Faculty Bibliography

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.

Lung injury is a major determinant of survival after pediatric hematopoietic cell transplantation (HCT). A deeper understanding of the relationship between pulmonary microbes, immunity, and the lung epithelium is needed to improve outcomes. In this multicenter study, we collected 278 bronchoalveolar lavage (BAL) samples from 229 patients treated at 32 children's hospitals between 2014-2022. Using paired metatranscriptomes and human gene expression data, we identified 4 patient clusters with varying BAL composition. Among those requiring respiratory support prior to sampling, in-hospital mortality varied from 22-60% depending on the cluster (p=0.007). The most common patient subtype, Cluster 1, showed a moderate quantity and high diversity of commensal microbes with robust metabolic activity, low rates of infection, gene expression indicating alveolar macrophage predominance, and low mortality. The second most common cluster showed a very high burden of airway microbes, gene expression enriched for neutrophil signaling, frequent bacterial infections, and moderate mortality. Cluster 3 showed significant depletion of commensal microbes, a loss of biodiversity, gene expression indicative of fibroproliferative pathways, increased viral and fungal pathogens, and high mortality. Finally, Cluster 4 showed profound microbiome depletion with enrichment of Staphylococci and viruses, gene expression driven by lymphocyte activation and cellular injury, and the highest mortality. BAL clusters were modeled with a random forest classifier and reproduced in a geographically distinct validation cohort of 57 patients from The Netherlands, recapitulating similar cluster-based mortality differences (p=0.022). Degree of antibiotic exposure was strongly associated with depletion of BAL microbes and enrichment of fungi. Potential pathogens were parsed from all detected microbes by analyzing each BAL microbe relative to the overall microbiome composition, which yielded increased sensitivity for numerous previously occult pathogens. These findings support personalized interpretation of the pulmonary microenvironment in pediatric HCT, which may facilitate biology-targeted interventions to improve outcomes.

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.

BACKGROUND:Lymphadenitis is the most common extrapulmonary tuberculosis (EPTB) manifestation. The microbiome is important to human health but uninvestigated in EPTB. We profiled the site-of-disease lymph node microbiome in tuberculosis lymphadenitis (TBL). METHODS:Fine-needle aspiration biopsies were collected from 158 pretreatment presumptive TBL patients in Cape Town, South Africa. 16S Illumina MiSeq rRNA gene sequencing was done. RESULTS:complex. CONCLUSIONS:-dominated dTBL lymphotypes, which contain taxa potentially targeted by TB treatment, were associated with milder, potentially earlier stage disease. These investigations lay foundations for studying the microbiome's role in lymphatic TB. The long-term clinical significance of these lymphotypes requires prospective validation.