Radiogenomic analysis of prediction HER2 status in breast cancer by linking ultrasound radiomic feature module with biological functions

Journal of Translational Medicine

Research

Yue Gao¹  Shangwei Ning¹  Yue Sun¹  Meixin Wu²  Baiyang Fu³  Hao Cui⁴  Nana Hu⁴  Panting Wang⁴  Wei Fan⁴  Yuan Yao⁴  Xudong Zhang⁴  Xiaoxuan Zuo⁴  Lei Zhang⁴  Dantong Zhao⁴  Hanqing Kong⁴  Jiawei Tian⁴ 

[1] College of Bioinformatics Science and Technology, Harbin Medical University, 150081, Harbin, China;Department of Clinical Medicine, The Second Affiliated Hospital of Harbin Medical University, 150086, Heilongjiang, China;Department of Surgery, The Second Affiliated Hospital of Harbin Medical University, 150086, Harbin, Heilongjiang, China;Department of Ultrasound Medicine, The Second Affiliated Hospital of Harbin Medical University, 150086, Harbin, Heilongjiang, China;

关键词: Breast cancer;    HER2;    Radiogenomics;    Radiomics;    Ultrasound;   

DOI  :  10.1186/s12967-022-03840-7

 received in 2022-05-26, accepted in 2022-12-19,  发布年份 2022

来源: Springer

【 摘 要 】

BackgroundHuman epidermal growth factor receptor 2 (HER2) overexpressed associated with poor prognosis in breast cancer and HER2 has been defined as a therapeutic target for breast cancer treatment. We aimed to explore the molecular biological information in ultrasound radiomic features (URFs) of HER2-positive breast cancer using radiogenomic analysis. Moreover, a radiomics model was developed to predict the status of HER2 in breast cancer.MethodsThis retrospective study included 489 patients who were diagnosed with breast cancer. URFs were extracted from a radiomics analysis set using PyRadiomics. The correlations between differential URFs and HER2-related genes were calculated using Pearson correlation analysis. Functional enrichment of the identified URFs-correlated HER2 positive-specific genes was performed. Lastly, the radiomics model was developed based on the URF-module mined from auxiliary differential URFs to assess the HER2 status of breast cancer.ResultsEight differential URFs (p < 0.05) were identified among the 86 URFs extracted by Pyradiomics. 25 genes that were found to be the most closely associated with URFs. Then, the relevant biological functions of each differential URF were obtained through functional enrichment analysis. Among them, Zone Entropy is related to immune cell activity, which regulate the generation of calcification in breast cancer. The radiomics model based on the Logistic classifier and URF-module showed good discriminative ability (AUC = 0.80, 95% CI).ConclusionWe searched for the URFs of HER2-positive breast cancer, and explored the underlying genes and biological functions of these URFs. Furthermore, the radiomics model based on the Logistic classifier and URF-module relatively accurately predicted the HER2 status in breast cancer.

【 授权许可】

CC BY   
© The Author(s) 2023

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