Local microbiota signatures of pro-tumor immunity and checkpoint inhibition susceptibility in lung cancer

New York University School Of Medicine, New York NY

Investigators

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Abstract

Abstract. PD-1 blockade has become first line therapy of most non-small cell lung cancer (NSCLC). However, given the variable effectiveness of immunotherapy in this disease there is a need to better understand factors that affect individual’s response to this therapy. The lung microbiota plays an important role in host immune responses affecting subject’s susceptibility to inflammatory airway diseases. We have demonstrated that lower airway microbiota is associated with Th17 phenotype in the lower airways. In lung cancer, we identified a dysbiotic signature in the lower airways called pneumotypeSPT that is associated with transcriptomic signatures associated with lung carcinogenesis. Our preliminary data shows that subject s with lower airway microbiota characterized as pneumotypeSPTmay have increased mortality and increased immune checkpoint inhibitedtone. While gut microbiota signatures are partially associated with PD-1 blockade response, the effects of the lower airway microbiota on the immune tone and PD-1 blockade susceptibility are not known. Thus, we hypothesize that lower airway dysbiosis (pneumotypeSPT) alters the host inflammatory phenotype in the tumor microenvironment affecting the response to PD-1 blockade. We will evaluate airway/stool microbial signatures associated subjects’ response to PD-1 blockade by longitudinal assessment of the progression free survival (Aim 1). In addition, we will perform longitudinal sampling of airways, stool, and blood to expand our mechanistic understanding of the dynamic changes in the microbiome and host immune response during PD-1 blockade treatment (Aim 2). Validation and extension of the assessment of the microbiome and host inflammatory profile will be accomplished by using complementary approaches ( microbiota: 16S rRNA gene and metatranscriptome sequencing; inflammation: airway brush transcriptome, polychromatic flow cytometry, and single cell RNA sequencing of T cells). In Aim 3 we will use a preclinical mouse model of lung cancer that will allow us to evaluate the effects of dysbiosis on the lower airway immune tone and PD-1 blockade susceptibility. Identification of microbial signatures that affect the response to this first line therapy will be key to a personalized therapeutic approach and will identify novel modifiable targets. During the R37 extension period we will build on the data geing generated in these three aims focusing on how microbes affect the metabolic microenvironment in the lower airways. The metabolites being affected by lower airway dysbiosis in the setting of advanced stage NSCLC likely play a key immunomodulatory role that affect s PD-1 blockade treatment response. Thus, in Aim 4, we will use the lower airway and plasma samples obtained under Aims 1 and 2 to test the hypothesis that lower airway dysbiosis in patients with NSCLC is associated with changes in the metabolic environment. To that end, we will use an untargeted LC-MS metabolomic approach. Then, in Aim 5 we will use the preclinical model of lung cancer done in Aim 3 to test for causality by evaluating the hypothesis that induced lower airway dysbiosis will remodel the tumor metabolic microenvironment decreasing the responses to PD-1 blockade.