Longitudinal transcriptomic analysis reveals persistent enrichment of iron homeostasis and erythrocyte function pathways in severe COVID-19 ARDS.

Introduction: The acute respiratory distress syndrome (ARDS) is a common complication of severe COVID-19 and contributes to patient morbidity and mortality. ARDS is a heterogeneous syndrome caused by various insults, and results in acute hypoxemic respiratory failure. Patients with ARDS from COVID-19 may represent a subgroup of ARDS patients with distinct molecular profiles that drive disease outcomes. Here, we hypothesized that longitudinal transcriptomic analysis may identify distinct dynamic pathobiological pathways during COVID-19 ARDS. Methods: We identified a patient cohort from an existing ICU biorepository and established three groups for comparison: 1) patients with COVID-19 ARDS that survived hospitalization (COVID survivors, n = 4), 2) patients with COVID-19 ARDS that did not survive hospitalization (COVID non-survivors, n = 5), and 3) patients with ARDS from other causes as a control group (ARDS controls, n = 4). RNA was isolated from peripheral blood mononuclear cells (PBMCs) at 4 time points (Days 1, 3, 7, and 10 following ICU admission) and analyzed by bulk RNA sequencing. Results: We first compared transcriptomes between groups at individual timepoints and observed significant heterogeneity in differentially expressed genes (DEGs). Next, we utilized the likelihood ratio test to identify genes that exhibit different patterns of change over time between the 3 groups and identified 341 DEGs across time, including hemoglobin subunit alpha 2 (HBA1, HBA2), hemoglobin subunit beta (HBB), von Willebrand factor C and EGF domains (VWCE), and carbonic anhydrase 1 (CA1), which all demonstrated persistent upregulation in the COVID non-survivors compared to COVID survivors. Of the 341 DEGs, 314 demonstrated a similar pattern of persistent increased gene expression in COVID non-survivors compared to survivors, associated with canonical pathways of iron homeostasis signaling, erythrocyte interaction with oxygen and carbon dioxide, erythropoietin signaling, heme biosynthesis, metabolism of porphyrins, and iron uptake and transport. Discussion: These findings describe significant differences in gene regulation during patient ICU course between survivors and non-survivors of COVID-19 ARDS. We identified multiple pathways that suggest heme and red blood cell metabolism contribute to disease outcomes. This approach is generalizable to larger cohorts and supports an approach of longitudinal sampling in ARDS molecular profiling studies, which may identify novel targetable pathways of injury and resolution.

Asthma and coronavirus disease 2019-related outcomes in hospitalized patients: A single-center experience.

BACKGROUND: Several chronic conditions have been associated with a higher risk of severe coronavirus disease 2019 (COVID-19), including asthma. However, there are conflicting conclusions regarding risk of severe disease in this population. OBJECTIVE: To understand the impact of asthma on COVID-19 outcomes in a cohort of hospitalized patients and whether there is any association between asthma severity and worse outcomes. METHODS: We identified hospitalized patients with COVID-19 with confirmatory polymerase chain reaction testing with (n = 183) and without asthma (n = 1319) using International Classification of Diseases, Tenth Revision, codes between March 1 and December 30, 2020. We determined asthma maintenance medications, pulmonary function tests, highest historical absolute eosinophil count, and immunoglobulin E. Primary outcomes included death, mechanical ventilation, intensive care unit (ICU) admission, and ICU and hospital length of stay. Analysis was adjusted for demographics, comorbidities, smoking status, and timing of illness in the pandemic. RESULTS: In unadjusted analyses, we found no difference in our primary outcomes between patients with asthma and patients without asthma. However, in adjusted analyses, patients with asthma were more likely to have mechanical ventilation (odds ratio, 1.58; 95% confidence interval [CI], 1.02-2.44; P = .04), ICU admission (odds ratio, 1.58; 95% CI, 1.09-2.29; P = .02), longer hospital length of stay (risk ratio, 1.30; 95% CI, 1.09-1.55; P < .003), and higher mortality (hazard ratio, 1.53; 95% CI, 1.01-2.33; P = .04) compared with the non-asthma cohort. Inhaled corticosteroid use and eosinophilic phenotype were not associated with considerabledifferences. Interestingly, patients with moderate asthma had worse outcomes whereas patients with severe asthma did not. CONCLUSION: Asthma was associated with severe COVID-19 after controlling for other factors.

