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Series GSE28827 Query DataSets for GSE28827
Status Public on Jun 01, 2012
Title Rapid identification of prognostic imaging biomarkers for non-small cell lung cancer by leveraging public gene expression microarray data
Organism Homo sapiens
Experiment type Expression profiling by array
Summary To rapidly identify new prognostic imaging biomarkers, we propose a bioinformatics approach that integrates gene expression and image data and leverages public gene expression data. We demonstrate our approach in non-small cell lung carcinoma patients for whom CT, PET/CT and gene expression data are available but without clinical follow-up. We extracted 180 image features and 56 high quality gene expression clusters, represented by metagenes. 115 image features were expressed in terms of metagenes, using sparse linear regression and cross-validation, with an accuracy of 65-86%. After mapping the signatures to a public gene expression dataset, 26 image features were significantly associated with recurrence-free survival and 22 with overall survival. A multivariate analysis identified multiple image features that were prognostic, independent of clinical covariates. Identifying prognostic imaging biomarkers by linking images and gene expression with outcomes in public gene expression datasets promises to accelerate the role of imaging in personalized medicine.
Overall design We studied 26 cases of NSCLC with both PET/CT and microarray data under IRB approval from Stanford University and the Veterans Administration Palo Alto Health Care System. The collection of tissue samples consisted of a distribution of poorly- to well-differentiated adenocarcinomas and squamous cell cancers. The surgeon had removed necrotic debris during excision and sampled cavitary lesions to include as much solid component as practical. Then, from the excised tumor, he cut a 3 to 5 mm thick slice along its longest axis, and froze it within 30 minutes of excision. We retrieved the frozen tissue and extracted the RNA that was then processed by the Stanford Functional Genomics Facility using Illumina Whole Genome Bead Chips (Human HT-12 v3.0)
Contributor(s) Gevaert O, Plevritis S
Citation(s) 22723499, 22710433
Submission date Apr 25, 2011
Last update date Aug 16, 2018
Contact name Olivier Gevaert
Phone 6507212378
Organization name Stanford University
Department Medicine
Lab Gevaert Lab
Street address 1265 Welch Road
City Stanford
State/province CA
ZIP/Postal code 94305-5479
Country USA
Platforms (1)
GPL6947 Illumina HumanHT-12 V3.0 expression beadchip
Samples (26)
GSM714044 Patient 1 (non small cell lung carcinoma)
GSM714045 Patient 2 (non small cell lung carcinoma)
GSM714046 Patient 3 (non small cell lung carcinoma)
BioProject PRJNA138787

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
GSE28827_RAW.tar 6.2 Mb (http)(custom) TAR
GSE28827_matrix_non-normalized.txt.gz 7.6 Mb (ftp)(http) TXT
Raw data are available on Series record
Processed data included within Sample table

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