Diversity of gene expression in adenocarcinoma of the lung.
Ontology highlight
ABSTRACT:
SUBMITTER: Garber ME
PROVIDER: S-EPMC61119 | biostudies-literature | 2001 Nov
REPOSITORIES: biostudies-literature
Publications
Diversity of gene expression in adenocarcinoma of the lung.
Garber M E ME Troyanskaya O G OG Schluens K K Petersen S S Thaesler Z Z Pacyna-Gengelbach M M van de Rijn M M Rosen G D GD Perou C M CM Whyte R I RI Altman R B RB Brown P O PO Botstein D D Petersen I I
Proceedings of the National Academy of Sciences of the United States of America 20011113 24
The global gene expression profiles for 67 human lung tumors representing 56 patients were examined by using 24,000-element cDNA microarrays. Subdivision of the tumors based on gene expression patterns faithfully recapitulated morphological classification of the tumors into squamous, large cell, small cell, and adenocarcinoma. The gene expression patterns made possible the subclassification of adenocarcinoma into subgroups that correlated with the degree of tumor differentiation as well as patie ...[more]
Similar Datasets
Project description:The global gene expression profiles for 67 human lung tumors representing 56 patients were examined by using 24,000-element cDNA microarrays. Subdivision of the tumors based on gene expression patterns faithfully recapitulated morphological classification of the tumors into squamous, large cell, small cell, and adenocarcinoma. The gene expression patterns made possible the subclassification of adenocarcinoma into subgroups that correlated with the degree of tumor differentiation as well as patient survival. Gene expression analysis thus promises to extend and refine standard pathologic analysis. Set of arrays organized by shared biological context, such as organism, tumors types, processes, etc. Computed
2005-09-30 | E-GEOD-3398 | biostudies-arrayexpress
Project description:The global gene expression profiles for 67 human lung tumors representing 56 patients were examined by using 24,000-element cDNA microarrays. Subdivision of the tumors based on gene expression patterns faithfully recapitulated morphological classification of the tumors into squamous, large cell, small cell, and adenocarcinoma. The gene expression patterns made possible the subclassification of adenocarcinoma into subgroups that correlated with the degree of tumor differentiation as well as patient survival. Gene expression analysis thus promises to extend and refine standard pathologic analysis. Set of arrays organized by shared biological context, such as organism, tumors types, processes, etc. Keywords: Logical Set
2005-09-30 | GSE3398 | GEO
Project description:The present study screened potential genes related to lung adenocarcinoma, with the aim of further understanding disease pathogenesis. The GSE2514 dataset including 20 lung adenocarcinoma and 19 adjacent normal tissue samples from 10 patients with lung adenocarcinoma aged 45-73 years was downloaded from Gene Expression Omnibus. Differentially expressed genes (DEGs) between the two groups were screened using the t-test. Potential gene functions were predicted using functional and pathway enrichment analysis, and protein-protein interaction (PPI) networks obtained from the STRING database were constructed with Cytoscape. Module analysis of PPI networks was performed through MCODE in Cytoscape. In total, 535 upregulated and 465 downregulated DEGs were identified. These included ATP5D, UQCRC2, UQCR11 and genes encoding nicotinamide adenine dinucleotide (NADH), which are mainly associated with mitochondrial ATP synthesis coupled electron transport, and which were enriched in the oxidative phosphorylation pathway. Other DEGs were associated with DNA replication (PRIM1, MCM3, and RNASEH2A), cell surface receptor-linked signal transduction and the enzyme-linked receptor protein signaling pathway (MAPK1, STAT3, RAF1, and JAK1), and regulation of the cytoskeleton and phosphatidylinositol signaling system (PIP5K1B, PIP5K1C, and PIP4K2B). Our findings suggest that DEGs encoding subunits of NADH, PRIM1, MCM3, MAPK1, STAT3, RAF1, and JAK1 might be associated with the development of lung adenocarcinoma.
