Gene Expression Nebulas
A data portal of transcriptomic profiles across multiple species

Gene Expression Nebulas

A data portal of transcriptome profiles across multiple species

PRJNA401995: Identification of relationships between Molecular and Imaging Phenotypes in Non-small cell lung cancer using radiogenomics Map

Source: NCBI / GSE103584
Submission Date: Sep 07 2017
Release Date: Aug 03 2018
Update Date: May 15 2019

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

GEN Datasets:
GEND000176
Strategy:
Species:
Tissue:
Healthy Condition:
Protocol
Growth Protocol: -
Treatment Protocol: -
Extract Protocol: For library preparation, the TruSeq Total Stranded RNA with Ribo-Zero Reduction (Illumina) was used following manufacturer’s instructions.
Library Construction Protocol: For library preparation, the TruSeq Total Stranded RNA with Ribo-Zero Reduction (Illumina) was used following manufacturer’s instructions.
Sequencing
Molecule Type: rRNA- RNA
Library Source:
Library Layout: PAIRED
Library Strand: Forward
Platform: ILLUMINA
Instrument Model: Illumina Hiseq 2500
Strand-Specific: Specific
Publications
A radiogenomic dataset of non-small cell lung cancer.
Scientific data . 2018-10-16 [PMID: 30325352]
Samples
Basic Information:
Sample Characteristic:
Biological Condition:
Experimental Variables:
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Analysis:
Data Resource GEN Sample ID GEN Dataset ID Project ID BioProject ID Sample ID Sample Name BioSample ID Sample Accession Experiment Accession Release Date Submission Date Update Date Species Race Ethnicity Age Age Unit Gender Source Name Tissue Cell Type Cell Subtype Cell Line Disease Disease State Development Stage Mutation Phenotype Case Detail Control Detail Growth Protocol Treatment Protocol Extract Protocol Library Construction Protocol Molecule Type Library Layout Strand-Specific Library Strand Spike-In Strategy Platform Instrument Model Cell Number Reads Number Gbases AvgSpotLen1 AvgSpotLen2 Uniq Mapping Rate Multiple Mapping Rate Coverage Rate