MRI-based breast cancer radiogenomics using RNA profiling: association with subtypes in a single-center prospective study.

Ah Young Park, Mi-Ryung Han, Bo Kyoung Seo, Hye-Yeon Ju, Gil Soo Son, Hye Yoon Lee, Young Woo Chang, Jungyoon Choi, Kyu Ran Cho, Sung Eun Song, Ok Hee Woo, Hyun Soo Park
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引用次数: 1

Abstract

Background: There are few prospective studies on the correlations between MRI features and whole RNA-sequencing data in breast cancer according to molecular subtypes. The purpose of our study was to explore the association between genetic profiles and MRI phenotypes of breast cancer and to identify imaging markers that influences the prognosis and treatment according to subtypes.

Methods: From June 2017 to August 2018, MRIs of 95 women with invasive breast cancer were prospectively analyzed, using the breast imaging-reporting and data system and texture analysis. Whole RNA obtained from surgical specimens was analyzed using next-generation sequencing. The association between MRI features and gene expression profiles was analyzed in the entire tumor and subtypes. Gene networks, enriched functions, and canonical pathways were analyzed using Ingenuity Pathway Analysis. The P value for differential expression was obtained using a parametric F test comparing nested linear models and adjusted for multiple testing by reporting Q value.

Results: In 95 participants (mean age, 53 years ± 11 [standard deviation]), mass lesion type was associated with upregulation of CCL3L1 (sevenfold) and irregular mass shape was associated with downregulation of MIR421 (sixfold). In estrogen receptor-positive cancer with mass lesion type, CCL3L1 (21-fold), SNHG12 (11-fold), and MIR206 (sevenfold) were upregulated, and MIR597 (265-fold), MIR126 (12-fold), and SOX17 (fivefold) were downregulated. In triple-negative breast cancer with increased standard deviation of texture analysis on precontrast T1-weighted imaging, CLEC3A (23-fold), SRGN (13-fold), HSPG2 (sevenfold), KMT2D (fivefold), and VMP1 (fivefold) were upregulated, and IGLC2 (73-fold) and PRDX4 (sevenfold) were downregulated (all, P < 0.05 and Q < 0.1). Gene network and functional analysis showed that mass type estrogen receptor-positive cancers were associated with cell growth, anti-estrogen resistance, and poor survival.

Conclusion: MRI characteristics are associated with the different expressions of genes related to metastasis, anti-drug resistance, and prognosis, depending on the molecular subtypes of breast cancer.

Abstract Image

Abstract Image

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使用RNA分析的基于mri的乳腺癌放射基因组学:在单中心前瞻性研究中与亚型的关联
背景:基于分子亚型对乳腺癌MRI特征与全rna测序数据相关性的前瞻性研究较少。我们的研究目的是探讨遗传谱与乳腺癌MRI表型之间的关系,并根据亚型确定影响预后和治疗的影像学标志物。方法:对2017年6月至2018年8月95例浸润性乳腺癌患者的mri进行前瞻性分析,采用乳腺影像报告和数据系统及纹理分析。从手术标本中获得的全RNA使用下一代测序进行分析。在整个肿瘤和亚型中分析了MRI特征与基因表达谱之间的关系。基因网络、富集功能和典型通路使用匠心途径分析。差异表达的P值通过比较嵌套线性模型的参数F检验获得,并通过报告Q值对多重检验进行调整。结果:在95名参与者(平均年龄53岁±11岁[标准差])中,肿块病变类型与CCL3L1上调相关(7倍),不规则肿块形状与MIR421下调相关(6倍)。在雌激素受体阳性肿瘤伴肿块型中,CCL3L1(21倍)、SNHG12(11倍)和MIR206(7倍)上调,MIR597(265倍)、MIR126(12倍)和SOX17(5倍)下调。在对比前t1加权成像纹理分析标准差增高的三阴性乳腺癌中,CLEC3A(23倍)、SRGN(13倍)、HSPG2(7倍)、KMT2D(5倍)、VMP1(5倍)上调,IGLC2(73倍)、PRDX4(7倍)下调(均P)。根据乳腺癌分子亚型的不同,MRI特征与转移、耐药和预后相关基因的不同表达有关。
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