| S-EPMC4763816 | biostudies-literature
Project description:Mining disease-related genes contributes momentously to handling lung adenocarcinoma (LUAD). But genetic complexity and tumor heterogeneity severely get in the way. Fortunately, new light has been shed by dramatic progress of bioinformatic technology in the past decades. In this research, we investigated relationships between gene expression and clinical features of LUAD via integrative bioinformatic analysis. First, we applied limma and DESeq2 packages to analyze differentially expressed genes (DEGs) of LUAD from GEO database and TCGA project (tumor tissues versus normal tissues), and acquired 180 down-regulated DEGs and 52 up-regulated DEGs. Then, we investigated genetic and biological assignment of theses DEGs by Bioconductor packages and STRING database. We found these DEGs were distributed dispersedly among chromosomes, enriched observably in extracellular matrix-related processes, and weighted hierarchically in interaction network. Finally, we established DEGs-based statistical models for evaluating TNM stage and survival status of LUAD. And these models (logistic regression models for TNM parameter and Cox regression models for survival probability) all possessed fine predictive efficacy (C-indexes: T, 0.740; N, 0.687; M, 0.823; overall survival, 0.678; progression-free survival, 0.611). In summary, we have successfully established gene expression-based models for assessing clinical characteristics of LUAD, which will assist its pathogenesis investigation and clinical intervention.
| S-EPMC7467359 | biostudies-literature
Project description:IntroductionA deeper understanding of intratumoral heterogeneity is essential for prognosis prediction or accurate treatment plan decisions in clinical practice. However, due to the cross-links and degradation of biomolecules within formalin-fixed paraffin-embedded (FFPE) specimens, it is challenging to analyze them. In this study, we aimed to optimize the simultaneous extraction of mRNA and DNA from microdissected FFPE tissues (φ = 100 µm) and apply the method to analyze tumor diversity in lung adenocarcinoma before and after erlotinib administration.MethodTwo magnetic beads were used for the simultaneous extraction of mRNA and DNA. The decross-linking conditions were evaluated for gene mutation and gene expression analyses of microdissected FFPE tissues. Lung lymph nodes before treatment and lung adenocarcinoma after erlotinib administration were collected from the same patient and were preserved as FFPE specimens for 4 years. Gene expression and gene mutations between histologically classified regions of lung adenocarcinoma (pre-treatment tumor in lung lymph node biopsies and post-treatment tumor, normal lung, tumor stroma, and remission stroma, in resected lung tissue) were compared in a microdissection-based approach.ResultsUsing the optimized simultaneous extraction of DNA and mRNA and whole-genome amplification, we detected approximately 4,000-10,000 expressed genes and the epidermal growth factor receptor (EGFR) driver gene mutations from microdissected FFPE tissues. We found the differences in the highly expressed cancer-associated genes and the positive rate of EGFR exon 19 deletions among the tumor before and after treatment and tumor stroma, even though they were collected from tumors of the same patient or close regions of the same specimen.ConclusionOur integrated spatial analysis method would be applied to various FFPE pathology specimens providing area-specific gene expression and gene mutation information.
| S-EPMC9731154 | biostudies-literature
Project description:Lung adenocarcinoma UNC0638 gene expression
| PRJNA491480 | ENA
Project description:BackgroundLung cancer is the leading cause of cancer-related death worldwide. Tremendous research efforts have been devoted to improving treatment procedures, but the average five-year overall survival rates are still less than 20%. Many biomarkers have been identified for predicting survival; challenges arise, however, in translating the findings into clinical practice due to their inconsistency and irreproducibility. In this study, we proposed an approach by identifying predictive genes through pathways.ResultsThe microarrays from Shedden et al. were used as the training set, and the log-rank test was performed to select potential signature genes. We focused on 24 cancer-related pathways from 4 biological databases. A scoring scheme was developed by the Cox hazard regression model, and patients were divided into two groups based on the medians. Subsequently, their predictability and generalizability were evaluated by the 2-fold cross-validation and a resampling test in 4 independent datasets, respectively. A set of 16 genes related to apoptosis execution was demonstrated to have good predictability as well as generalizability in more than 700 lung adenocarcinoma patients and was reproducible in 4 independent datasets. This signature set was shown to have superior performances compared to 6 other published signatures. Furthermore, the corresponding risk scores derived from the set were found to associate with the efficacy of the anti-cancer drug ZD-6474 targeting EGFR.ConclusionsIn summary, we presented a new approach to identify reproducible survival predictors for lung adenocarcinoma, and the identified genes may serve as both prognostic and predictive biomarkers in the future.
