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CaArray_beer-00153: Gene-expression profiles predict survival of patients with lung adenocarcinoma

ABSTRACT: Histopathology is insufficient to predict disease progression and clinical outcome in lung adenocarcinoma. Here we show that gene-expression profiles based on microarray analysis can be used to predict patient survival in early-stage lung adenocarcinomas. Genes most related to survival were identified with univariate Cox analysis. Using either two equivalent but independent training and testing sets, or 'leave-one-out' cross-validation analysis with all tumors, a risk index based on the top 50 genes identified low-risk and high-risk stage I lung adenocarcinomas, which differed significantly with respect to survival. This risk index was then validated using an independent sample of lung adenocarcinomas that predicted high- and low-risk groups. This index included genes not previously associated with survival. The identification of a set of genes that predict survival in early-stage lung adenocarcinoma allows delineation of a high-risk group that may benefit from adjuvant therapy.

ORGANISM(S): Homo sapiens

PROVIDER: GSE68571 | GEO | 2015/05/06

SECONDARY ACCESSION(S): PRJNA283120

REPOSITORIES: GEO

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caArray_beer-00153: Gene-expression profiles predict survival of patients with lung adenocarcinoma

Project description:Histopathology is insufficient to predict disease progression and clinical outcome in lung adenocarcinoma. Here we show that gene-expression profiles based on microarray analysis can be used to predict patient survival in early-stage lung adenocarcinomas. Genes most related to survival were identified with univariate Cox analysis. Using either two equivalent but independent training and testing sets, or 'leave-one-out' cross-validation analysis with all tumors, a risk index based on the top 50 genes identified low-risk and high-risk stage I lung adenocarcinomas, which differed significantly with respect to survival. This risk index was then validated using an independent sample of lung adenocarcinomas that predicted high- and low-risk groups. This index included genes not previously associated with survival. The identification of a set of genes that predict survival in early-stage lung adenocarcinoma allows delineation of a high-risk group that may benefit from adjuvant therapy. beer-00153 Assay Type: Gene Expression Provider: Affymetrix Array Designs: Hu6800 Organism: Homo sapiens (ncbitax) Disease States: lung cancer, normal

2015-05-06 | E-GEOD-68571 | biostudies-arrayexpress

caArray_jacob-00182: Gene expression-based survival prediction in lung adenocarcinoma: a multi-site, blinded validation study

Project description:Here we report a large, training*testing, multi-site, blinded validation study to characterize the performance of several prognostic models based on gene expression for 442 lung adenocarcinomas. The hypotheses proposed examined whether microarray measurements of gene expression either alone or combined with basic clinical covariates (stage, age, sex) could be used to predict overall survival in lung cancer subjects. Several models examined produced risk scores that substantially correlated with actual subject outcome. Most methods performed better with clinical data, supporting the combined use of clinical and molecular information when building prognostic models for early-stage lung cancer. This study also provides the largest available set of microarray data with extensive pathological and clinical annotation for lung adenocarcinomas. jacob-00182 Assay Type: Gene Expression Provider: Affymetrix Array Designs: HG-U133A Organism: Homo sapiens (ncbitax) Material Types: cell, synthetic_RNA, organism_part, whole_organism, total_RNA Disease States: Lung Adenocarcinoma

2015-05-02 | E-GEOD-68465 | biostudies-arrayexpress

caArray_jacob-00182: Gene expression-based survival prediction in lung adenocarcinoma: a multi-site, blinded validation study

2015-05-02 | GSE68465 | GEO

Proteomic analyses identify dysregulated proteins and pathways between low-risk and high-risk subtype of early-stage lung adenocarcinoma and their prognostic impacts

Project description:Proteomic analyses identify dysregulated proteins and pathways between low-risk and high-risk subtype of early-stage lung adenocarcinoma and their prognostic impacts.Sample labels: A,low-risk tumor;B,low-risk normal;C,high-risk tumor;D,high-risk normal.

2020-07-18 | MSV000085775 | MassIVE

Exon Level Expression Profiling analysis of early stage NSCLC suffering rapidly relapse

Project description:Postoperative recurrence is the main cause of poor prognosis in early stage lung adenocarcinoma (LUAD). Factors that can predict recurrence risk are critically needed.we designed a screening procedure based on gene profile data.The differentially expressed genes (DEGs) between patients with recurrence-free survival (RFS)<1 year and RFS>3 years were found.Cox proportional hazards model, IHC and Kaplan-Meier survival analysis were preformed to validate these biomarkers in TCGA and Daping validation sets.

