Immuno-Transcriptomic Profiling of Blood and Tumor Tissue Identifies Gene Signatures Associated with Immunotherapy Response in Metastatic Bladder Cancer

Abstract

'Sara S. Fonseca Costa' 'Laura Ciarloni' 'Marco Ongaro' 'Hana Zdimerova' 'Marine M. Leblond' 'Sahar Hosseinian Ehrensberger' 'Pedro Romero' 'Grégory Verdeil' 'Hiroki Ide'] Simple Summary Muscle-invasive bladder cancer (MIBC) accounts for 25% of bladder cancer cases. Despite the broader usage of immune checkpoint blockades targeting the PD-1/PD-L1 axis, the response rate and survival of patients remain low for this disease. Redirecting these patients swiftly toward alternative therapeutic strategies upon immunotherapy failure should be a priority. So far, no marker allows the early outcome of the treatment to be precisely determined. The aim of our study was to determine to what extent a whole blood transcriptomic analysis could reflect the efficiency of immunotherapy in a well-established MIBC genetic mouse model. We report that it is a valuable approach to predict the response to immunotherapy in our model. Abstract Blood-based biomarkers represent ideal candidates for the development of non-invasive immuno-oncology-based assays. However, to date, no blood biomarker has been validated to predict clinical responses to immunotherapy. In this study, we used next-generation sequencing (RNAseq) on bulk RNA extracted from whole blood and tumor samples in a pre-clinical MIBC mouse model. We aimed to identify biomarkers associated with immunotherapy response and assess the potential application of simple non-invasive blood biomarkers as a therapeutic decision-making assay compared to tissue-based biomarkers. We established that circulating immune cells and the tumor microenvironment (TME) display highly organ-specific transcriptional responses to ICIs. Interestingly, in both, a common lymphocytic activation signature can be identified associated with the efficient response to immunotherapy, including a blood-specific CD8+ T cell activation/proliferation signature which predicts the immunotherapy response.