| S-EPMC3877965 | biostudies-literature
Project description:Individual variations in the transcriptional profile of normal lung tissue may reflect the lung ADCA patients’ predisposition to a specific clinical stage Associations between clinical outcome of cancer patients and the gene expression signature in primary tumors at time of diagnosis have been reported. To test whether gene expression patterns in the normal tissue surrounding the cancerous tissue might correlate with clinical stage, we compared transcriptome of normal lung samples of adenocarcinoma (ADCA) smoker patients of clinical stage I versus stage >I, and identified 55 differentially expressed genes. Eight out of 10 genes validated by quantitative real-time PCR confirmed statistical association with clinical stage, with 6 genes downregulated in high clinical stage patients, including the TMEM100 gene showing the best statistical association. Five of these 6 genes were also downregulated in lung ADCA tissue as compared to normal tissue. Functional studies in vitro indicated that four of them (SLC14A1, SMAD6, TMEM100, and TXNIP) inhibited colony formation when over-expressed by transfection in lung cancer cell lines, suggesting their potential tumor-suppressor activity. Our findings indicated that individual variations in the transcriptional profile of normal lung tissue may reflect the lung ADCA patients’ predisposition to a specific clinical stage. The 120 RNA samples from normal lung were combined in 24 small pools, with 12 pools constituted by stage I patients and 12 pools by stage >I patients (5 samples per pool)
| S-ECPF-GEOD-31267 | biostudies-other
Project description:Many studies support a stepwise continuum of morphologic changes between atypical adenomatous hyperplasia (AAH) and lung adenocarcinoma (ADC). Here we characterized gene expression patterns and the association of differentially expressed genes and immune tumor microenvironment behaviors in AAH to ADC during ADC development. Tumor tissues from nine patients with ADC and synchronous multiple ground glass nodules/lesions (GGN/Ls) were analyzed using RNA sequencing. Using clustering, we identified genes differentially and sequentially expressed in AAH and ADC compared to normal tissues. Functional enrichment analysis using gene ontology terms was performed, and the fraction of immune cell types was estimated. We identified up-regulated genes (ACSL5 and SERINC2) with a stepwise change of expression from AAH to ADC and validated those expressions by quantitative PCR and immunohistochemistry. The immune cell profiles revealed increased B cell activities and decreased natural killer cell activities in AAH and ADC. A stepwise change of differential expression during ADC development revealed potential effects on immune function in synchronous precursors and in tumor lesions in patients with lung cancer.
| S-EPMC8700398 | biostudies-literature
Project description:Gene expression profiling of 60 lung adenocarcinoma tumors and their matched histologically normal adjacent lung tissue samples were analyzed using Illumina HumanWG-6 v3.0 expression beadchip. We integrated these data with DNA methylation profiles of the same samples to identify potential DNA methylation regulated genes. Lung cancer is the leading cause of cancer death worldwide and adenocarcinoma is its most common histological subtype. Clinical and molecular evidence indicates that lung adenocarcinoma is a heterogeneous disease, which has important implications for treatment. Here we performed genome-scale DNA methylation profiling using the Illumina Infinium HumanMethylation27 platform on 59 matched lung adenocarcinoma/non-tumor lung samples, with genome-scale verification on an independent set of tissues. We identified 766 genes showing altered DNA methylation between tumors and non-tumor lung. By integrating DNA methylation and mRNA expression data, we identified 164 hypermethylated genes showing concurrent downregulation, and 57 hypomethylated genes showing increased expression. Integrated pathways analysis indicates that these genes are involved in cell differentiation, epithelial to mesenchymal transition, RAS and WNT signaling pathways and cell cycle regulation, among others. Comparison of DNA methylation profiles between lung adenocarcinomas of current and never-smokers showed modest differences, identifying only LGALS4 as significantly hypermethylated and downregulated in smokers. LGALS4, encoding a galactoside-binding protein involved in cell-cell and cell-matrix interactions, was recently shown to be a tumor-suppressor in colorectal cancer. Unsupervised analysis of the DNA methylation data identified two tumor subgroups, one of which showed increased DNA methylation and was significantly associated with KRAS mutation and to a lesser extent, with smoking. Our analysis lays the groundwork for further molecular studies of lung adenocarcinoma by providing new candidate DNA methylation biomarkers for early detection, identifying novel molecular alterations potentially involved in lung adenocarcinoma development/progression, and describing an epigenetic subgroup of lung adenocarcinoma associated with KRAS mutation. 58 lung adenocarcinoma and 58 adjacent non-tumor lung fresh frozen tissues were macrodissected, and total RNA was isolated to be analyzed using the Illumina HumanWG-6 v3.0 expression beadchip.
| S-ECPF-GEOD-32863 | biostudies-other