2018-10-27 | GSE121841 | GEO

A Gene Expression Signature to Predict Metastasis and Survival in Non-small Cell Lung Cancer

Project description:Background: Current histopathological methods are inadequate for predicting outcome and recurrence in patients with non-small cell lung carcinoma (NSCLC) after surgery. In this study, we investigated the use of gene expression signatures to predict outcome and metastasis in lung cancer patients. Methods: Gene expression was studied by microarray and the real-time reverse transcriptase polymerase chain reaction (RT-PCR) in normal and lung tumor tissue of 188 NSCLC patients who underwent surgical resection. The 5 cancer-related genes and 1 reference gene expression levels measureed by real-time RT-PCR were used in a prospectively defined algorithm to determine the risk for each patient. Finally, we used an independent cohort to verify the 5 gene-based predictive model derived from decision tree analysis. Results: The 5 gene-based decision tree model was able to predict the prognosis. The recurrence rate at 36 months was 53% in the low-risk group versus 83% in the high-risk group (P=0.002). The 5 gene-based model could also predict overall survival (P<0.001). In multivariate analysis, the decision tree model predicted that high-low dichotomy and stage were both significant for recurrence. In addition, it could also predict metastasis and survival of NSCLC patients within the stage I-II subgroups. A similar result was found using an independent cohort of NSCLC patients. The high-risk patients had a significantly poorer overall survival than the low-risk patients (P=0.005). We also found distinct gene signatures which could distinguish between NSCLC, and normal tissue and histology subtypes. Conclusions: A gene expression signature can predict metastasis and survival of NSCLC patients. Keywords: Survival and metastasis analysis

2006-06-07 | GSE4882 | GEO

CCL171, T47D, MDA-MB231 cell lines: stimulation with BMP7 and antagonists

Project description:Methods: We used an ex vivo culture model and measured gene expression changes in human lung fibroblasts after stimulation with BMPs and their antagonists using HEEBO microarrays. The in vitro data were correlated with in vivo observations in published expression datasets of human lung adenocarcinomas. Results: We have systematically analyzed the response to BMP2, BMP4, BMP7 and their antagonists, gremlin and noggin, to define common and specific gene expression patterns. A BMP2 induced gene expression signature was defined, which is specific for stromal fibroblasts. Gene expression profiles from lung adenocarcinoma biopsies were analyzed to determine the prognostic significance of the Fibroblast specific BMP2 induced gene list. This gene list successfully segregated patients with different prognostic outcome in 3 datasets. In a small dataset (Garber et al.) there was a strong trend for a worse prognosis of patients with adenocarcinomas of all stages over-expressing the Fibroblast specific BMP2 induced gene list. In two larger datasets with stage I adenocarcinomas we observed a significantly worse disease-free (p=0.002, Lee et al. and p=0.002, Bhattacharjee et al.) and overall survival (p=0.0002). Conclusions: The effects of BMPs and their antagonists are heterogeneous in different cell types. The gene expression pattern induced by BMP2 in primary lung fibroblasts may predict outcomes of patients with lung adenocarcinomas. A stimulus or stress experiment design type is where that tests response of an organism(s) to stress/stimulus. e.g. osmotic stress, behavioral treatment stimulus_or_stress_design

2016-02-19 | E-GEOD-66108 | biostudies-arrayexpress

MERLION LUNG CANCER STUDY

2009-01-01 | GSE10445 | GEO

LC/MS-based FFPE tissue-proteomic analyses of early lung adenocarcinoma

Project description:Clinical FFPE tissue proteomic analyses were performed for early lung adenocarcinomas including adenocarcinoma in-situ (AIS), minimally invasive adenocarcinoma (MIA) and lepidic predominant invasive adenocarcinoma (LPA).

2020-01-30 | PXD017334 | JPOST Repository

Transcription profiling of human stage IB lung adenocarcinomas and large cell carcinomas to predict outcomes (Merlion lung cancer study)

Project description:Series of stage IB lung adenocarcinomas and large cell carcinomas. The aim of the study was to predict outcome using a Copy Number Driven Gene Expression signature. Experiment Overall Design: Homogeneous series of 72 cases of lung primary stage IB adenocarcinomas/large cell carcinomas, analyzed using the Human U133Plus 2.0 oligonucleotide arrays (Affymetrix, Santa Clara, CA).

2009-01-14 | E-GEOD-10445 | biostudies-arrayexpress

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