Robust assessment of tumor mutational burden in cytological specimens from lung cancer patients.

OBJECTIVES: Tumor mutational burden (TMB) has emerged as a promising predictive biomarker for immune checkpoint inhibitor therapy. While the feasibility of TMB analysis on formalin-fixed paraffin-embedded (FFPE) samples has been thoroughly evaluated, only limited analyses have been performed on cytological samples, and no dedicated study has investigated concordance of TMB between different sample types. Here, we assessed TMB on matched histological and cytological samples from lung cancer patients and evaluated the accuracy of TMB estimation in these sample types. MATERIALS AND METHODS: We analyzed mutations and resulting TMB in FFPE samples and matched ethanol-fixed cytological smears (n = 12 matched pairs) by using a targeted next-generation sequencing assay (Oncomine™ Tumor Mutational Load). Two different variant allele frequency (VAF) thresholds were used to estimate TMB (VAF = 5% or 10%). RESULTS: At 5% VAF threshold, 73% (107/147) of mutations were concordantly detected in matched histological and cytological samples. Discordant variants were mainly unique to FFPE samples (34/40 discordant variants) and mostly C:G > T:A transitions with low allelic frequency, likely indicating formalin fixation artifacts. Increasing the VAF threshold to 10% clearly increased the number of concordantly detected mutations in matched histological and cytological samples to 96% (100/106 mutations), and drastically reduced the number of FFPE-only mutations (from 34 to 4 mutations). In contrast, cytological samples showed consistent mutation count and TMB values at both VAF thresholds. Using FFPE samples, 2 out of 12 patients were classified as TMB-high at VAF cutoff of 5% but TMB-low at 10%, whereas cytological specimens allowed consistent patient classification independently from VAF cutoff. CONCLUSION: Our results show that cytological smears provide more consistent TMB values due to high DNA quality and lack of formalin-fixation induced artifacts. Therefore, cytological samples should be the preferred sample type for robust TMB estimation.

Tumor mutational burden assessed by targeted NGS predicts clinical benefit from immune checkpoint inhibitors in non-small cell lung cancer.

In non-small cell lung cancer (NSCLC), immune checkpoint inhibitors (ICIs) significantly improve overall survival (OS). Tumor mutational burden (TMB) has emerged as a predictive biomarker for patients treated with ICIs. Here, we evaluated the predictive power of TMB measured by the Oncomine™ Tumor Mutational Load targeted sequencing assay in 76 NSCLC patients treated with ICIs. TMB was assessed retrospectively in 76 NSCLC patients receiving ICI therapy. Clinical data (RECIST 1.1) were collected and patients were classified as having either durable clinical benefit (DCB) or no durable benefit (NDB). Additionally, genetic alterations and PD-L1 expression were assessed and compared with TMB and response rate. TMB was significantly higher in patients with DCB than in patients with NDB (median TMB = 8.5 versus 6.0 mutations/Mb, Mann-Whitney p = 0.0244). 64% of patients with high TMB (cut-off = third tertile, TMB ≥ 9) were responders (DCB) compared to 33% and 29% of patients with intermediate and low TMB, respectively (cut-off = second and first tertile, TMB = 5-9 and TMB ≤ 4, respectively). TMB-high patients showed significantly longer progression-free survival (PFS) and OS (log-rank test p = 0.0014 for PFS and 0.0197 for OS). While identifying different subgroups of patients, combining PD-L1 expression and TMB increased the predictive power (from AUC 0.63 to AUC 0.65). Our results show that the TML panel is an effective tool to stratify patients for ICI treatment. A combination of biomarkers might maximize the predictive precision for patient stratification. Our study supports TMB evaluation through targeted NGS in NSCLC patient samples as a tool to predict response to ICI therapy. We offer recommendations for a reliable and cost-effective assessment of TMB in a routine diagnostic setting. © 2019 The Authors. The Journal of Pathology published by John Wiley & Sons Ltd on behalf of Pathological Society of Great Britain and Ireland.