GRAMMY - InteGRAtive analysis of tuMor, Microenvironment, immunitY and patient expectation for personalized response prediction in Gastric Cancer

Chemotherapy combined with surgery represents the standard of care for stages II-III gastric cancer, but the efficacy of such treatments is still limited for many patients. As the disease shows a high level of molecular heterogenity, identifying novel sensitising markers offers hope to better stratify patients and achieve a better outcome for them. Additionally, a deeper understanding of the role of psychological factors on prognosis can also improve patient survival.

Gastric cancer (GC) is a complex disease that represents the fifth most common malignancy in the world and the third leading cause of cancer death in both sexes. GC shows a high level of heterogeneity as well as a marked gender difference in incidence, GC affecting twice as many men as women. Chemotherapy (Ct) combined with surgery represents the standard of care for stages II-III GC, but the efficacy of such treatments is still limited for many patients. It is mandatory to develop novel therapeutic strategies aimed at identifying predictive markers, as well as deciphering the impact of the psychological-social and cultural environment of each patient on the outcome. Our consortium is endowed with a strong complementarity potential to develop multiscale approaches aimed at characterizing the cellular, molecular and inflammatory components that specify each GC, with optimized methodologies. All partners operate in Clinical Institutes with a strong specificity in treating GC, and are used to developing translational approaches. The personalized medicine project design we propose will aim at translating the acquired laboratory data into an individualized treatment tool for improving patient stratification. We also advocate for the fact that communication style according to patients' condition and physician-patient interaction can influence therapy response, and distress and coping styles can lower therapeutic compliance. Moreover, we will include interviews of patients to identify the levels of understanding of each patient of his disease and to foresee compliance to treatment. This integration of such separate levels of information obtained is specifically challenging, while extremely promising, towards identification of the putative links between disease-specific cellular and molecular characteristics, patient perception and prognosis. Finally, specific ICT tools will be developed to integrate data from all the various sources, from biology to social.