The Genetics of Lung Cancer Susceptibility in Smokers
Ontology highlight
ABSTRACT:
PROVIDER: PRJNA242214 | ENA |
REPOSITORIES: ENA
Similar Datasets
Project description:RNA was obtained from histologically normal bronchial epithelium of smokers during time of clinical bronchoscopy from relatively accessible airway tissue. Gene expression data from smokers with lung cancer was compared with samples from smokers without lung cancer. This allowed us to generate a diagnostic gene expression profile that could distinguish the two classes. This profile could provide additional clinical benefit in diagnosing cancer amongst smokers with suspect lung cancer. Keywords: Disease state analysis
2006-02-27 | GSE4115 | GEO
Project description:Prior microarray studies of smokers at high risk for lung cancer have demonstrated that heterogeneity in bronchial airway epithelial cell gene expression response to smoking can serve as an early diagnostic biomarker for lung cancer. This study examines the relationship between gene expression variation and genetic variation in a central molecular pathway (NRF2-mediated antioxidant response) associated with smoking exposure and lung cancer. We assessed global gene expression in histologically normal airway epithelial cells obtained at bronchoscopy from smokers who developed lung cancer (SC, n=20), smokers without lung cancer (SNC, n=24), and never smokers (NS, n=8). Functional enrichment showed that the NRF2-mediated antioxidant response pathway differed significantly among these groups. Keywords: Global mRNA expression profiling 21 total arrays (20 unique patients) run on total RNA obtained from Bronchial Epithelium of Smokers with Lung Cancer 30 total arrays (24 unique patients) run on total RNA obtained from Bronchial Epithelium of Smokers without Lung Cancer 9 total arrays (8 unique patients) run on total RNA obtained from Bronchial Epithelium of Never Smokers
2010-09-30 | E-GEOD-19027 | biostudies-arrayexpress
Project description:Lung Cancer Genetic Study among Asian Never Smokers
| PRJNA705758 | ENA
Project description:Lung Cancer Genetic Study among Asian Never Smokers
| PRJNA705757 | ENA
Project description:Integrative analyses of lung cancer in never smokers
| PRJNA492373 | ENA
Project description:Integrative analyses of lung cancer in never smokers
| PRJNA492374 | ENA
Project description:Prior microarray studies of smokers at high risk for lung cancer have demonstrated that heterogeneity in bronchial airway epithelial cell gene expression response to smoking can serve as an early diagnostic biomarker for lung cancer. This study examines the relationship between gene expression variation and genetic variation in a central molecular pathway (NRF2-mediated antioxidant response) associated with smoking exposure and lung cancer. We assessed global gene expression in histologically normal airway epithelial cells obtained at bronchoscopy from smokers who developed lung cancer (SC, n=20), smokers without lung cancer (SNC, n=24), and never smokers (NS, n=8). Functional enrichment showed that the NRF2-mediated antioxidant response pathway differed significantly among these groups. Keywords: Global mRNA expression profiling
2010-10-01 | GSE19027 | GEO
Project description:Genome-wide association studies (GWAS) identified over fifty genomic loci associated with lung cancer risk. However, the genetic mechanisms and target genes underlying these loci are largely unknown, as most risk-associated-variants might regulate gene expression in a context-specific manner. Here, we generated a barcode-shared multiome (transcriptome and chromatin accessibility map) of 117,911 human lung cells from ever- and never-smokers to profile context-specific gene regulation. We observed that most of differentially expressed genes based on smoking status (smoking-responsive genes) were cell-type specific, and inter-cellular communication strength for Major Histocompatibility Complex-I and -II pathways were inverted between ever- and never-smokers. Accessible chromatin peak detection identified candidate cis-regulatory elements (cCREs) from each lung cell type, and 37% of them were cell-type specific. Colocalization of lung cancer candidate causal variants (CCVs) with these cCREs prioritized the variants for 68% of the GWAS loci, a subset of which was also supported by transcription factor footprinting. cCRE colocalization and single-cell based trait relevance score nominated epithelial and immune cells as the main cell groups contributing to lung cancer susceptibility. Notably, cCREs of rare epithelial cell types, including AT2-proliferating (0.13%) and basal cells (1.8%), overlapped with CCVs from multiple GWAS loci. A multi-level cCRE-gene linking system identified candidate susceptibility genes from 57% of lung cancer loci, including smoking-responsive genes. Our multiome dataset identified lung cancer susceptibility genes that were not detected in previous tissue- or cell-line-based approaches and further revealed the cell types and contexts where the susceptibility genes are functional, including the interplay of epithelial and immune cell types even in a single locus.
2024-08-14 | GSE241468 | GEO
Project description:Cytologically normal airway epithelial samples were collected during bronchoscopy of current and former smokers. Subjects enrolled in this study were either under suspicion of having lung cancer, had dysplasia in their airway, or were a healthy current, former or never smoker. We supplemented existing GEO series (GSE4115 and GSE7895) with the samples in this study to explore PI3K pathway activity in the these cohorts. This study contains: 2 arrays from smokers with COPD (no lung cancer), 1 array from smoker without COPD (no lung cancer); 2 samples from patients with lung cancer, 2 samples from patients without lung cancer; 20 samples from 10 matched individuals with airway dysplasia before and after treatment with myo-inositol, 6 additional samples from individuals with airway dysplasia; 27 samples from mammary epithelial cells used in oncogenic pathway analysis that have either the PI3K pathway activated, the Np63 pathway activated, or are a GFP control.
2010-04-11 | E-GEOD-12815 | biostudies-arrayexpress
Project description:Introduction: Lung cancer screening by computed tomography (CT) reduces mortality but exhibited high false-positive rates. We established a diagnostic classifier combining chest CT features with bronchial genomics. Materials and Methods: Patients with CT-detected suspected lung cancer were enrolled. The sample collected by bronchial brushing was used for RNA sequencing. R software was applied to build the model. Results: A total of 283 patients, including 183 with lung cancer and 100 with benign lesions, were included. When incorporating genomic data with radiological characteristics, the advanced model yielded 0.903 AUC with 81.1% NPV. Moreover, the classifier performed well regardless of lesion size, location, stage, histologic type, or smoking status. Pathway analysis showed enhanced epithelial differentiation, tumor metastasis, and impaired immunity were predominant in smokers with cancer, whereas tumorigenesis played a central role in non-smokers with cancer. Apoptosis and oxidative stress contributed critically in metastatic lung cancer; by contrast, immune dysfunction was pivotal in locally advanced lung cancer. Conclusions: We devised a minimal-to-noninvasive, efficient diagnostic classifier for smokers and non-smokers with lung cancer, which provides evidence for different mechanisms of cancer development and metastasis associated with smoking. A negative classifier result will help the physician make conservative diagnostic decisions.
2021-02-18 | GSE166926 | GEO