ABSTRACT
The 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 as Oscillospira sp., Clostridia UCG-014, Lachnospiraceae UCG-010 sp., Prevotella copri, and a decrease in Sutterella sp., Lactobacillales, and Streptococcus sp. Patients who developed immune-related adverse events (irAEs) had an overall increased microbial diversity and richness, and a stool microbiome depleted in Agathobacter. 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.
ABSTRACT
We prospectively performed a longitudinal analysis of circulating tumor DNA (ctDNA) from 149 plasma samples and CT scans in Stage III and IV metastatic melanoma patients (n = 20) treated with targeted agents or immunotherapy using two custom next-generation sequencing (NGS) Ion AmpliSeq™ HD panels including 60 and 81 amplicons in 18 genes, respectively. Concordance of matching cancer-associated mutations in tissue and plasma was 73.3%. Mutant allele frequency (MAF) levels showed a range from 0.04% to 28.7%, well detectable with NGS technologies utilizing single molecule tagging like the AmpliSeq™ HD workflow. Median followup time of the tissue and/or plasma positive cohort (n = 15) was 24.6 months and median progression-free survival (PFS) was 7.8 months. Higher MAF ≥ 1% at baseline was not significantly associated with a risk of progression (Odds Ratio = 0.15; p = 0.155). Although a trend could be seen, MAF levels did not differ significantly over time between patients with and without a PFS event (p = 0.745). Depending on the cell-free DNA amount, NGS achieved a sensitivity down to 0.1% MAF and allowed for parallel analysis of multiple mutations and previously unknown mutations. Our study indicates that NGS gene panels could be useful for monitoring disease burden during therapy with ctDNA in melanoma patients.