Faculty Bibliography

RATIONALE/BACKGROUND:Lower airway enrichment with oral commensals has been previously associated with grade 3 severe primary graft dysfunction (PGD) after lung transplantation (LT). We aimed to determine whether this dysbiotic signature is present across all PGD severity grades, including milder forms, and whether it is associated with a distinct host inflammatory endotype. METHODS:Lower airway samples from 96 LT recipients with varying degrees of PGD were used to evaluate the lung allograft microbiota via 16S rRNA gene sequencing. Bronchoalveolar lavage (BAL) cytokine concentrations and cell differential percentages were compared across PGD grades. In a subset of samples, we evaluated the lower airway host transcriptome using RNA sequencing methods. RESULTS:Differential analyses demonstrated lower airway enrichment with supraglottic-predominant taxa (SPT) in both moderate and severe PGD. Dirichlet Multinomial Mixtures (DMM) modeling identified two distinct microbial clusters. A greater percentage of subjects with moderate-severe PGD were identified within the dysbiotic cluster (C-SPT) than within the no PGD group (48 and 29%, respectively) though this difference did not reach statistical significance (p=0.06). PGD severity associated with increased BAL neutrophil concentration (p=0.03) and correlated with BAL concentrations of MCP-1/CCL2, IP-10/CXCL10, IL-10, and TNF-α (p<0.05). Furthermore, microbial signatures of dysbiosis correlated with neutrophils, MCP-1/CCL-2, IL-10, and TNF-α (p<0.05). C-SPT exhibited differential expression of TNF, SERPINE1 (PAI-1), MPO, and MMP1 genes and upregulation of MAPK pathways, suggesting that dysbiosis regulates host signaling to promote neutrophilic inflammation. CONCLUSIONS:Lower airway dysbiosis within the lung allograft is associated with a neutrophilic inflammatory endotype, an immune profile commonly recognized as the hallmark for PGD pathogenesis. This data highlights a putative role for lower airway microbial dysbiosis in the pathogenesis of this syndrome.

BACKGROUND:Risk of early-stage lung adenocarcinoma (LUAD) recurrence after surgical resection is significant, and post-recurrence median survival is approximately two years. Currently there are no commercially available biomarkers that predict recurrence. Here, we investigated whether microbial and host genomic signatures in the lung can predict recurrence. METHODS:In 91 early-stage (Stage IA/IB) LUAD-patients with extensive follow-up, we used 16s rRNA gene sequencing and host RNA-sequencing to map the microbial and host transcriptomic landscape in tumor and adjacent unaffected lung samples. RESULTS:23 out of 91 subjects had tumor recurrence over 5-year period. In tumor samples, LUAD recurrence was associated with enrichment with Dialister, Prevotella, while in unaffected lung, recurrence was associated with enrichment with Sphyngomonas and Alloiococcus. The strengths of the associations between microbial and host genomic signatures with LUAD recurrence were greater in adjacent unaffected lung samples than in the primary tumor. Among microbial-host features in the unaffected lung samples associated with recurrence, enrichment with Stenotrophomonas geniculata and Chryseobacterium were positively correlated with upregulation of IL-2, IL-3, IL-17, EGFR, HIF-1 signaling pathways among the host transcriptome. In tumor samples, enrichment with Veillonellaceae Dialister, Ruminococcacea, Haemophilus Influenza, and Neisseria were positively correlated with upregulation of IL-1, IL-6, IL17, IFN, and Tryptophan metabolism pathways. CONCLUSIONS:Overall, modeling suggested that a combined microbial/transcriptome approach using unaffected lung samples had the best biomarker performance (AUC=0.83). IMPACT/CONCLUSIONS:This study suggests that LUAD recurrence is associated with distinct pathophysiological mechanisms of microbial-host interactions in the unaffected lung rather than those present in the resected tumor.

