Abstract 4574: Combining multimodal biomarkers as an immunogram to guide immunotherapy use: A proof of concept

Our recent understanding of the immune contribution to fight cancer has deeply modified the standard of care of cancer patients. As an example, immunotherapies by immune checkpoint inhibitors (ICI) anti-PD1/PDL1 are now approved in several cancer indications, such as Non-Small Cell Lung Cancers or melanoma. However, ICI are less effective for other high incidence indications like colorectal cancer (CRC). Here, the heterogeneity as well as the relatively low degree of patient response to those immunotherapies have highlighted that factors, present in the tumor microenvironment (TME), may limit or boost the efficacy of treatment. In this context, the comprehensive assessment of these factors could be key to stratify patients and allow the selection of the optimal treatment. In order to help clinical researchers and biopharmaceutical companies to measure the immune contribution to drug efficacy, HalioDx has developed the Cancer Immunogram, a solution based on Blank CU et al. Science (2016). Our multi-parameter approach encompassing a unique range of immune scoring assays is based on the analysis and the understanding of the immune contexture of tumors and offers a personalized and dynamic “fingerprint” of tumor-immune system interaction. Here, we provide a Proof of Concept for the Cancer Immunogram in the context of CRC by combining the following technologies and biomarkers: Tumor Mutational Burden (Tumour foreignness), DNA mismatch-repair deficiency (MSI), TCR Sequencing (T Cell Clonality), Immunoscore® Colon (Immune Cell Infiltration), Immunosign® (Tumor Sensitivity to Immune Effectors), Halioseek® PDL1/CD8, Brightplex T-Cell Exhaustion Panel (Immune Checkpoints) and Brightplex MDSC Panel and Treg detection (Immune Suppression). We show that the Cancer Immunogram allows to identify patient specific patterns which might improve the prediction of the response to therapy. We believe that the Cancer Immunogram will help researchers and clinicians to personalise treatments in order to improve patients’ outcomes and response to cancer treatment. Citation Format: Thomas Sbarrato, Lucie Sudre, Laurent Vanhille, Pernelle Outters, Mihaela Angelova, Bernhard Mlecnik, Angela Vasaturo, Gabriela Bindea, Tessa Fredriksen, Lucie Lafontaine, Daniela Bruni, Jerome Galon, Jacques Fieschi. Combining multimodal biomarkers as an immunogram to guide immunotherapy use: A proof of concept [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2019; 2019 Mar 29-Apr 3; Atlanta, GA. Philadelphia (PA): AACR; Cancer Res 2019;79(13 Suppl):Abstract nr 4574.