Epigenetic Age Acceleration Enhances Prediction of Overall Survival in Early-Stage Non-Small Cell Lung Cancer
Ontology highlight
ABSTRACT:
ORGANISM(S): Homo sapiens
PROVIDER: GSE347344 | GEO | 2026/09/19
REPOSITORIES: GEO
Similar Datasets
Project description:Tobacco smoking is responsible for over 90% of lung cancer cases, and yet the precise molecular alterations induced by smoking in lung that develop into cancer and impact survival have remained obscure. We performed gene expression analysis using HG-U133A Affymetrix chips on 135 fresh frozen tissue samples of adenocarcinoma and paired noninvolved lung tissue from current, former and never smokers, with biochemically validated smoking information. ANOVA analysis adjusted for potential confounders, multiple testing procedure, Gene Set Enrichment Analysis, and GO-functional classification were conducted for gene selection. Results were confirmed in independent adenocarcinoma and non-tumor tissues from two studies. We identified a gene expression signature characteristic of smoking that includes cell cycle genes, particularly those involved in the mitotic spindle formation (e.g., NEK2, TTK, PRC1). Expression of these genes strongly differentiated both smokers from non-smokers in lung tumors and early stage tumor tissue from non-tumor tissue (p<0.001 and fold-change>1.5, for each comparison), consistent with an important role for this pathway in lung carcinogenesis induced by smoking. These changes persisted many years after smoking cessation. NEK2 (p<0.001) and TTK (p=0.002) expression in the noninvolved lung tissue was also associated with a 3-fold increased risk of mortality from lung adenocarcinoma in smokers. Our work provides insight into the smoking-related mechanisms of lung neoplasia, and shows that the very mitotic genes known to be involved in cancer development are induced by smoking and affect survival. These genes are candidate targets for chemoprevention and treatment of lung cancer in smokers. Keywords: comparative genomics
2008-02-20 | GSE10072 | GEO
Project description:Tobacco smoking is responsible for over 90% of lung cancer cases, and yet the precise molecular alterations induced by smoking in lung that develop into cancer and impact survival have remained obscure. We performed gene expression analysis using HG-U133A Affymetrix chips on 135 fresh frozen tissue samples of adenocarcinoma and paired noninvolved lung tissue from current, former and never smokers, with biochemically validated smoking information. ANOVA analysis adjusted for potential confounders, multiple testing procedure, Gene Set Enrichment Analysis, and GO-functional classification were conducted for gene selection. Results were confirmed in independent adenocarcinoma and non-tumor tissues from two studies. We identified a gene expression signature characteristic of smoking that includes cell cycle genes, particularly those involved in the mitotic spindle formation (e.g., NEK2, TTK, PRC1). Expression of these genes strongly differentiated both smokers from non-smokers in lung tumors and early stage tumor tissue from non-tumor tissue (p<0.001 and fold-change>1.5, for each comparison), consistent with an important role for this pathway in lung carcinogenesis induced by smoking. These changes persisted many years after smoking cessation. NEK2 (p<0.001) and TTK (p=0.002) expression in the noninvolved lung tissue was also associated with a 3-fold increased risk of mortality from lung adenocarcinoma in smokers. Our work provides insight into the smoking-related mechanisms of lung neoplasia, and shows that the very mitotic genes known to be involved in cancer development are induced by smoking and affect survival. These genes are candidate targets for chemoprevention and treatment of lung cancer in smokers. Experiment Overall Design: Overall, 180 adenocarcinoma and non-tumor tissue samples were selected for the analyses, including duplicate or triplicate samples from 14 subjects for quality control. From the original 180 samples, 148 provided sufficient quantity of high-quality RNA for microarray analyses; 13 additional samples were excluded because of problematic assays. Normalization was conducted on the remaining 135 microarrays. After normalization, 13 samples were excluded because of low percentage of tumor cells in the tumor tissues. This report is based on 122 samples, of which 15 duplicates were averaged, resulting in 107 final expression values from 58 tumor and 49 non-tumor tissues from 20 never smokers, 26 former smokers, and 28 current smokers.
