From the Department of Radiology, Korea University Ansan Hospital, Korea University College of Medicine, 123 Jeokgeum-ro, Danwon-gu, Ansan city, Gyeonggi-do, 15355, Republic of Korea (A.Y.P., E.K.P., S.H.C., B.K.S.); Department of Radiology, CHA Bundang Medical Center, CHA University, Seongnam, Republic of Korea (A.Y.P.); Department of Laboratory Medicine, Korea University Anam Hospital, Korea University College of Medicine, Seoul, Republic of Korea (M.R.H., Y.C., H.H.); Division of Life Sciences, College of Life Sciences and Bioengineering, Incheon National University, Incheon, Republic of Korea (M.R.H.); Division of Hematology/Oncology, Department of Internal Medicine, Korea University Anam Hospital, Korea University College of Medicine, Seoul, Republic of Korea (K.H.P.); Division of Hematology/Oncology, Department of Internal Medicine, Korea University Ansan Hospital, Korea University College of Medicine, Gyeonggi-do, Republic of Korea (J.S.K.); Division of Breast and Endocrine Surgery, Department of Surgery, Korea University Ansan Hospital, Korea University College of Medicine, Gyeonggi-do, Republic of Korea (G.S.S., H.Y.L., Y.W.C.); Department of Radiology, Korea University Anam Hospital, Korea University College of Medicine, Seoul, Republic of Korea (K.R.C., S.E.S.); Department of Radiology, Korea University Guro Hospital, Korea University College of Medicine, Seoul, Republic of Korea (O.H.W.); Department of Pathology, Korea University Ansan Hospital, Korea University College of Medicine, Gyeonggi-do, Republic of Korea (J.H.L.); and Medical Science Research Center, Korea University Ansan Hospital, Korea University College of Medicine, Gyeonggi-do, Republic of Korea (J.C.).
Radiology. 2020 Apr;295(1):24-34. doi: 10.1148/radiol.2020191368. Epub 2020 Feb 4.
Background Radiogenomic investigations for breast cancer provide an understanding of tumor heterogeneity and discover image phenotypes of genetic variation. However, there is little research on the correlations between US features of breast cancer and whole-transcriptome profiling. Purpose To explore US phenotypes reflecting genetic alteration relevant to breast cancer treatment and prognosis by comparing US images of tumor with their RNA sequencing results. Materials and Methods From January to October 2016, B-mode and vascular US images in 31 women (mean age, 49 years ± 9 [standard deviation]) with breast cancer were prospectively analyzed. B-mode features included size, shape, echo pattern, orientation, margin, and calcifications. Vascular features were evaluated by using microvascular US and contrast agent-enhanced US: vascular index, vessel morphologic features, distribution, penetrating vessels, enhancement degree, order, margin, internal homogeneity, and perfusion defect. RNA sequencing was conducted with total RNA obtained from a surgical specimen by using next-generation sequencing. US features were compared with gene expression profiles, and ingenuity pathway analysis was used to analyze gene networks, enriched functions, and canonical pathways associated with breast cancer. The value for differential expression was extracted by using a parametric test comparing nested linear models. Results Thirteen US features were associated with various patterns of 340 genes ( < .05). Nonparallel orientation at B-mode US was associated with upregulation of (log twofold change [log2FC] = 4.0; < .001), (log2FC = 2.5; < .001), (log2FC = 2.6; = .005), and (log2FC = 2.6; = .003). Complex vessel morphologic structure was associated with upregulation of (log2FC = 2.0; = .01) and downregulation of (log2FC = -2.0; = .006) and (log2FC = -2.4; = .01). The top networks with regard to orientation or vessel morphologic structure were associated with cell cycle, death, and proliferation. Conclusion Compared with RNA sequencing, B-mode and vascular US features reflected genomic alterations associated with hormone receptor status, angiogenesis, or prognosis in breast cancer. © RSNA, 2020 .
背景 乳腺癌的放射基因组学研究提供了对肿瘤异质性的认识，并发现了与遗传变异相关的图像表型。然而，关于乳腺癌的 US 特征与全转录组谱之间的相关性的研究甚少。目的 通过比较肿瘤的 US 图像与其 RNA 测序结果，探讨反映与乳腺癌治疗和预后相关的遗传改变的 US 表型。材料与方法 本研究前瞻性分析了 2016 年 1 月至 10 月间 31 名女性（平均年龄，49 岁±9[标准差]）的乳腺癌 B 型和血管 US 图像。B 型特征包括大小、形状、回声模式、方位、边界和钙化。血管特征通过微血管 US 和对比增强 US 进行评估：血管指数、血管形态特征、分布、穿透血管、增强程度、顺序、边界、内部均匀性和灌注缺损。通过下一代测序从手术标本中提取总 RNA 进行 RNA 测序。将 US 特征与基因表达谱进行比较，并使用 ingenuity 通路分析分析与乳腺癌相关的基因网络、富集功能和经典通路。通过比较嵌套线性模型的参数检验提取差异表达的 值。结果 13 个 US 特征与 340 个基因的各种模式相关（ <.05）。B 型 US 上的非平行方位与 （log2FC=4.0； <.001）、 （log2FC=2.5； <.001）、 （log2FC=2.6； =.005）和 （log2FC=2.6； =.003）的上调相关。复杂的血管形态结构与 （log2FC=2.0； =.01）的上调和 （log2FC=-2.0； =.006）和 （log2FC=-2.4； =.01）的下调相关。关于方位或血管形态结构的顶级网络与细胞周期、死亡和增殖有关。结论 与 RNA 测序相比，B 型和血管 US 特征反映了与乳腺癌激素受体状态、血管生成或预后相关的基因组改变。©RSNA，2020。
