Simple SummaryOur study evaluated the use of the intestinal microbiome as a prognostic marker that seems to modulate response to immune checkpoint inhibitor (ICI) treatment in patients with late-stage non-small cell lung cancer (NSCLC), renal cell carcinoma (RCC), and metastatic melanoma. BiomeOne®, a stool microbiome-based algorithm, was able to classify patient samples according to the likeliness of achieving clinical benefit of ICI before treatment initiation by identifying an immunotherapy-favorable microbiome signature, outperforming the standard PD-L1 expression test. This study has additionally shed new light on the intestinal microbiome signature associated with the occurrence of irAEs, paving way to larger studies to validate and expand the current knowledge. Lastly, robust, easy-to-use, and non-invasive microbiome-based diagnostics hold promising potential for oncology, and further work should aim to expand these applications to other cancer types and microbiome-centered interventions, such as fecal microbiota transplantation (FMT), moving one step forward towards the era of personalized medicine.AbstractThe intestinal microbiome is by now an undebatable key player in the clinical outcome of ICI therapies. However, no microbiome profiling method to aid therapy decision is yet validated. We conducted a multi-centric study in patients with stage III/IV melanoma, NSCLC, or RCC receiving ICI treatment. The stool microbiome profile of 63 patients was analyzed with BiomeOne®, a microbiome-based algorithm that anticipates whether a patient will achieve clinical benefit with ICIs prior to therapy initiation. Classification of patient samples as Rs and NRs was achieved with a sensitivity of 81% and a specificity of 50% in this validation cohort. An ICI-favorable response was characterized by an intestinal microbiome rich in bacteria such asOscillospirasp., Clostridia UCG-014,LachnospiraceaeUCG-010 sp.,Prevotella copri, and a decrease inSutterellasp., Lactobacillales, andStreptococcussp. Patients who developed immune-related adverse events (irAEs) had an overall increased microbial diversity and richness, and a stool microbiome depleted inAgathobacter. When compared with the programmed death-ligand 1 (PD-L1) expression test in the subcohort of NSCLC patients (n= 38), BiomeOne®exhibited a numerically higher sensitivity (78.6%) in identifying responders when compared with the PD-L1 test (67.9%). This study provides an evaluation of BiomeOne®, the first microbiome-based test for prediction of ICI response, to achieve market authorization. Validation with further indications and expansion to other microbiome-based interventions will be essential to bring microbiome-based diagnostics into standard clinical practice.