2008-04-07 | E-GEOD-10072 | biostudies-arrayexpress
Project description:Objective: Neoadjuvant chemoimmunotherapy has improved outcomes in resectable non-small cell lung cancer (NSCLC), yet its real-world implementation is often challenged by surgical delays, cancellations, immune-related fibrosis, and increased postoperative complications. Smokers with NSCLC, despite being at higher risk for postoperative complications, have enhanced responses to neoadjuvant chemoimmunotherapy. This study aimed to identify smoking-associated immune cell determinants that could inform treatment strategies. Methods: Single-cell RNA sequencing was performed on 61 lung samples from non-smokers, smokers, and patients with chronic obstructive pulmonary disease (COPD), as well as 8 invasive lung adenocarcinomas, to define smoking-related immune signatures. Using RNA sequencing data from 102 resected NSCLC and 24 NSCLC patients treated with neoadjuvant chemoimmunotherapy, we conducted in silico deconvolution to evaluate associations between cellular composition and clinical outcomes. Results: Among 140 lung cellular phenotypes, two natural killer (NK) cell subsets were strongly associated with smoking and COPD severity. “Stress-responsive NK (NKSR)” cells exhibited immature features and cytokine-responsive signatures. “Exhausted NK (NKExh)” cells showed mature features and elevated multiple immune checkpoint expression (PDCD1, TIGIT, and LAG3). Abundant intratumoral NKSR cells were associated with significantly improved survival after surgery, particularly in current smokers. Conversely, tumors with low NKSR and high NKExh cell profiles were associated with better responses to neoadjuvant chemoimmunotherapy. Conclusions: Tumor-infiltrating NK cell phenotyping may aid in therapeutic stratification in smokers with NSCLC. NKSR cell preservation predicts favorable outcomes with upfront surgery, while NKExh cell enrichment indicates greater benefit from neoadjuvant chemoimmunotherapy. These profiles may help optimize treatment by balancing therapeutic benefit and risk.
2025-06-30 | GSE300685 | GEO
Project description:Because DNA methylation changes reliably with age, machine learning models called epigenetic clocks can estimate an individual’s age based on their DNA methylation profile. This epigenetic measure of age can deviate from one’s true age, and the difference between the epigenetic age and true age, known as epigenetic age acceleration (EAA), has been found to directly correlate with morbidity and mortality in adults. Emerging evidence suggests that EAA is also associated with aberrant health outcomes in children, making epigenetic clocks useful tools for studying aging and development. We developed two highly accurate epigenetic clocks for the rhesus macaque, utilizing 1,008 blood samples from 690 macaques between 2 days and 23.4 years of age with diverse genetic backgrounds and exposure to environmental conditions. The first clock, which is trained on all samples, achieves a Pearson correlation between true age and predicted age of 0.983 and median absolute error of 0.210 years. To study phenotypes during development, the second clock is optimized for macaques younger than 6 years and achieves a Pearson correlation of 0.974 and a median absolute error of 0.148 years. Using the latter clock, we investigated whether epigenetic aging is affected by early life adversity in the form of infant maltreatment. Our data suggests that maltreatment and increased hair cortisol levels are associated with epigenetic age acceleration right after the period of maltreatment.
2026-07-01 | GSE272604 | GEO
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
Project description:Cigarette smoke is associated with the majority of lung cancers: however, 25% of lung cancer patients are non-smokers, and half of all newly diagnosed lung cancer patients are former smokers. Lung tumors exhibit distinct epidemiological, clinical, pathological, and molecular features depending on smoking status, suggesting divergent mechanisms underlie tumorigenesis in smokers and non-smokers. MicroRNAs (miRNAs) are integral contributors to tumorigenesis and mediate biological responses to smoking. Based on the hypothesis that smoking-specific miRNA differences in lung adenocarcinomas reflect distinct tumorigenic processes selected by different smoking and non-smoking environments, we investigated the contribution of miRNA disruption to lung tumor biology and patient outcome in the context of smoking status. Results: We discovered novel and distinct smoking-status-specific patterns of miRNA and miRNA-mediated gene networks, and identified miRNAs that were prognostically significant in a smoking-dependent manner. Conclusions: We conclude that miRNAs disrupted in a smoking-status-dependent manner affect distinct cellular pathways and differentially influence lung cancer patient prognosis in current, former and never smokers. Our findings may represent promising biologically relevant markers for lung cancer prognosis or therapeutic intervention.
