Kinetic Evaluation of Cell Membrane Hydrolysis during Apoptosis by Human Isoforms of Secretory Phospholipase A2*

Some isoforms of secretory phospholipase A2 (sPLA2) distinguish between healthy and damaged or apoptotic cells. This distinction reflects differences in membrane physical properties. Because various sPLA2 isoforms respond differently to properties of artificial membranes such as surface charge, they should also behave differently as these properties evolve during a dynamic physiological process such as apoptosis. To test this idea, S49 lymphoma cell death was induced by glucocorticoid (6–48 h) or calcium ionophore. Rates of membrane hydrolysis catalyzed by various concentrations of snake venom and human groups IIa, V, and X sPLA2 were compared after each treatment condition. The data were analyzed using a model that evaluates the adsorption of enzyme to the membrane surface and subsequent binding of substrate to the active site. Results were compared temporally to changes in membrane biophysics and composition. Under control conditions, membrane hydrolysis was confined to the few unhealthy cells present in each sample. Increased hydrolysis during apoptosis and necrosis appeared to reflect substrate access to adsorbed enzyme for the snake venom and group X isoforms corresponding to weakened lipid-lipid interactions in the membrane. In contrast, apoptosis promoted initial adsorption of human groups V and IIa concurrent with phosphatidylserine exposure on the membrane surface. However, this observation was inadequate to explain the behavior of the groups V and IIa enzymes toward necrotic cells where hydrolysis was reduced or absent. Thus, a combination of changes in cell membrane properties during apoptosis and necrosis capacitates the cell for hydrolysis differently by each isoform

RNF43 mutations predict response to anti-BRAF/EGFR combinatory therapies in BRAFV600E metastatic colorectal cancer

Anti-BRAF/EGFR therapy was recently approved for the treatment of metastatic BRAFV600E colorectal cancer (mCRCBRAF-V600E). However, a large fraction of patients do not respond, underscoring the need to identify molecular determinants of treatment response. Using whole-exome sequencing in a discovery cohort of patients with mCRCBRAF-V600E treated with anti-BRAF/EGFR therapy, we found that inactivating mutations in RNF43, a negative regulator of WNT, predict improved response rates and survival outcomes in patients with microsatellite-stable (MSS) tumors. Analysis of an independent validation cohort confirmed the relevance of RNF43 mutations to predicting clinical benefit (72.7% versus 30.8%; P = 0.03), as well as longer progression-free survival (hazard ratio (HR), 0.30; 95% confidence interval (CI), 0.12-0.75; P = 0.01) and overall survival (HR, 0.26; 95% CI, 0.10-0.71; P = 0.008), in patients with MSS-RNF43mutated versus MSS-RNF43wild-type tumors. Microsatellite-instable tumors invariably carried a wild-type-like RNF43 genotype encoding p.G659fs and presented an intermediate response profile. We found no association of RNF43 mutations with patient outcomes in a control cohort of patients with MSS-mCRCBRAF-V600E tumors not exposed to anti-BRAF targeted therapies. Overall, our findings suggest a cross-talk between the MAPK and WNT pathways that may modulate the antitumor activity of anti-BRAF/EGFR therapy and uncover predictive biomarkers to optimize the clinical management of these patients. The presence of inactivating mutations in RNF43, a negative regulator of WNT, in tumor cells predicts improved response rates and survival outcomes in patients with metastatic BRAF(V600E) colorectal cancer treated with anti-BRAF/EGFR therapy

Interrogating open issues in cancer precision medicine with patient-derived xenografts.

Patient-derived xenografts (PDXs) have emerged as an important platform to elucidate new treatments and biomarkers in oncology. PDX models are used to address clinically relevant questions, including the contribution of tumour heterogeneity to therapeutic responsiveness, the patterns of cancer evolutionary dynamics during tumour progression and under drug pressure, and the mechanisms of resistance to treatment. The ability of PDX models to predict clinical outcomes is being improved through mouse humanization strategies and the implementation of co-clinical trials, within which patients and PDXs reciprocally inform therapeutic decisions. This Opinion article discusses aspects of PDX modelling that are relevant to these questions and highlights the merits of shared PDX resources to advance cancer medicine from the perspective of EurOPDX, an international initiative devoted to PDX-based research

Interrogating open issues in cancer medicine with patient-derived xenografts

This corrects the article DOI: 10.1038/nrc.2016.14