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TCGA 中三阴性乳腺癌亚组的乳腺癌特征的综合分析揭示了新的 miRNA 特异性簇，包括 miR-17-92a，可区分基底样 1 和基底样 2 三阴性乳腺癌亚型。

Integrative analysis of breast cancer profiles in TCGA by TNBC subgrouping reveals novel microRNA-specific clusters, including miR-17-92a, distinguishing basal-like 1 and basal-like 2 TNBC subtypes.

机构信息

Department of Computer Science, Baylor University, Waco, TX, USA.

Instiute of Biomedical Studies, Baylor University, Waco, TX, USA.

出版信息

BMC Cancer. 2020 Feb 21;20(1):141. doi: 10.1186/s12885-020-6600-6.

DOI:10.1186/s12885-020-6600-6
PMID:32085745
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC7035760/
Abstract

BACKGROUND

The term triple-negative breast cancer (TNBC) is used to describe breast cancers without expression of estrogen receptor, progesterone receptor or HER2 amplification. To advance targeted treatment options for TNBC, it is critical that the subtypes within this classification be described in regard to their characteristic biology and gene expression. The Cancer Genome Atlas (TCGA) dataset provides not only clinical and mRNA expression data but also expression data for microRNAs.

RESULTS

In this study, we applied the Lehmann classifier to TCGA-derived TNBC cases which also contained microRNA expression data and derived subtype-specific microRNA expression patterns. Subsequent analyses integrated known and predicted microRNA-mRNA regulatory nodes as well as patient survival data to identify key networks. Notably, basal-like 1 (BL1) TNBCs were distinguished from basal-like 2 TNBCs through up-regulation of members of the miR-17-92 cluster of microRNAs and suppression of several known miR-17-92 targets including inositol polyphosphate 4-phosphatase type II, INPP4B.

CONCLUSIONS

These data demonstrate TNBC subtype-specific microRNA and target mRNA expression which may be applied to future biomarker and therapeutic development studies.

摘要

背景

三阴性乳腺癌（TNBC）这一术语用于描述缺乏雌激素受体、孕激素受体或 HER2 扩增的乳腺癌。为了推进 TNBC 的靶向治疗选择，描述这一分类内的亚型在其特征生物学和基因表达方面是至关重要的。癌症基因组图谱（TCGA）数据集不仅提供了临床和 mRNA 表达数据，还提供了 microRNA 的表达数据。

结果

在这项研究中，我们将 Lehmann 分类器应用于包含 microRNA 表达数据的 TCGA 衍生的 TNBC 病例，并得出了亚型特异性的 microRNA 表达模式。随后的分析整合了已知和预测的 microRNA-mRNA 调控节点以及患者生存数据，以确定关键网络。值得注意的是，通过上调 microRNA-17-92 簇的成员和抑制几个已知的 miR-17-92 靶标，包括肌醇多磷酸 4-磷酸酶 II 型、INPP4B，BL1 型 TNBC 与 BL2 型 TNBC 区分开来。

结论

这些数据表明 TNBC 亚型特异性的 microRNA 和靶标 mRNA 表达，可应用于未来的生物标志物和治疗开发研究。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/379f/7035760/06e308b1145a/12885_2020_6600_Fig9_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/379f/7035760/74c051ebc242/12885_2020_6600_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/379f/7035760/58bbac81000f/12885_2020_6600_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/379f/7035760/48e71d35e197/12885_2020_6600_Fig3_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/379f/7035760/f85175877dd6/12885_2020_6600_Fig4_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/379f/7035760/db9ed5a2e9fa/12885_2020_6600_Fig5_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/379f/7035760/6e11c0198e70/12885_2020_6600_Fig6_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/379f/7035760/5a25f43131f3/12885_2020_6600_Fig7_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/379f/7035760/de07626e734b/12885_2020_6600_Fig8_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/379f/7035760/06e308b1145a/12885_2020_6600_Fig9_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/379f/7035760/74c051ebc242/12885_2020_6600_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/379f/7035760/58bbac81000f/12885_2020_6600_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/379f/7035760/48e71d35e197/12885_2020_6600_Fig3_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/379f/7035760/f85175877dd6/12885_2020_6600_Fig4_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/379f/7035760/db9ed5a2e9fa/12885_2020_6600_Fig5_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/379f/7035760/6e11c0198e70/12885_2020_6600_Fig6_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/379f/7035760/5a25f43131f3/12885_2020_6600_Fig7_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/379f/7035760/de07626e734b/12885_2020_6600_Fig8_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/379f/7035760/06e308b1145a/12885_2020_6600_Fig9_HTML.jpg

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