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Genomic Characteristics of Triple-Negative Breast Cancer Nominate Molecular Subtypes That Predict Chemotherapy Response

机译:三阴性乳腺癌的基因组特征提名分子亚型预测化疗反应

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摘要

The heterogeneity of triple-negative breast cancer (TNBC) poses difficulties for suitable treatment and leads to poor outcome. This study aimed to define a consensus molecular subtype (CMS) of TNBC and thus elucidate genomic characteristics and relevant therapy. Weintegrated the expression profiles of 957TNBC samples from published datasets. We identified genomic characteristics of subtype by exploring the pathway activity, microenvironment, and clinical relevance. In addition, drug response (DR) scores (n = 181) were computationally investigated using chemical perturbation gene signatures and validated in our own patient with TNBC (n = 38) who received chemotherapy and organoid biobank data (n = 64). Subsequently, cooperative functions with drugs were also explored. Finally, we classified TNBC into four CMSs: stemlike; mesenchymal-like; immunomodulatory; luminal-androgen receptor. CMSs also elucidated distinct tumor-associated microenvironment and pathway activities. Furthermore, we discovered metastasis-promoting genes, such as secreted phosphoprotein 1 by comparing with primary. Computational DR scores associated with CMS revealed drug candidates (n = 18), and it was successfully evaluated in cisplatin response of both patients and organoids. Our CMS recapitulated in-depth functional and cellular heterogeneity encompassing primary and metastatic TNBC. We suggest DR scores to predict CMS-specific DRs and to be successfully validated. Finally, our approach systemically proposes a relevant therapeutic prediction model as well as prognostic markers for TNBC.
机译:三阴性乳腺癌(TNBC)的异质性造成适当治疗的困难,导致结果不佳。本研究旨在定义TNBC的共有分子亚型(CMS),从而阐明基因组特征和相关疗法。我们来自发布的数据集的957TNBC样本的表达方式。通过探索途径活性,微环境和临床相关性,我们确定了亚型的基因组特征。此外,使用化学扰动基因签名计算药物反应(DR)评分(N = 181),并在我们自己的患者中验证TNBC(n = 38),接受化疗和有机体Biobank数据(n = 64)。随后,还探讨了药物的合作功能。最后,我们将TNBC分为四个CMS:STEMLIKE;间充质般的;免疫调节;腔雄激素受体。 CMS也阐明了不同的肿瘤相关的微环境和途径活动。此外,通过与初级相比,我们发现促进促进基因,例如分泌的磷蛋白1。与CMS相关的计算DR分数揭示了药物候选物(n = 18),并在两种患者和有机体的顺铂反应中成功评估。我们的CMS涵盖了深入的功能和细胞异质性,包括主要和转移性TNBC。我们建议DR分数来预测CMS特定的DRS并成功验证。最后,我们的方法系统性地提出了相关的治疗性预测模型以及TNBC的预后标志物。

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  • 来源
    《Molecular cancer research: MCR》 |2020年第2期|共11页
  • 作者单位

    Natl Canc Ctr Res Inst Bioinformat Anal Team Goyang South Korea;

    Natl Canc Ctr Res Inst Bioinformat Anal Team Goyang South Korea;

    Natl Canc Ctr Ctr Breast Canc Hosp Goyang South Korea;

    Natl Canc Ctr Ctr Breast Canc Hosp Goyang South Korea;

    Natl Canc Ctr Ctr Breast Canc Hosp Goyang South Korea;

    Natl Canc Ctr Div Translat Sci Translat Canc Res Branch Goyang South Korea;

    Natl Canc Ctr Ctr Breast Canc Hosp Goyang South Korea;

    Natl Canc Ctr Ctr Breast Canc Hosp Goyang South Korea;

    Natl Canc Ctr Res Inst Bioinformat Anal Team Goyang South Korea;

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  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类 肿瘤学;
  • 关键词

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