Identifying Circulating Tumor DNA Mutation Profiles in Metastatic Breast Cancer Patients with Multiline Resistance.

来自 PUBMED

作者:

Hu ZYXie NTian CYang XLiu LLi JXiao HWu HLu JGao JHu XCao MShui ZXiao MTang YHe QChang LXia XYi XLiao QOuyang Q

展开

摘要:

In cancer patients, tumor gene mutations contribute to drug resistance and treatment failure. In patients with metastatic breast cancer (MBC), these mutations increase after multiline treatment, thereby decreasing treatment efficiency. The aim of this study was to evaluate gene mutation patterns in MBC patients to predict drug resistance and disease progression. A total of 68 MBC patients who had received multiline treatment were recruited. Circulating tumor DNA (ctDNA) mutations were evaluated and compared among hormone receptor (HR)/human epidermal growth factor receptor 2 (HER2) subgroups. The baseline gene mutation pattern (at the time of recruitment) varied among HR/HER2 subtypes. BRCA1 and MED12 were frequently mutated in triple negative breast cancer (TNBC) patients, PIK3CA and FAT1 mutations were frequent in HR+ patients, and PIK3CA and ERBB2 mutations were frequent in HER2+ patients. Gene mutation patterns also varied in patients who progressed within either 3 months or 3-6 months of chemotherapy treatment. For example, in HR+ patients who progressed within 3 months of treatment, the frequency of TERT mutations significantly increased. Other related mutations included FAT1 and NOTCH4. In HR+ patients who progressed within 3-6 months, PIK3CA, TP53, MLL3, ERBB2, NOTCH2, and ERS1 were the candidate mutations. This suggests that different mechanisms underlie disease progression at different times after treatment initiation. In the COX model, the ctDNA TP53 + PIK3CA gene mutation pattern successfully predicted progression within 6 months. ctDNA gene mutation profiles differed among HR/HER2 subtypes of MBC patients. By identifying mutations associated with treatment resistance, we hope to improve therapy selection for MBC patients who received multiline treatment.

收起

展开

DOI:

10.1016/j.ebiom.2018.05.015

被引量:

42

年份:

1970

SCI-Hub (全网免费下载) 发表链接

通过 文献互助 平台发起求助,成功后即可免费获取论文全文。

查看求助

求助方法1:

知识发现用户

每天可免费求助50篇

求助

求助方法1:

关注微信公众号

每天可免费求助2篇

求助方法2:

求助需要支付5个财富值

您现在财富值不足

您可以通过 应助全文 获取财富值

求助方法2:

完成求助需要支付5财富值

您目前有 1000 财富值

求助

我们已与文献出版商建立了直接购买合作。

你可以通过身份认证进行实名认证,认证成功后本次下载的费用将由您所在的图书馆支付

您可以直接购买此文献,1~5分钟即可下载全文,部分资源由于网络原因可能需要更长时间,请您耐心等待哦~

身份认证 全文购买

相似文献(441)

参考文献(39)

引证文献(42)

来源期刊

EBioMedicine

影响因子:11.194

JCR分区: 暂无

中科院分区:暂无

研究点推荐

关于我们

zlive学术集成海量学术资源,融合人工智能、深度学习、大数据分析等技术,为科研工作者提供全面快捷的学术服务。在这里我们不忘初心,砥砺前行。

友情链接

联系我们

合作与服务

©2024 zlive学术声明使用前必读