Gastrointestinal Microbiome and Response to Immunotherapy in Metastatic Malignant Melanoma

This prospective, non-randomized clinical study evaluates the prognostic and predictive value of the gastrointestinal microbiome in patients with metastatic malignant melanoma treated with immune checkpoint inhibitors (PD-1 inhibitors and CTLA-4 inhibitors) in the first-line setting. Although immunotherapy has improved survival in metastatic melanoma, clinical outcomes remain heterogeneous and a substantial proportion of patients experience immune-related adverse events, pseudoprogression, or hyperprogression. Identification of biomarkers that predict response and toxicity remains clinically important. The gastrointestinal tract contains a high concentration of microbes and lymphoid tissue, and the immune system and microbiome exist in close interaction. The gastrointestinal microbiome influences systemic immune response through cytokine production and regulation of T-cell activity. Previous studies suggest that microbiome composition and diversity may be associated with overall survival (OS), progression-free survival (PFS), and treatment response in patients receiving immune checkpoint inhibitors. Antibiotic-induced dysbiosis has been associated with reduced efficacy of immunotherapy, and fecal microbiota transplantation has shown potential in overcoming resistance to PD-1 inhibitors. The primary objective of this study is to determine whether the predominant composition of the gastrointestinal microbiome is associated with objective response to PD-1 and CTLA-4 inhibitors in patients with metastatic malignant melanoma, assessed according to iRECIST criteria. The primary hypothesis is that a specific microbiome profile is associated with treatment response and progression-free survival (PFS). Secondary objectives include evaluation of the association between microbiome composition and immune-related adverse events, disease progression during treatment, and peripheral blood immune cell populations (CD3+, CD4+, CD8+, CD4/CD8 ratio, and macrophages). A total of 132 patients treated with first-line immune checkpoint inhibitors at the Institute of Oncology Ljubljana between March 2022 and March 2024 were enrolled. Clinical data were collected in anonymized form and include sex, age, date of diagnosis, performance status at treatment initiation, laboratory parameters (including LDH and S100), melanoma localization, BRAF status, treatment duration, radiologic response, and immune-related adverse events. In addition to standard-of-care treatment, participants underwent study-specific biological sample collection according to a predefined schedule. Stool samples were collected prior to treatment initiation, at week 12 (+2 weeks) and week 28 (+2 weeks), at suspected progression/hyperprogression, and at the occurrence of immune-related adverse events. If participants received antibiotic therapy, stool collection was postponed and performed three weeks after completion of antibiotics. Samples were analyzed at the Biotechnical Faculty, University of Ljubljana using amplicon sequencing of 16S rRNA with Illumina 16S/ITS Nextera two-step PCR and MiSeq 2×300 technology. Bioinformatic and statistical analyses were performed using the UPARSE pipeline, Silva NR SSU and LTP SSU databases, Mothur software package, and the R package Phyloseq. Peripheral venous blood samples were collected up to four weeks before treatment initiation, at week 12 (+2 weeks) and week 28 (+2 weeks), at suspected progression/hyperprogression, and at the occurrence of immune-related adverse events. Additional blood samples were analyzed at the Department of Cytology, Institute of Oncology Ljubljana using flow cytometry to determine immune cell populations, including CD3+, CD4+, CD8+, CD4/CD8 ratio, and macrophages. Samples were analyzed using FACSCanto 10 and FACSDiva software. Radiologic evaluation was performed using PET/CT or CT triplet (head, chest, abdomen) within four weeks prior to treatment initiation and at week 12 (+2 weeks) and week 28 (+2 weeks). Additional imaging was performed at suspected progression or based on clinical judgement. Treatment response was evaluated according to iRECIST criteria and categorized as complete response (CR), partial response (PR), stable disease (SD), or progressive disease (PD). Pseudoprogression was defined as temporary radiologic progression without clinical deterioration followed by subsequent reduction of tumor burden.