Biomarkers of the Proinflammatory Response and Elements of Immune Suppression

$272,582P50FY2015CANIH

University Of Pittsburgh At Pittsburgh, Pittsburgh PA

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Abstract

Project 1 builds on our preliminary data and recent reports in the literature that have identified a series of biomarkers of a pro-inflammatory immune response and of immunosuppression in both tumor tissue and in circulating blood that have promising therapeutic predictive and disease prognostic value in melanoma patients treated with immunotherapy. These will be simultaneoulsy evaluated as part of E1609 trial testing adjuvant ipilimumab at high dose and standard dose versus IFN? in patients with operable stage IIIB/C and M1a/b melanoma. This project will have 3 aims to be tested within each of the E1609 trial cohorts: Aim 1: Circulation. (1a) Circulating cellular populations: test the hypothesis that baseline and/or early on-treatment IFNg+CD4+ and IFNg+CD8+ antigen specific T-cell immunity as well as specific host suppressor elements (defined populations of regulatory T cells and myeloid-derived suppressor cells) correlate with clinical outcome (RFS and OS), (lb) Circulating serum biomarkers: test the hypothesis that baseline and/or earty on-treatment pro-inflammatory cytokine and chemokine profiles correlate with clinical outcome. Aim 2: Tumor and tumor microenvironment: First, test the hypothesis that a pretreatment, pro-inflammatory, tumor microenvironment (high baseline expression levels of immune-related genes) correlates with clinical outcome (RFS and OS). As secondary sub-aims, we will test the association of the tumor mutational status (BRAF, NRAS and wild-type status for both) and clinical outcome. We will also assess the predictive value of the methylation levels of immune-related genes. Aim 3: Based on the common systems biology, an overall model analysis will be developed to link markers of interest in Aims 1 and 2 (linking significant markers in the circulation with those in the tumor microenvironment) where we hypothesize that a pro-inflammatory therapeutically predictive signature(s) of biomarkers will be identified and validated within each of the trial arms. We expect overlapping predictive models for ipilimumab and HDI based on the common systems biology.

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