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基于非参数随机森林分析的稳健炎性乳腺癌基因特征。

Robust inflammatory breast cancer gene signature using nonparametric random forest analysis.

机构信息

Department of Pediatrics, Faculty of Medicine and Dentistry, University of Alberta, Edmonton, AB, Canada.

Department of Biomedical and Molecular Sciences, Queen's University, Kingston, ON, Canada.

出版信息

Breast Cancer Res. 2021 Sep 27;23(1):92. doi: 10.1186/s13058-021-01467-y.

Abstract

Inflammatory breast cancer (IBC) is a rare, aggressive cancer found in all the molecular breast cancer subtypes. Despite extensive previous efforts to screen for transcriptional differences between IBC and non-IBC patients, a robust IBC-specific molecular signature has been elusive. We report a novel IBC-specific gene signature (59 genes; G59) that achieves 100% accuracy in discovery and validation samples (45/45 correct classification) and remarkably only misclassified one sample (60/61 correct classification) in an independent dataset. G59 is independent of ER/HER2 status, molecular subtypes and is specific to untreated IBC samples, with most of the genes being enriched for plasma membrane cellular component proteins, interleukin (IL), and chemokine signaling pathways. Our finding suggests the existence of an IBC-specific molecular signature, paving the way for the identification and validation of targetable genomic drivers of IBC.

摘要

炎性乳腺癌(IBC)是一种罕见且侵袭性的癌症,存在于所有分子乳腺癌亚型中。尽管之前已经进行了大量的研究来筛选 IBC 和非 IBC 患者之间的转录差异,但仍未找到一个稳健的 IBC 特异性分子特征。我们报告了一个新的 IBC 特异性基因特征(59 个基因;G59),在发现和验证样本中达到了 100%的准确性(45/45 正确分类),在一个独立的数据集上仅错误分类了一个样本(60/61 正确分类)。G59 独立于 ER/HER2 状态、分子亚型,并且仅特异性地针对未经治疗的 IBC 样本,大多数基因富含质膜细胞成分蛋白、白细胞介素(IL)和趋化因子信号通路。我们的发现表明存在 IBC 特异性分子特征,为鉴定和验证 IBC 的可靶向基因组驱动因素铺平了道路。

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