Precision medicine is considered to be one of the major issues in patient care. A lot of research has already proven itself with the implementation of targeted therapies including immunotherapies offering patients improved response and survival rates. But despite these major therapeutic advances, resistance to anti-cancer treatment is a major obstacle in the care of patients. Indeed, to date, many patients die of cancer, 9.6 million deaths worldwide in 2018. Nowadays, improving understanding of the mechanisms of resistance of cancer cells to anti-tumor treatments is therefore a major issue. The great diversity of molecular mechanisms involved in the phenomena of resistance to treatment, whether intrinsic (de novo, or primary) or acquired (secondary), constitutes a real therapeutic challenge. Indeed, a better understanding of the mechanisms of resistance would make it possible to explore new therapeutic strategies making it possible to circumvent these phenomena of escape in different types of cancer. It is in this context that the OncoSNIPE project was developed. The objective of this project is to identify early and / or late markers of resistance to treatment in 3 different pathologies concerned with resistance issues : triple negative breast cancer or lum B or locally advanced or metastatic non- small-cell lung cancer or pancreatic cancer. In this project, in order to best cover the diversity of mechanisms involved in these resistances, the investigators propose a multidisciplinary approach with clinical, genomic, transcriptomic and immunological dimensions of the pathology through the data collected from 600 patients (200 for each pathology) for 4 years.~The patient populations targeted in this study have one common thing: rapid progression of their pathology, making it possible to obtain models for evaluating markers of early and / or late responses over the period of follow-up of 2-year post-inclusion patients, and thus provide the information necessary to understand the resistance mechanisms.~To explore the phenomena of resistance, during the therapeutic response and / or the progression of the pathology, the investigators will used a multidisciplinary approach including high-throughput sequencing (Exome-seq and RNAseq) and immunological profil by ELISA . Patients will have long-term follow-up with different biological samples, at baseline (blood and biopsy) and at each tumoral evaluation or tumoral progression evaluated by medical imaging.
Precision medicine is considered to be one of the major issues in patient care. A lot of research has already proven itself with the implementation of targeted therapies including immunotherapies offering patients improved response and survival rates. But despite these major therapeutic advances, resistance to anti-cancer treatment is a major obstacle in the care of patients. Indeed, to date, many patients die of cancer, 9.6 million deaths worldwide in 2018. Nowadays, improving understanding of the mechanisms of resistance of cancer cells to anti-tumor treatments is therefore a major issue. The great diversity of molecular mechanisms involved in the phenomena of resistance to treatment, whether intrinsic (de novo, or primary) or acquired (secondary), constitutes a real therapeutic challenge. Indeed, a better understanding of the mechanisms of resistance would make it possible to explore new therapeutic strategies making it possible to circumvent these phenomena of escape in different types of cancer. It is in this context that the OncoSNIPE project was developed. The objective of this project is to identify early and / or late markers of resistance to treatment in 3 different pathologies concerned with resistance issues: triple negative breast cancer or Lum B or locally advanced or metastatic non -small-cell lung cancer or pancreatic cancer. In this project, in order to best cover the diversity of mechanisms involved in these resistances, the investigators propose a multidisciplinary approach with clinical, genomic, transcriptomic and immunological dimensions of the pathology through the data collected from 600 patients (200 for each pathology) for 4 years