Breast Cancer: Radiogenomic Biomarker Reveals Associations among Dynamic Contrast-enhanced MR Imaging, Long Noncoding RNA, and Metastasis

被引:98
作者
Yamamoto, Shota [1 ]
Han, Wonshik [2 ]
Kim, Youngwoo [2 ]
Du, Liutao [1 ]
Jamshidi, Neema [1 ]
Huang, Danshan [1 ]
Kim, Jong Hyo [2 ]
Kuo, Michael D. [1 ]
机构
[1] Univ Calif Los Angeles, Sch Med, Dept Radiol Sci, Los Angeles, CA 90095 USA
[2] Seoul Natl Univ, Coll Med, Canc Res Inst, Seoul, South Korea
关键词
GENE-EXPRESSION PROGRAMS; DCE-MRI; HEPATOCELLULAR-CARCINOMA; FEATURES; PREDICTION; PHENOTYPES; HOTAIR; TUMORS;
D O I
10.1148/radiol.15142698
中图分类号
R8 [特种医学]; R445 [影像诊断学];
学科分类号
1002 ; 100207 ; 1009 ;
摘要
Purpose: To perform a radiogenomic analysis of women with breast cancer to study the multiscale relationships among quantitative computer vision-extracted dynamic contrast material-enhanced (DCE) magnetic resonance (MR) imaging phenotypes, early metastasis, and long noncoding RNA (lncRNA) expression determined by means of high-resolution next-generation RNA sequencing. Materials and Methods: In this institutional review board-approved study, an automated image analysis platform extracted 47 computational quantitative features from DCE MR imaging data in a training set (n = 19) to screen for MR imaging biomarkers indicative of poor metastasis-free survival (MFS). The lncRNA molecular landscape of the candidate feature was defined by using an RNA sequencing-specific negative binomial distribution differential expression analysis. Then, this radiogenomic biomarker was applied prospectively to a validation set (n = 42) to allow prediction of MFS and lncRNA expression by using quantitative polymerase chain reaction analysis. Results: The quantitative MR imaging feature, enhancing rim fraction score, was predictive of MFS in the training set (P = .007). RNA sequencing analysis yielded an average of 55.7 x 10(6) reads per sample and identified 14880 lncRNAs from a background of 189883 transcripts per sample. Radiogenomic analysis allowed identification of three previously uncharacterized and five named lncRNAs significantly associated with high enhancing rim fraction, including Homeobox transcript antisense intergenic RNA (HOTAIR) (P < .05), a known predictor of poor MFS in patients with breast cancer. Independent validation confirmed the association of the enhancing rim fraction phenotype with both MFS (P = .002) and expression of four of the top five differentially expressed lncRNAs (P < .05), including HOTAIR. Conclusion: The enhancing rim fraction score, a quantitative DCE MR imaging lncRNA radiogenomic biomarker, is associated with early metastasis and expression of the known predictor of metastatic progression, HOTAIR. (C) RSNA, 2015
引用
收藏
页码:384 / 392
页数:9
相关论文
共 35 条
[1]   Computerized Image Analysis for Identifying Triple-Negative Breast Cancers and Differentiating Them from Other Molecular Subtypes of Breast Cancer on Dynamic Contrast-enhanced MR Images: A Feasibility Study [J].
Agner, Shannon C. ;
Rosen, Mark A. ;
Englander, Sarah ;
Tomaszewski, John E. ;
Feldman, Michael D. ;
Zhang, Paul ;
Mies, Carolyn ;
Schnall, Mitchell D. ;
Madabhushi, Anant .
RADIOLOGY, 2014, 272 (01) :91-99
[2]   Differential expression analysis for sequence count data [J].
Anders, Simon ;
Huber, Wolfgang .
GENOME BIOLOGY, 2010, 11 (10)
[3]  
[Anonymous], 2000, Handbook of Medical Imaging
[4]   Transcriptional profiling of long non-coding RNAs and novel transcribed regions across a diverse panel of archived human cancers [J].
Brunner, Alayne L. ;
Beck, Andrew H. ;
Edris, Badreddin ;
Sweeney, Robert T. ;
Zhu, Shirley X. ;
Li, Rui ;
Montgomery, Kelli ;
Varma, Sushama ;
Gilks, Thea ;
Guo, Xiangqian ;
Foley, Joseph W. ;
Witten, Daniela M. ;
Giacomini, Craig P. ;
Flynn, Ryan A. ;
Pollack, Jonathan R. ;
Tibshirani, Robert ;
Chang, Howard Y. ;
van de Rijn, Matt ;
West, Robert B. .
GENOME BIOLOGY, 2012, 13 (08) :R75
[5]   Computerized Assessment of Breast Lesion Malignancy using DCE-MRI: Robustness Study on Two Independent Clinical Datasets from Two Manufacturers [J].
Chen, Weijie ;
Giger, Maryellen L. ;
Newstead, Gillian M. ;
Bick, Ulrich ;
Jansen, Sanaz A. ;
Li, Hui ;
Lan, Li .
ACADEMIC RADIOLOGY, 2010, 17 (07) :822-829
[6]   Mapping pathophysiological features of breast tumors by MRI at high spatial resolution [J].
Degani, H ;
Gusis, V ;
Weinstein, D ;
Fields, S ;
Strano, S .
NATURE MEDICINE, 1997, 3 (07) :780-782
[7]   easyRNASeq: a bioconductor package for processing RNA-Seq data [J].
Delhomme, Nicolas ;
Padioleau, Ismael ;
Furlong, Eileen E. ;
Steinmetz, Lars M. .
BIOINFORMATICS, 2012, 28 (19) :2532-2533
[8]   Identification of noninvasive imaging surrogates for brain tumor gene-expression modules [J].
Diehn, Maximilian ;
Nardini, Christine ;
Wang, David S. ;
McGovern, Susan ;
Jayaraman, Mahesh ;
Liang, Yu ;
Alclape, Kenneth ;
Cha, Soonmee ;
Kuo, Michael D. .
PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA, 2008, 105 (13) :5213-5218
[9]   Non-coding RNAs in human disease [J].
Esteller, Manel .
NATURE REVIEWS GENETICS, 2011, 12 (12) :861-874
[10]  
Furman-Haran E, 2014, TECHNOL CANCER RES T, V13, P445, DOI [10.7785/tcrt.2013.600263, 10.7785/tcrtexpress.2013.600263]