Immune checkpoint inhibitors (ICIs), a class of drugs able to block immune suppressive pathways in order to prime an anticancer immunity, revolutionized standard of care in many solid tumors, including melanoma, non small cell lung cancer (NSCLC), recurrent/metastatic head and neck squamous cell carcinoma (R/M-HNSCC) and renal cell carcinoma (RCC) .
In the last decade, the relationship between immunology and oncology has been thoroughly clarified; the immune system is the guardian of our health and organism integrity and is able to identify and destroy arising tumor cells and to function as a primary defense against cancer. Despite the exciting results, only a small subset of patients benefits from ICIS. The main goal of current scientific research is to identify possible predictive biomarker of response to immunotherapy in order to optimize and maximize the outcome of patients with HNSCC.
The last effort on the identification of biomarkers failed to demonstrate that a single biomarker can optimally select patients resistant/ responder to immunotherapy.
It's reasonable to imagine that a comprehensive profile, rather than a single biomarker, could be necessary to better select patient.
In the future, it may be possible to individualize therapeutic strategies based on these biomarkers. Therefore, the aim of this study is to realize a comprehensive cancer evaluation including clinical patients features, genomic characteristics, microbiome/microbiota, circulating and tissue immunological parameters in order to identify predictive biomarkers of response or resistance to immunotherapy.
In the context of multiple treatment possibilities, the identification of predictive markers of response and toxicity is a challenging approach for drug selection in order to obtain the best clinical benefit while minimizing the side effects for each patient.
It's reasonable to imagine that a comprehensive profile, rather than a single biomarker, could be necessary to better select patient.
In the future, it may be possible to individualize therapeutic strategies based on these biomarkers. Therefore, the aim of this study is to realize a comprehensive cancer evaluation through network analysis approach, including clinical patients features, genomic characteristics, microbiome evaluation, circulating and tissue immunological parameters in order to identify predictive biomarkers of response or resistance to immunotherapy.