Our goal is to find predictive biomarkers of response to immune check point blockade and to decipher mechanisms of resistance to immunotherapy in the tumor microenvironment (TME) and in the blood. These questions are currently addressed in several cancer types, with a focus on clear cell renal cell cancer and in soft tissue sarcoma, by using a combination of multiplex immunohistochemistry, RNAseq, WES, TCRseq, neoantigen prediction and non invasive approaches. Bioinformatics tools to identify immune and stromal cell signatures in the TME are developed in human and in mouse (MCP-counter).
Our current main themes are :
1-Tertiary lymphoid structures, B cells and immune classes, predictive markers of response to immunotherapy
We are addressing these questions in prospective clinical trials of treatment with Pembroluzimab (anti-PD1) of patients with soft tissue sarcoma where patients are selected for the presence of TLS in the TME, in a phase II BIOmarker driven trial with Nivolumab (N) and Ipilimumab or VEGFR tyrosine Kinase inhibitor where naïve metastatic ccRCC patients are selected according to the molecular classes of their tumors (BIOniKK) and in a Phase II safety trial of nivolumab in patients with metastatic ccRCC who have progressed during or after prior systemic anti-angiogenic regimen.
2- Cellular markers of response to immunotherapy with ICBs
The use of non-invasive patient selection and monitoring measures is the next essential step in the development of immunotherapy. Bioinformatic tools for the identification and the analyses of immune blood subpopulations by immunofluorescence (12 markers) and by mass spectrometry (45 markers, La Pitié platform) are being developed to establish the validity of a blood immune population to predict the response or toxicity of a treatment in clear cell renal cell cancer in patients enrolled in the trials described above.
- Wolf H Fridman Professor emeritus
- Catherine Sautès-Fridman, Professor emeritus
- Cheng Ming Sun, CR INSERM