Pilot study demonstrating potential association between breast cancer image-based risk phenotypes and genomic biomarkers
Pilot study demonstrating potential association between breast cancer image-based risk phenotypes and genomic biomarkers
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DOI：
10.1118/1.4865811
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发表时间：
2014-03-01
期刊：
影响因子：
3.8
通讯作者：
Di Rienzo, Anna
中科院分区：
文献类型：
--
作者：
Li, Hui;Giger, Maryellen L.;Di Rienzo, Anna
目的：在这项初步研究中，作者检查了基于图像的表型和基因组生物标志物之间的关联。UGT 2B基因对乳腺密度和乳腺X线摄影实质模式个体间变异的潜在遗传贡献通过进行基于图像的表型和基因组生物标志物[单核苷酸多态性（SNP）基因型]之间的关联研究来证明。使用GE Senographe 2000 D FFDM系统（12位; 0.1 mm像素大小）采集全视野数字乳腺X线照片。从乳头后面的中心乳房区域选择大小为256 x 256像素的感兴趣区域，进行计算机图像分析，以产生基于图像的乳腺摄影密度和实质纹理模式的表型。使用Sequenom MassArray系统进行SNP基因分型。对UGT 2B基因簇进行了123个次要等位基因频率高于5%的SNP的基因分型，并用于研究。基于图像的表型和基因组生物标志物之间的关联进行了评估与皮尔逊相关系数通过PLINK软件，并包括排列和校正多个SNP comparison.Results：从表型-基因型关联分析，薄壁组织纹理粗糙度功能被发现与SNP rs 451632后，多个SNP的多重检验校正（p = 0.022）。幂律β，这是用来表征纹理模式的频率成分，被发现与SNP rs 4148298（p = 0.035）。结论：作者的研究结果表明，UGT 2B基因变异可能有助于个体间的差异，乳腺X线摄影实质模式和乳腺密度。了解基于图像的表型和基因组生物标志物之间的关系可能有助于了解基于图像的生物标志物的生物学机制，并在个性化医疗中发挥未来的作用。(c)2014年美国医学物理学家协会。
Purpose: In this pilot study, the authors examined associations between image-based phenotypes and genomic biomarkers. The potential genetic contribution of UGT2B genes to interindividual variation in breast density and mammographic parenchymal patterns is demonstrated by performing an association study between image-based phenotypes and genomic biomarkers [single-nucleotide polymorphism (SNP) genotypes].Methods: This candidate-gene approach study included 179 subjects for whom both mammograms and blood DNA samples had been obtained. The full-field digital mammograms were acquired using a GE Senographe 2000D FFDM system (12-bit; 0.1 mm-pixel size). Regions-of-interest, 256 x 256 pixels in size, selected from the central breast region behind the nipple underwent computerized image analysis to yield image-based phenotypes of mammographic density and parenchymal texture patterns. SNP genotyping was performed using a Sequenom MassArray System. One hundred twenty three SNPs with minor allele frequency above 5% were genotyped for the UGT2B gene clusters, and used in the study. The association between the image-based phenotypes and genomic biomarkers was assessed with the Pearson correlation coefficient via the PLINK software, and included permutation and correction for multiple SNP comparisons.Results: From the phenotype-genotype association analysis, a parenchyma texture coarseness feature was found to be correlated with SNP rs451632 after multiple test correction for the multiple SNPs (p = 0.022). The power law beta, which is used to characterize the frequency component of texture patterns, was found to be correlated with SNP rs4148298 (p = 0.035).Conclusions: The authors' results indicate that UGT2B gene variation may contribute to interindividual variation in mammographic parenchymal patterns and breast density. Understanding the relationship between image-based phenotypes and genomic biomarkers may help understand the biologic mechanism for image-based biomarkers and yield a future role in personalized medicine. (c) 2014 American Association of Physicists in Medicine.