Discovering molecular subgroups and cellular heterogeneity associated with pulmonary disease
OA Version
Citation
Abstract
Respiratory diseases are a leading cause of mortality worldwide, affecting millions each year. A major contributor to this burden is the absence of effective early detection strategies capable of predicting disease aggressiveness at an early stage. Transcriptomics-based approaches, particularly RNA sequencing (RNA-seq), offer promising avenues for the development of predictive biomarkers.RNA-seq has transformed genomics research and is increasingly shaping clinical diagnostics and precision medicine. Among its applications, single-cell RNA sequencing (scRNA-seq) has been pivotal in uncovering cellular heterogeneity relevant to tissue development and disease progression. This thesis explores the application of RNA-seq methodologies to advance the characterization of respiratory disease.
First, we developed the SCTK-QC pipeline within the SingleCellTK Bioconductor package to provide streamlined preprocessing and quality control of scRNA-seq data. Next, using multi-modal profiling of transcriptomes and cell surface proteins, we characterized immune microenvironments in tumor-negative lymph node regions of early-stage lung cancer patients. Importantly, at higher tumor stages we noted an increasingly immunosuppressive landscape in hilar nodal regions possibly more conducive to tumor invasion. Finally, we validated transcriptional signatures associated with rapidly declining lung function in the setting of Chronic Obstructive Pulmonary Disease (COPD) utilizing a novel bulk RNA-seq cohort derived from bronchial as well as nasal epithelial brushings. Crucially, part of the observed signature was attributable to altered epithelial cell composition, which included the increase of secretory cell populations and the decrease of ciliary cell populations. Collectively, these studies highlight the value of transcriptomic approaches in improving our understanding and clinical assessment of important respiratory diseases such as lung cancer and COPD.
Description
2026
License
Attribution-NonCommercial 4.0 International