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

Local microbiota signatures of pro-tumor immunity and checkpoint inhibition susceptibility in lung cancer
肺癌中促肿瘤免疫和检查点抑制敏感性的局部微生物群特征
批准号:
10545754
负责人:
Leopoldo Nicolas Segal
金额:
$62.66万
依托单位国家:
美国
项目类别:
财政年份:
2020
资助国家:
美国
项目状态:
已结题
起止时间:
2020-01-01 至 2024-12-31
关键词:
16S ribosomal RNA sequencingAffectAirway DiseaseBiological MarkersBloodBlood specimenCancer EtiologyCancer ModelCellsCessation of lifeCharaCharacteristicsClinicalClinical TrialsColorDataDiseaseDistantEarly identificationEffectivenessEligibility DeterminationEtiologyEvaluationFecesFlow CytometryGrantIL17 geneImmuneImmune responseImmunityImmunotherapyInflammationInflammatoryInterventionInvestigationLinkLoxP-flanked alleleLungLung AdenocarcinomaMalignant NeoplasmsMalignant neoplasm of lungMediatingMethodsMicrobeModelingModificationMusNewly DiagnosedNon-Small-Cell Lung CarcinomaOralOutcomePIK3CG genePathway interactionsPatientsPhenotypePlayPre-Clinical ModelPredispositionPrevalencePrevotellaProgression-Free SurvivalsRNARibosomal RNARoleSamplingT cell responseT-LymphocyteTaxonomyTestingTumor BurdenTumor ImmunityValidationVeillonellaaspiratecheckpoint inhibitiondesigndysbiosisgut microbiotagut-lung axisimmune checkpointindividual responseinnovationlung carcinogenesislung microbiotametatranscriptomemetatranscriptomicsmicrobialmicrobial signaturemicrobiomemicrobiome researchmicrobiotamicrobiota profilesmortalitymouse modelmucosal microbiotamultiple omicsneoantigensnovelpersonalized therapeuticpre-clinicalpredicting responseprimary outcomeprogrammed cell death ligand 1programmed cell death protein 1prospectiverRNA Genesrespiratory microbiotaresponserisk stratificationsingle-cell RNA sequencingsmoking prevalencestool sampletherapy outcometraittranscriptometranscriptome sequencingtranscriptomicstreatment responderstreatment responsetumortumor microenvironment

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Abstract. Despite the declining prevalence of smoking in the US, lung cancer continues to be the leading cause of cancer deaths. Treatment of lung cancer with 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 subjects with lower airway microbiota characterized as pneumotypeSPT may have increased mortality and increased immune checkpoint inhibited tone. 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. To study this, we will utilize a scientifically rigorous approach to conduct this pathophysiological investigation using prospective airway, stool, and blood samples collected before and after PD-1 blockade treatment of subjects with advanced NSCLC. 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. Lay summary. The treatment of lung cancer, the leading cause of cancer deaths in the U.S., has been revolutionized by the use of immunotherapy. However, the response to this therapy is variable and recent data suggest that microbes that colonize our bodies (called microbiome) can affect subject individual’s response. In this project, we will uncover microbial signatures that affect the lung cancer treatment response to immunotherapy.
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