Unraveling the Pivotal Network of Ultrasound and Somatic Mutations in Triple-Negative and Non-Triple-Negative Breast Cancer.

IF 3.3 4区 医学 Q2 ONCOLOGY
Yunxia Huang, Yi Guo, Qin Xiao, Shuyu Liang, Qiang Yu, Lang Qian, Jin Zhou, Jian Le, Yuchen Pei, Lei Wang, Cai Chang, Sheng Chen, Shichong Zhou
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引用次数: 0

Abstract

Purpose: The emergence of genomic targeted therapy has improved the prospects of treatment for breast cancer (BC). However, genetic testing relies on invasive and sophisticated procedures.

Patients and methods: Here, we performed ultrasound (US) and target sequencing to unravel the possible association between US radiomics features and somatic mutations in TNBC (n=83) and non-TNBC (n=83) patients. Least absolute shrinkage and selection operator (Lasso) were utilized to perform radiomic feature selection. The Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis was utilized to identify the signaling pathways associated with radiomic features.

Results: Thirteen differently represented radiomic features were identified in TNBC and non-TNBC, including tumor shape, textual, and intensity features. The US radiomic-gene pairs were differently exhibited between TNBC and non-TNBC. Further investigation with KEGG verified radiomic-pathway (ie, JAK-STAT, MAPK, Ras, Wnt, microRNAs in cancer, PI3K-Akt) associations in TNBC and non-TNBC.

Conclusion: The pivotal network provided the connections of US radiogenomic signature and target sequencing for non-invasive genetic assessment of precise BC treatment.

Abstract Image

Abstract Image

Abstract Image

揭示三阴性和非三阴性乳腺癌超声和体细胞突变的关键网络。
目的:基因组靶向治疗的出现改善了乳腺癌(BC)治疗的前景。然而,基因检测依赖于侵入性和复杂的程序。患者和方法:在这里,我们进行了超声(US)和靶标测序,以揭示TNBC (n=83)和非TNBC (n=83)患者的US放射组学特征与体细胞突变之间可能的关联。利用最小绝对收缩和选择算子(Lasso)进行放射学特征选择。利用京都基因与基因组百科全书(KEGG)分析确定与放射学特征相关的信号通路。结果:在TNBC和非TNBC中确定了13种不同的放射学特征,包括肿瘤形状、文本和强度特征。美国放射组基因对在TNBC和非TNBC之间表现不同。KEGG进一步研究证实了放射学通路(即JAK-STAT、MAPK、Ras、Wnt、癌症中的microrna、PI3K-Akt)在TNBC和非TNBC中的关联。结论:该枢纽网络为精确治疗BC提供了US放射基因组标记和靶标测序的连接。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
CiteScore
4.10
自引率
0.00%
发文量
40
审稿时长
16 weeks
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