 |
 |
GEO help: Mouse over screen elements for information. |
|
| Status |
Public on Aug 03, 2018 |
| Title |
Identification of relationships between Molecular and Imaging Phenotypes in Non-small cell lung cancer using radiogenomics Map |
| Organism |
Homo sapiens |
| Experiment type |
Expression profiling by high throughput sequencing
|
| Summary |
Purpose: To create a radiogenomic map linking computed tomographic (CT) image features and gene expression profiles generated by RNA sequencing for patients with non-small cell lung cancer (NSCLC).
Methods: A cohort of 113 patients with NSCLC diagnosed between April 2008 and September 2014 who had preoperative CT data and tumor tissue available was studied. For each tumor, a thoracic radiologist recorded 87 semantic image features, selected to reflect radiologic characteristics of nodule shape, margin, texture, tumor environment, and overall lung characteristics. Next, total RNA was extracted from the tissue and analyzed with RNA sequencing technology. Ten highly coexpressed gene clusters, termed metagenes, were identified, validated in publicly available gene-expression cohorts, and correlated with prognosis. Next, a radiogenomics map was built that linked semantic image features to metagenes by using the t statistic and the Spearman correlation metric with multiple testing correction.
Results: RNA sequencing analysis resulted in 10 metagenes that capture a variety of molecular pathways, including the epidermal growth factor (EGF) pathway. A radiogenomic map was created with 32 statistically significant correlations between semantic image features and metagenes.
Conclusions: Radiogenomic analysis of NSCLC showed multiple associations between semantic image features and metagenes that represented canonical molecular pathways
|
| |
|
| Overall design |
We studied 130 cases of NSCLC with CT, PET/CT and RNASeq 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 centrillion genomic services using Illumina Hiseq 2500
|
| |
|
| Contributor(s) |
Bakr S, Gevaert O, Plevritis S |
| Citation(s) |
30325352 |
| Submission date |
Sep 07, 2017 |
| Last update date |
May 17, 2019 |
| Contact name |
Shaimaa Bakr |
| E-mail(s) |
sbakr@stanford.edu
|
| Organization name |
Stanford University
|
| Department |
Electrical Engineering
|
| Street address |
4450 Serra Mall, Stanford, CA 94305
|
| City |
Stanford |
| State/province |
CA |
| ZIP/Postal code |
94305 |
| Country |
USA |
| |
|
| Platforms (1) |
| GPL16791 |
Illumina HiSeq 2500 (Homo sapiens) |
|
| Samples (130)
|
|
| Relations |
| BioProject |
PRJNA401995 |
| SRA |
SRP117020 |
| Supplementary file |
Size |
Download |
File type/resource |
| GSE103584_R01_NSCLC_RNAseq.txt.gz |
6.8 Mb |
(ftp)(http) |
TXT |
SRA Run Selector |
| Raw data are available in SRA |
| Processed data are available on Series record |
|
|
|
|
 |
Less...
More...