Faculty Bibliography

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.

The respiratory microbiome and its impact in health and disease is now well characterised. With the development of next-generation sequencing and the use of other techniques such as metabolomics, the functional impact of microorganisms in different host environments can be elucidated. It is now clear that the respiratory microbiome plays an important role in respiratory disease. In some diseases, such as bronchiectasis, examination of the microbiome can even be used to identify patients at higher risk of poor outcomes. Furthermore, the microbiome can aid in phenotyping. Finally, development of multi-omic analysis has revealed interactions between the host and microbiome in some conditions. This review, although not exhaustive, aims to outline how the microbiome is investigated, the healthy respiratory microbiome and its role in respiratory disease.

Respiratory failure is associated with increased mortality in COVID-19 patients. There are no validated lower airway biomarkers to predict clinical outcome. We investigated whether bacterial respiratory infections were associated with poor clinical outcome of COVID-19 in a prospective, observational cohort of 589 critically ill adults, all of whom required mechanical ventilation. For a subset of 142 patients who underwent bronchoscopy, we quantified SARS-CoV-2 viral load, analysed the lower respiratory tract microbiome using metagenomics and metatranscriptomics and profiled the host immune response. Acquisition of a hospital-acquired respiratory pathogen was not associated with fatal outcome. Poor clinical outcome was associated with lower airway enrichment with an oral commensal (Mycoplasma salivarium). Increased SARS-CoV-2 abundance, low anti-SARS-CoV-2 antibody response and a distinct host transcriptome profile of the lower airways were most predictive of mortality. Our data provide evidence that secondary respiratory infections do not drive mortality in COVID-19 and clinical management strategies should prioritize reducing viral replication and maximizing host responses to SARS-CoV-2.