Deciphering Genomic Underpinnings of Quantitative MRI-based Radiomic Phenotypes of Invasive Breast Carcinoma

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 (T...

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Bibliographic Details
Published in:Scientific reports 2015-12, Vol.5 (1), p.17787-17787, Article 17787
Main Authors: Zhu, Yitan, Li, Hui, Guo, Wentian, Drukker, Karen, Lan, Li, Giger, Maryellen L., Ji, Yuan
Format: Article
Language:English
Subjects:
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631/114/2164
631/114/2401
692/4028/67/1347
692/4028/67/2321
692/4028/67/69
Blood flow
Breast cancer
Breast carcinoma
Breast Neoplasms - diagnostic imaging
Breast Neoplasms - genetics
Breast Neoplasms - pathology
Copy number
Deoxyribonucleic acid
DNA
Female
Gene expression
Genetic Association Studies
Genome, Human
Genomes
Humanities and Social Sciences
Humans
Magnetic resonance imaging
Magnetic Resonance Imaging - methods
MicroRNAs - genetics
MicroRNAs - metabolism
miRNA
multidisciplinary
Mutation - genetics
Neoplasm Invasiveness
NMR
Nuclear magnetic resonance
Phenotype
Radiography
Radiomics
Science
Transcription
Transcription, Genetic
Tumors
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Summary: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.
ISSN:2045-2322
2045-2322
DOI:10.1038/srep17787