Database Commons
Database Commons

a catalog of worldwide biological databases

Database Profile

Radiogenomics

General information

URL: http://compgenome.org/Radiogenomics
Full name: Integration and Analysis of Cancer Genomics and Imaging Data for Improving Cancer Research and Treatment
Description: A comprehensive radiogenomic study of breast invasive carcinoma based on the integration of The Cancer Imaging Archive (TCIA)12 and The Cancer Genome Atlas (TCGA) is presented. Quantitative MRI phenotypes of tumors (such as tumor size, shape, margin, and blood flow kinetics) were associated with their corresponding molecular profiles. These findings pave potential paths for the discovery of genetic mechanisms regulating specific tumor phenotypes and for improving MRI techniques as potential non-invasive approaches to probe the cancer molecular status.
Year founded: 2015
Last update:
Version:
Accessibility:
Accessible
Country/Region: United States

Contact information

University/Institution: University of Chicago
Address: Department of Public Health Sciences, The University of Chicago, Chicago, Illinois, USA
City: Chicago
Province/State: Illinois
Country/Region: United States
Contact name (PI/Team): Yuan Ji
Contact email (PI/Helpdesk): koaeraser@gmail.com

Publications

26639025
Deciphering Genomic Underpinnings of Quantitative MRI-based Radiomic Phenotypes of Invasive Breast Carcinoma. [PMID: 26639025]
Zhu Y, Li H, Guo W, Drukker K, Lan L, Giger ML, Ji Y.

Magnetic Resonance Imaging (MRI) has been routinely used for the diagnosis and treatment of breast cancer. However, the relationship between the MRI tumor phenotypes and the underlying genetic mechanisms remains under-explored. We integrated multi-omics molecular data from The Cancer Genome Atlas (TCGA) with MRI data from The Cancer Imaging Archive (TCIA) for 91 breast invasive carcinomas. Quantitative MRI phenotypes of tumors (such as tumor size, shape, margin, and blood flow kinetics) were associated with their corresponding molecular profiles (including DNA mutation, miRNA expression, protein expression, pathway gene expression and copy number variation). We found that transcriptional activities of various genetic pathways were positively associated with tumor size, blurred tumor margin, and irregular tumor shape and that miRNA expressions were associated with the tumor size and enhancement texture, but not with other types of radiomic phenotypes. We provide all the association findings as a resource for the research community (available at http://compgenome.org/Radiogenomics/). These findings pave potential paths for the discovery of genetic mechanisms regulating specific tumor phenotypes and for improving MRI techniques as potential non-invasive approaches to probe the cancer molecular status.

Sci Rep. 2015:5() | 121 Citations (from Europe PMC, 2026-04-04)

Ranking

All databases:
1220/6932 (82.415%)
Raw bio-data:
88/587 (85.179%)
Genotype phenotype and variation:
167/1012 (83.597%)
Expression:
237/1361 (82.66%)
Pathway:
72/454 (84.361%)
Metadata:
115/723 (84.232%)
1220
Total Rank
116
Citations
10.545
z-index

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Record metadata

Created on: 2018-01-28
Curated by:
Lin Liu [2022-08-16]
Sidra Younas [2018-04-12]
Meiye Jiang [2018-01-28]