Integrative analysis of multi-platform reverse-phase protein array data for the pharmacodynamic assessment of response to targeted therapies.

Reverse-phase protein array (RPPA) technology uses panels of high-specificity antibodies to measure proteins and protein post-translational modifications in cells and tissues. The approach offers sensitive and precise quantification of large numbers of samples and has thus found applications in the analysis of clinical and pre-clinical samples. For effective integration into drug development and clinical practice, robust assays with consistent results are essential. Leveraging a collaborative RPPA model, we set out to assess the variability between three different RPPA platforms using distinct instrument set-ups and workflows. Employing multiple RPPA-based approaches operated across distinct laboratories, we characterised a range of human breast cancer cells and their protein-level responses to two clinically relevant cancer drugs. We integrated multi-platform RPPA data and used unsupervised learning to identify protein expression and phosphorylation signatures that were not dependent on RPPA platform and analysis workflow. Our findings indicate that proteomic analyses of cancer cell lines using different RPPA platforms can identify concordant profiles of response to pharmacological inhibition, including when using different antibodies to measure the same target antigens. These results highlight the robustness and the reproducibility of RPPA technology and its capacity to identify protein markers of disease or response to therapy.

Genetic markers and phosphoprotein forms of beta-catenin pß-Cat552 and pß-Cat675 are prognostic biomarkers of cervical cancer.

BACKGROUND: Cervical cancer (CC) remains a leading cause of gynaecological cancer-related mortality world wide and constitutes the third most common malignancy in women. The RAIDs consortium (http://www.raids-fp7.eu/) conducted a prospective European study [BioRAIDs (NCT02428842)] with the objective to stratify CC patients for innovative treatments. A "metagene" of genomic markers in the PI3K pathway and epigenetic regulators had been previously associated with poor outcome [2]. METHODS: To detect new, more specific, targets for treatment of patients who resist standard chemo-radiation, a high-dimensional Cox model was applied to define dominant molecular variants, copy number variations, and reverse phase protein arrays (RPPA). FINDINGS: Survival analysis on 89 patients with all omics data available, suggested loss-of-function (LOF) or activating molecular alterations in nine genes to be candidate biomarkers for worse prognosis in patients treated by chemo-radiation while LOF of ATRX, MED13 as well as CASP8 were associated with better prognosis. When protein expression data by RPPA were factored in, the supposedly low molecular weight and nuclear form, of beta-catenin, phosphorylated in Ser552 (pß-Cat552), ranked highest for good prognosis, while pß-Cat675 was associated with worse prognosis. INTERPRETATION: These findings call for molecularly targeted treatments involving p53, Wnt pathway, PI3K pathway, and epigenetic regulator genes. Pß-Cat552 and pß-Cat675 may be useful biomarkers to predict outcome to chemo-radiation, which targets the DNA repair axis. FUNDING: European Union's Seventh Program for research, technological development and demonstration (agreement N°304,810), the Fondation ARC pour la recherche contre le cancer.

Assessment of signaling pathway inhibitors and identification of predictive biomarkers in malignant pleural mesothelioma.

OBJECTIVES: Malignant pleural mesothelioma (MPM) is an aggressive tumor with limited therapeutic options, requiring the development of efficient targeted therapies based on molecular phenotype of the tumor and to identify predictive biomarkers of the response. MATERIALS AND METHODS: The effect of inhibitors was investigated by cell viability assessment on primary MPM cell lines established in our laboratory from patient tumors, well characterized at the molecular level. Effects on apoptosis, cell proliferation and viability on MPM growing in multicellular spheroid were also assessed for verteporfin. Gene and protein expression, and gene knockdown by RNA interference were used to define mechanism of inhibition and specific predictive biomarkers. RESULTS: Anti-tumor effect of eight major signaling pathways inhibitors involved in mesothelial carcinogenesis was investigated. Three inhibitors were more efficient than cisplatin, the drug used as first-line chemotherapy in patients with MPM: verteporfin, a putative YAP inhibitor, defactinib, a FAK inhibitor and NSC668394, an Ezrin inhibitor. Verteporfin, the most efficient inhibitor, induced cell proliferation arrest and cell death, and is effective on 3D spheroid multicellular model. Verteporfin sensitivity was YAP-independent and related to molecular classification of the tumors. Biomarkers based on gene expression were identified to predict accurately sensitivity to these three inhibitors. CONCLUSION: Our study shows that drug screening on well-characterized MPM cells allows for the identification of novel potential therapeutic strategies and defining specific biomarkers predictive of the drug response.