Development of a proteomics-based predictor for targeted use of IAP antagonists in colorectal cancer
Session type: Poster / e-Poster / Silent Theatre session
Resistance to apoptosis is a classical Hallmark of Cancer, which can manifest clinically as lack of response to chemotherapeutic agents such as 5-FU. Cancer cells can acquire resistance through increasing their expression of (and therefore dependence on) anti-apoptotic proteins such as Inhibitor of Apoptosis Proteins (IAPs), making such proteins attractive therapeutic targets.
In order to develop an approach for predicting response to IAP antagonist therapy(TL32711), we quantified the basal expression of “IAP interactome” proteins in a panel of colorectal cancer cell lines. Cell death induction in response to TL32711 alone and in combination with standard-of-care chemotherapy(5-FU+Oxaliplatin–“FOLFOX”) was assessed by high content microscopy. The impact of TNFα was also assessed to mimic a pro-inflammatory tumour microenvironment. Selected cell lines were aligned to CRIS and CMS transcriptomic subgroups.
No significant correlations were observed between apoptosis protein expression and molecular subgroup, and no significant correlations between CRIS or CMS subgroups and response to TL32711 (-/+TNFα). However, CRIS-D and E cell lines responded well to FOLFOX+TL32711 co-treatment in the presence of TNFα. Although no correlations were observed between expression of any individual apoptotic protein and response to TL32711, we identified that the ratio of caspase-8, and its regulator, FLIP(L), was significantly correlated with sensitivity to TL32711+TNFα(r2= 0.46, p=0.02). Expression of no individual protein correlated with response to FOLFOX alone; however, the level of apoptosis induced in response to FOLFOX in combination with TL32711+TNFα correlated with both cIAP1(r2= 0.61, p=0.003) and FLIP(L)(r2= 0.46, p=0.02) expression. Building on these promising results, predictive algorithms are currently being developed incorporating expression of intrinsic apoptosis signalling proteins to more accurately predict response to IAP antagonist therapy.
Our initial work focussing on the IAP interactome suggests that it will be possible to develop a predictive tool to stratify colorectal cancer patients into groups likely to respond to IAP antagonist-based therapy.