Clinical Research Directory

Biomarkers in Immunotherapy of Melanoma

Background: Immunotherapy has been successful in treating advanced melanoma, but a large proportion of patients do not respond to the treatment with immune checkpoint inhibitors (ICIs). Preclinical and small cohort studies suggest biomarkers from the primary tumor, stool and body fluids as markers of response. This prospective study will evaluate gastrointestinal microbiome (bacterial spices and virome) composition and exosomal mRNA expression of PD-L1 and IFNγ correlation with radiological response rates to ICIs treatment of advanced melanoma patients. Methods: Patients treated with immune checkpoint inhibitors as a first line treatment for metastatic melanoma are recruted to the study. Stool samples are submitted before the start of treatment, at the 12 (+/-2) week and 28 (+/-4) week, and at the event ( such as, suspected disease progression/hyperprogressio, immune related adverse event (irAE), etc). Peripheral venous blood samples are taken additionaly at the same time points for cytologic and molecular tests. Histological material from the tumor tissue is obtained before the start of immunotherapy treatment. Primary objectives are to determine whether human gastrointestinal microbiome (bacterial and viral) and exosomal mRNA expression of PD-L1 and IFNγ predict response to treatment with PD-1 and CTLA-4 inhibitors and are associated with occurrence of irAE in patients with metastatic melanoma at different time points. Response is evaluated radiologically with imaging methods in accordance with the irRECIST criteria. Conclussion: Despite the great success of the treatment of metastatic melanoma with immunotherapy, there remains a significant proportion of patients who do not respond to treatment or who develop severe adverse events during treatment. Identification of novel predictive and prognostic biomarkers for immunotherapy treatment response is therefore necessary. This study is the first to combine and investigate multiple potential predictive and prognostic biomarkers and its dynamics. The results could serve for a better and multi-level understanding of the various factors influencing immunotherapy treatment.