP inhibition in breast cancer cells (Figure 2). Therefore we
also hypothesise that NAD metabolism may have a previously uncharacterised role in
regulating function of the spliceosome via PARP activity. This hypothesis is supported by a
recent CRISPR screen that revealed ribonucleases are novel synthetically lethal determinants of
PARP inhibitor response (Zimmermann et al., 2018). In this study a total of 73 high-confidence genes
were identified across three cell lines that when mutated resulted in increased sensitivity to PARP
inhibitors. A number of RNA splicing factors, such as DDX46 and SRSF11, were among these genes
but not investigated further. Notably, DDX46 and SRSF11 were also identified by our chemical
proteomics workflow as one of the most de-PARylated proteins after treatment with PARP inhibitors
in MDA-MB-231 cells .

Addressing UK skills demand: The most important impact of the CDT will be to train a new generation of Chemical Biology PhD graduates (~80) to be future leaders of enterprise, molecular technology innovation and translation for academia and industry. They will be able to embrace the life science's industrialisation thereby filling a vital skills gap in UK industry. These students will be able to bridge the divide between academia/industry and development/application across the physical/mathematical sciences and life sciences, as well as the human-machine interfaces. The technology programme of the CDT will empower our students as serial inventors, not reliant on commercial solutions.
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These advances will make a significant contribution to innovation in UK industry, with a 5-10 year timeframe for commercial realisation. e.g. These tools will facilitate the identification of illness in its early stages, minimising permanent damage (10 yrs) and reducing associated healthcare costs. In the context of drug discovery, the ability to fuse the power of AI with molecular technologies that provide insight into the molecular mechanisms of disease, target and biomarker validation and testing for side effects of candidates will radically transform productivity (5-10 yrs). Developments in automation and rapid prototyping will reduce the barrier to entry for new start-ups and turn biology into an information technology driven by data, computation and high-throughput robotics. Technologies such as integrated single cell analysis and label free molecular tracking will be exploitable for clinical diagnostics and drug discovery on shorter time scales (ca.3-5 yrs).
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