Association between gut microbiome components and immunotherapy efficacy in two small cell lung cancer cases with divergent outcomes

Introduction. Immunotherapy can be effective in some patients with small-cell lung cancer (SCLC) with good performance status. However, the factors contributing to sustained treatment responses remain unclear. The intestinal microbiome profile has emerged as a potential biomarker for the effectiveness of chemoimmunotherapy in SCLC. Evidence suggests that microbiome diversity, both in richness and abundance, may influence immunotherapy outcomes. The presence or absence of specific bacterial populations may also be linked to treatment success or failure. This pilot study compared the gut microbiome profile in two SCLC patients with partial responses to chemoimmunotherapy but had distinctly different outcomes. Material and methods. Metagenomic analysis of the gut microbiome was performed using stool samples from two patients collected prior to treatment initiation. Gut microbiome composition was determined based on next-generation sequencing of the hypervariable regions of the 16S rRNA gene. Both patients received a treatment regimen consisting of atezolizumab, carboplatin and etoposide. Results. The progression-free survival (PFS) and overall survival (OS) were 5.7 and 10.2 months for the first patient and 19.9 and 34.9 months for the second patient, respectively. The patient with early progression exhibited reduced species-level diversity compared to the long-term responder. Additionally, bacteria from the families Lachnospiraceae , Akkermansiaceae were found to be more prevalent in the patient with greater immunotherapy benefit. Conversely, the families Enterobacteriaceae , Succinivibrionaceae , Streptococcaceae, and Desulfovibrionaceae were more abundant in the patient with short survival than in patients with prolonged response . Conclusions. Bacteria residing in the gut may affect the efficacy of chemoimmunotherapy in SCLC patients and represents a promising candidate for predictive biomarkers of treatment response and efficacy.