Faculty Bibliography

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.

Malignant pleural effusions (MPE) complicate malignancies and portend worse outcomes. MPE is comprised of various components, including immune cells, cancer cells, and cell-free DNA/RNA. There have been investigations into using these components to diagnose and prognosticate MPE. We hypothesize that the microbiome of MPE is unique and may be associated with diagnosis and prognosis. We compared the microbiota of MPE against microbiota of pleural effusions from non-malignant and paramalignant states. We collected a total of 165 pleural fluid samples from 165 subjects; Benign (n = 16), Paramalignant (n = 21), MPE-Lung (n = 57), MPE-Other (n = 22), and Mesothelioma (n = 49). We performed high throughput 16S rRNA gene sequencing on pleural fluid samples and controls. We showed that there are compositional differences among pleural effusions related to non-malignant, paramalignant, and malignant disease. Furthermore, we showed differential enrichment of bacterial taxa within MPE depending on the site of primary malignancy. Pleural fluid of MPE-Lung and Mesothelioma were associated with enrichment with oral and gut bacteria that are commonly thought to be commensals, including Rickettsiella, Ruminococcus, Enterococcus, and Lactobacillales. Mortality in MPE-Lung is associated with enrichment in Methylobacterium, Blattabacterium, and Deinococcus. These observations lay the groundwork for future studies that explore host-microbiome interactions and their influence on carcinogenesis.

INTRODUCTION/BACKGROUND:There are few existing severity scoring systems in the literature, and no formally widely accepted chest X-ray template for reporting COVID-19 infection. We aimed to modify the chest X-ray COVID-19 severity scoring system from the Brixia scoring system with placement of more emphasis on consolidation and to assess if the scoring tool could help predict intubation. METHODS:A severity chest X-ray scoring system was modified from the Brixia scoring system. PCR positive COVID-19 positive patient's chest X-rays admitted to our hospital over 3 months were reviewed and correlated with; non-invasive ventilation, intubation and death. An analysis was performed using a receiver operating curve to predict intubation from all admission chest X-rays. RESULTS:The median score of all 325 admission chest X-rays was 3 (Interquartile range (IQR) 0-6.5). The median score of admission chest X-rays of those who did not require ICU admission and survived was 1.5 (IQR 0-5); and 9 (IQR 4.75-12) was median admission score of those requiring intubation. The median scores of the pre-intubation ICU chest X-rays was 11.5 (IQR 9-14.125), this increased from a median admission chest X-ray score for this group of 9 (P-value < 0.01). A cut-off score of 6 had a sensitivity of 77% and specificity of 73% in predicting the need for intubation. CONCLUSION/CONCLUSIONS:Higher chest X-ray severity scores are associated with intubation, need for non-invasive ventilation and death. This tool may also be helpful in predicting intubation.