Hematopoietic cell transplantation (HCT) uses cytotoxic chemotherapy and/or radiation followed by intravenous infusion of stem cells to cure malignancies, bone marrow failure and inborn errors of immunity, hemoglobin and metabolism. Lung injury is a known complication of the process, due in part to disruption in the pulmonary microenvironment by insults such as infection, alloreactive inflammation and cellular toxicity. How microorganisms, immunity and the respiratory epithelium interact to contribute to lung injury is uncertain, limiting the development of prevention and treatment strategies. Here we used 278 bronchoalveolar lavage (BAL) fluid samples to study the lung microenvironment in 229 pediatric patients who have undergone HCT treated at 32 children's hospitals between 2014 and 2022. By leveraging paired microbiome and human gene expression data, we identified high-risk BAL compositions associated with in-hospital mortality (P = 0.007). Disadvantageous profiles included bacterial overgrowth with neutrophilic inflammation, microbiome contraction with epithelial fibroproliferation and profound commensal depletion with viral and staphylococcal enrichment, lymphocytic activation and cellular injury, and were replicated in an independent cohort from the Netherlands (P = 0.022). In addition, a broad array of previously occult pathogens was identified, as well as a strong link between antibiotic exposure, commensal bacterial depletion and enrichment of viruses and fungi. Together these lung-immune system-microorganism interactions clarify the important drivers of fatal lung injury in pediatric patients who have undergone HCT. Further investigation is needed to determine how personalized interpretation of heterogeneous pulmonary microenvironments may be used to improve pediatric HCT outcomes.

INTRODUCTION/UNASSIGNED:Mounting evidence indicates that an individual's humoral adaptive immune response plays a critical role in the setting of SARS-CoV-2 infection, and that the efficiency of the response correlates with disease severity. The relationship between the adaptive immune dynamics in the lower airways with those in the systemic circulation, and how these relate to an individual's clinical response to SARS-CoV-2 infection, are less understood and are the focus of this study. MATERIAL AND METHODS/UNASSIGNED:We investigated the adaptive immune response to SARS-CoV-2 in paired samples from the lower airways and blood from 27 critically ill patients during the first wave of the pandemic (median time from symptom onset to intubation 11 days). Measurements included clinical outcomes (mortality), bronchoalveolar lavage fluid (BALF) and blood specimen antibody levels, and BALF viral load. RESULTS/UNASSIGNED:While there was heterogeneity in the levels of the SARS-CoV-2-specific antibodies, we unexpectedly found that some BALF specimens displayed higher levels than the paired concurrent plasma samples, despite the known dilutional effects common in BALF samples. We found that survivors had higher levels of anti-spike, anti-spike-N-terminal domain and anti-spike-receptor-binding domain IgG antibodies in their BALF (p<0.05), while there was no such association with antibody levels in the systemic circulation. DISCUSSION/UNASSIGNED:Our data highlight the critical role of local adaptive immunity in the airways as a key defence mechanism against primary SARS-CoV-2 infection.

Approximately 30% of early-stage lung adenocarcinoma patients present with disease progression after successful surgical resection. Despite efforts of mapping the genetic landscape, there has been limited success in discovering predictive biomarkers of disease outcomes. Here we performed a systematic multi-omic assessment of 143 tumors and matched tumor-adjacent, histologically-normal lung tissue with long-term patient follow-up. Through histologic, mutational, and transcriptomic profiling of tumor and adjacent-normal tissue, we identified an inflammatory gene signature in tumor-adjacent tissue as the strongest clinical predictor of disease progression. Single-cell transcriptomic analysis demonstrated the progression-associated inflammatory signature was expressed in both immune and non-immune cells, and cell type-specific profiling in monocytes further improved outcome predictions. Additional analyses of tumor-adjacent transcriptomic data from The Cancer Genome Atlas validated the association of the inflammatory signature with worse outcomes across cancers. Collectively, our study suggests that molecular profiling of tumor-adjacent tissue can identify patients at high risk for disease progression.