2014-10-30 | GSE62182 | GEO
Project description:Cigarette smoking is the major cause of cancers of the respiratory tract, including non-small cell lung cancer (NSCLC) and head and neck cancer (HNC). In order to better understand carcinogenesis of the lung and upper airways, we have compared the gene expression profiles of tumour-distant, histologically normal bronchial biopsy specimens obtained from current smokers with NSCLC or HNC (SC, considered as a single group), as well as non-smokers (NS) and smokers without cancer (SNC). RNA from a total of 97 biopsies was used for gene expression profiling (Affymetrix HG-U133 Plus 2.0 array). Differentially expressed genes were used to compare NS, SNC, and SC, and functional analysis was carried out using Ingenuity Pathway Analysis (IPA). Smoking-related cancer of the respiratory tract was found to affect the expression of genes encoding xenobiotic biotransformation proteins, as well as proteins associated with crucial inflammation/immunity pathways and other processes that protect the airway from the chemicals in cigarette smoke or contribute to carcinogenesis. Finally, we used the prediction analysis for microarray (PAM) method to identify gene signatures of cigarette smoking and cancer, and uncovered a 15-gene signature that distinguished between SNC and SC with an accuracy of 83%. Thus, gene profiling of histologically normal bronchial biopsy specimens provided insight into cigarette-induced carcinogenesis of the respiratory tract and gene-signatures of cancer in smokers.
2014-05-24 | E-MTAB-1690 | biostudies-arrayexpress
Project description:Lung cancer is the worldwide leading cause of death from cancer. Tobacco usage is the major pathogenic factor, however, not all lung cancers can be attributable to smoking. The genetic aberrations that differ between smokers' and never-smokers’ lung carcinomas remain to a large extent unclear. We analyzed 72 early-stage primary lung carcinomas including small cell lung cancers LCNEC, adenocarcinomas and squamous cell carcinomas by Illumina HT12 gene expression microarrays.
2012-05-17 | GSE29016 | GEO
Project description:Cystatin A (gene: CSTA), is up-regulated in non-small-cell lung cancer (NSCLC) and dysplastic vs normal human bronchial epithelium. In the context that chronic obstructive pulmonary disease (COPD), a small airway epithelium (SAE) disorder, is independently associated with NSCLC (especially squamous cell carcinoma, SCC), but only occurs in a subset of smokers, we hypothesized that genetic variation, smoking and COPD modulate CSTA gene expression levels in SAE, with further up-regulation in SCC. Gene expression was assessed by microarray in SAE of 178 individuals [healthy nonsmokers (n=60), healthy smokers (n=82), and COPD smokers (n=36)], with corresponding large airway epithelium (LAE) data in a subset (n=52). Blood DNA was genotyped by SNP microarray. Twelve SNPs upstream of the CSTA gene were all significantly associated with CSTA SAE gene expression (p<0.04 to 5 x 10-4). CSTA gene expression levels in SAE were higher in COPD smokers (28.4 ± 2.0) than healthy smokers (19.9 ± 1.4, p<10-3), who in turn had higher levels than nonsmokers (16.1 ± 1.1, p<0.04). CSTA LAE gene expression was also smoking-responsive (p<10-3). Using comparable publicly available NSCLC expression data, CSTA was up-regulated in SCC vs LAE (p<10-2) and down-regulated in adenocarcinoma vs SAE (p<10-7). All phenotypes were associated with significantly different proportional gene expression of CSTA to cathepsins. The data demonstrate that regulation of CSTA expression in human airway epithelium is influenced by genetic variability, smoking, and COPD, and is further up-regulated in SCC, all of which should be taken into account when considering the role of CSTA in NSCLC pathogenesis.
2012-06-20 | GSE22047 | GEO
Project description:There are inherited genetic factors that cause different responses to cigarette smoking exposure among individuals. We tried to identify these differences in heavy smokers by examining copy number variations (CNVs) between lung cancer patients and healthy controls. To rule out the CNVs infulenced by age, smoking history and sex, those were matched in both groups.
2011-01-10 | GSE25528 | GEO