{'fraction_non_alphanumeric': 0.02513227513227513, 'fraction_numerical': 0.007936507936507936, 'mean_word_length': 5.576811594202899, 'pattern_counts': {'":': 0, '<': 2, '<?xml version=': 0, '>': 0, 'https://': 1, 'lorem ipsum': 0, 'www.': 0, 'xml': 0}, 'pii_count': 0, 'substrings_counts': 0, 'word_list_counts': {'cursed_substrings.json': 0, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
Host transcriptomic signatures associated with dysbiosis in a preclinical model of lung cancer.

3107 Background: Enrichment of the lower airway microbiota with oral commensals has been associated with transcriptomic changes affecting several inflammatory pathways associated with non-small cell lung cancer (NSCLC) development and progression. Using a mouse model of NSCLC, we evaluated the effects of lower airway dysbiosis on tumor progression and host transcriptomics. Methods: Preclinical model of lung cancer was constructed by introducing luminescence-tagged Kras mutated cells into C57/B6 mice, causing lung cancer to develop. Lower airway dysbiosis was induced by weekly intratracheal challenge with either PBS or Veillonella parvula in wild type and lung cancer mice. Experiments were repeated twice to evaluate for survival as well as lower airway host response using flow cytometry and RNA sequencing (HiSeq). Sequence data was processed using a validated mouse gene expression signature matrix with cibersort from https://cibersort.stanford.edu and DESeq using FDR correction. Results: In wild type mice, lower airway dysbiosis with Veillonella did not affect the survival, weight gain or airway lumen diameter. Among lung cancer mice, dysbiosis led to increased mortality, weight loss, and tumor burden. Multiple transcriptomic signatures were identified among the dysbiosis groups (both in WT and lung cancer mice). Unsupervised hierarchical clustering of immune cell profiles using cibersort on whole transcriptome showed near perfect separation between the four experimental conditions. Amongst the most differentially enriched immune cell subsets, we identified that lung dysbiosis upregulates genes annotated to Th1 and Th2 cells (p < 0.01, q < 0.2). Using flow cytometry, we identified that PD-1, IL-17, and ROR-gamma are differentially expressed in CD4+ cells in dysbiosis conditions, and these patterns are consistent in whole RNA transcriptome. Conclusions: Transcriptomic signatures reveal immune profiles associated with dysbiosis, an experimental condition associated with worse outcomes in lung cancer. This investigation provides novel insights into how disruption of the lower airway microbiome may contribute to the pathogenesis of NSCLC.