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Series GSE72192 Query DataSets for GSE72192
Status Public on Aug 20, 2015
Title Combined clinical and genomic signatures for the prognosis of early stage non-small cell lung cancer based on gene copy number alterations [Affymetrix]
Organism Homo sapiens
Experiment type Genome variation profiling by SNP array
Summary Background: The development of a more refined prognostic methodology for early non-small cell lung cancer (NSCLC) is an unmet clinical need. An accurate prognostic tool might help to select patients at early stages for adjuvant therapies. Results: A new integrated bioinformatics searching strategy, that combines gene copy number alterations and expression, together with clinical parameters was applied to derive two prognostic genomic signatures. The proposed methodology combines data from patients with and without clinical data with a priori information on the ability of a gene to be a prognostic marker. Two initial candidate sets of 513 and 150 genes for lung adenocarcinoma (ADC) and squamous cell carcinoma (SCC), respectively, were generated by identifying genes which have both: a) significant correlation between copy number and gene expression, and b) significant prognostic value at the gene expression level in external databases. From these candidates, two panels of 7 (ADC) and 5 (SCC) genes were further identified via semi-supervised learning. These panels, together with clinical data (stage, age and sex), were used to construct the ADC and SCC hazard scores combining clinical and genomic data. The signatures were validated in two independent datasets (n=73 for ADC, n=97 for SCC), confirming that the prognostic value of both clinical-genomic models is robust, statistically significant (P=0.008 for ADC and P=0.019 for SCC) and outperforms both the clinical models (P=0.060 for ADC and P=0.121 for SCC) and the genomic models applied separately (P=0.350 for ADC and P=0.269 for SCC). Conclusion: The present work provides a methodology to generate a robust signature using copy number data that can be potentially used to any cancer. Using it, we found new prognostic scores based on DNA s that, jointly with clinical information, are able to predict overall survival (OS) in patients with early-stage ADC and SCC.
 
Overall design Copy number analysis of Affymetrix 500K SNP arrays was performed in autosomal chromosomes for 39 early stage Non-Small Cell Lung Cancer (NSCLC) patients
 
Contributor(s) Montuenga L
Citation(s) 26444668
Submission date Aug 19, 2015
Last update date May 17, 2017
Contact name Angel Rubio
E-mail(s) arubio@ceit.es
Organization name CEIT
Department Bioinformatics
Street address Paseo Mikeletegi, Nº 48
City San Sebastian
State/province GUIPÚZCOA
ZIP/Postal code 20009
Country Spain
 
Platforms (2)
GPL3718 [Mapping250K_Nsp] Affymetrix Mapping 250K Nsp SNP Array
GPL3720 [Mapping250K_Sty] Affymetrix Mapping 250K Sty2 SNP Array
Samples (78)
GSM1857240 Early stage lung adenocarcinoma sample BN03_Nsp
GSM1857241 Early stage lung adenocarcinoma sample BN04_Nsp
GSM1857242 Early stage lung adenocarcinoma sample BN05_Nsp
This SubSeries is part of SuperSeries:
GSE72195 Combined clinical and genomic signatures for the prognosis of early stage non-small cell lung cancer based on gene copy number alterations
Relations
BioProject PRJNA293340

Download family Format
SOFT formatted family file(s) SOFTHelp
MINiML formatted family file(s) MINiMLHelp
Series Matrix File(s) TXTHelp

Supplementary file Size Download File type/resource
GSE72192_Affy_Genedata_Ensembl54.txt.gz 405.4 Kb (ftp)(http) TXT
GSE72192_RAW.tar 1.8 Gb (http)(custom) TAR (of CEL)
Processed data included within Sample table
Processed data are available on Series record
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