Background: Preclinical and clinical data indicate that chemoradiotherapy (CRT) in combination with checkpoint inhibitors may prime an anti-tumor immunological response in esophageal cancer. However, responses to neoadjuvant therapy can vary widely and the key biomarkers to determine response remain poorly understood. The fecal microbiome is a novel and potentially modifiable biomarker of immunotherapy response, and both fecal and tumor microbes have been found to associate with outcomes in esophageal cancer. Methods: Fecal and tumor samples were collected from patients with stage II–III resectable esophageal or gastroesophageal junction carcinoma treated with neoadjuvant immune checkpoint inhibitors (ICIs) plus CRT prior to surgical resection. Microbiome profiles were analyzed by 16S rRNA amplicon sequencing and taxonomic data were integrated with fecal metabolite analysis to assess microbial function. Results: The fecal microbiome of patients with pathological complete response (PCR) grouped in distinct clusters compared to patients with residual viable tumor (RVT) by Bray–Curtis diversity metric. Integrated taxonomic and metabolomic analysis of fecal samples identified a sphingolipid and primary bile acid as enriched in the PCR, the levels of which correlated with several bacterial species: Roseburis inulinivorans, Ruminococcus callidus, and Fusicantenibacter saccharivorans. Analysis of the tumor microbiome profiles identified several bacterial genera previously associated with esophageal tumors, including Streptococcus and Veillonella. Conclusions: These results further characterize the fecal and tumor microbiome of patients with operable esophageal cancer and identify specific microbes and metabolites that may help elucidate how microbes contribute to tumor response with neoadjuvant CRT combined with ICI.

Immune checkpoint inhibitor (ICI) therapy has yielded revolutionary outcomes among some individuals with skin cancer, but a large percentage of individuals do not benefit from these treatments. The gut microbiota is hypothesized to impact ICI therapy outcomes. However, data on ICI therapy, gut microbiota, and non-melanoma skin cancers are limited. To examine the association of gut microbiota structure and function with non-melanoma skin cancer ICI outcomes, we performed 16S rRNA V1-V2 gene amplicon sequencing of 68 fecal samples collected longitudinally from individuals with basal cell carcinoma ( n = 5), Merkel cell carcinoma ( n = 5), or cutaneous squamous cell carcinoma (CSCC, n = 11), followed by tumor-dependent differential analyses of bacterial composition and fecal sample analysis by untargeted metabolomics. Across all tumor types, we identified 10 differential bacterial genera between responders (R) or non-responders (NR) to ICI therapy. Among individuals with CSCC, we identified 10 genera and 20 species that differentiated between R and NR and yielded 8 pathways enriched in NR and 12 pathways enriched in R by predicted functional pathway analyses. Untargeted fecal metabolomics to examine putative gut microbiota metabolites associated with CSCC ICI R/NR identified nine KEGG pathways associated with ICI efficacy. In summary, this exploratory study suggests gut microbiota features that are associated with ICI efficacy in individuals with non-melanoma skin cancers and highlights the need for larger studies to validate the results. IMPORTANCE: Prior studies examining associations between ICI efficacy and the gut microbiome have focused primarily on individuals with melanoma, for whom ICI therapy was first approved. Meanwhile, data regarding microbiome features associated with ICI responses in individuals with non-melanoma skin cancers (NMSCs) have remained limited. This initial fecal microbiota examination of individuals with NMSCs suggests that larger-scale studies to extend and validate our findings may yield predictive or prognostic biomarkers for individuals with NMSC receiving ICI with potential to provide insight to complementary, effective therapeutic interventions through microbiota modification.

While immune checkpoint inhibitors (ICI)-based regimens and chemo-immunotherapy combinations (chemo-ICI) are now first-line therapy for patients with metastatic non-small cell lung cancer (NSCLC), the number of patients who experience a sustained response to treatment remains limited. The majority of patients will not benefit from initial treatment (primary resistance) or develop progressive disease after an initial period of response (acquired resistance). Microbiome-based biomarkers offer an opportunity to identify patients who may have a poor response to ICI-based regimens using non-invasive methods, and potentially, then the microbiota may be amenable to therapy-enhancing alteration. However, a deep understanding of the longitudinal dynamics of gut microbial features in patients treated with ICIs in NSCLC, a feature of likely importance for microbiome-based therapeutics, remains limited. In this study, we show that patients with NSCLC who experience primary resistance to an ICI-based regimen show a loss of intra-individual microbiome stability in the first 4 months during treatment with an ICI-based regimen, independent of antibiotic exposure. Loss of microbiome stability was validated in a second tumor type in patients with melanoma. To identify key microbial species associated with progression, recursive feature elimination with random forest classifiers was used to identify temporally associated microbial species associated with disease progression. An index of these progression-associated species was able to predict clinical outcomes based on pre-treatment fecal samples, with further validation on an independent cohort. Together, our data show that microbial instability may be an early indicator of ICI-resistance in patients with NSCLC and melanoma, with the potential to be developed into biomarkers of primary resistance to ICI-based regimens.

Mucosal-associated invariant T (MAIT) cells are innate-like T cells capable of MR1-dependent immune surveillance, but how intratumoral bacteria modulate MR1 expression in human lung tumors remains unclear. We studied intratumoral MAIT cells from paired single-cell RNA and TCR sequencing datasets of tumor-infiltrating CD3 T cells isolated from non-small cell lung cancer tumors in patients receiving neoadjuvant PD-1 blockade therapy. MAIT cells were subclustered to identify conventional MAIT-associated TCR clonotypes, which were then used to examine how bacterial exposure impacts cell-surface MR1 expression and downstream MAIT TCR activation. We found that select intratumoral Enterococcus species (spp.) did not directly activate MAIT cells but enhanced MR1-dependent MAIT activation in the presence of exogenous 5-OP-RU by increasing cell-surface MR1 expression on antigen-presenting cells including dendritic cells, B cells, and mononuclear phagocytes. This increase in MR1 cell surface expression is modulated through a posttranscriptional mechanism consistent with altered intracellular processing and trafficking of MR1. These findings reveal a role for tumor-associated bacteria in modulating MR1-dependent innate-like T cell activation and provide a basis for future studies examining whether this process influences response to immune checkpoint blockade.