Radiogenomic Analysis of Breast Cancer by Using B-Mode and Vascular US and RNA Sequencing.

Radiology

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.).

Published: April 2020

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 .

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http://dx.doi.org/10.1148/radiol.2020191368DOI Listing

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