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乳腺癌基因组分析揭示了基因、突变和信号网络。

Breast cancer genomic analyses reveal genes, mutations, and signaling networks.

机构信息

Manipal Academy of Higher Education (MAHE), Manipal, 576104, Karnataka, India.

Institute of Bioinformatics, International Technology Park, Whitefield, Bangalore, 560066, Karnataka, India.

出版信息

Funct Integr Genomics. 2024 Nov 4;24(6):206. doi: 10.1007/s10142-024-01484-y.

DOI:10.1007/s10142-024-01484-y
PMID:39496981
Abstract

Breast cancer (BC) is the most commonly diagnosed cancer and the predominant cause of death in women. BC is a complex disorder, and the exploration of several types of BC omic data, highlighting genes, perturbations, signaling and cellular mechanisms, is needed. We collected mutational data from 9,555 BC samples using cBioPortal. We classified 1174 BC genes (mutated ≥ 40 samples) into five tiers (BCtier_I-V) and subjected them to pathway and protein‒protein network analyses using EnrichR and STRING 11, respectively. BCtier_I possesses 12 BC genes with mutational frequencies > 5%, with only 5 genes possessing > 10% frequencies, namely, PIK3CA (35.7%), TP53 (34.3%), GATA3 (11.5%), CDH1 (11.4%) and MUC16 (11%), and the next seven BC genes are KMT2C (8.8%), TTN (8%), MAP3K1 (8%), SYNE1 (7.2%), AHNAK2 (7%), USH2A (5.5%), and RYR2 (5.4%). Our pathway analyses revealed that the five top BC pathways were the PI3K-AKT, TP53, NOTCH, HIPPO, and RAS pathways. We found that BC panels share only seven genes. These findings show that BC arises from genetic disruptions evident in BC signaling and protein networks.

摘要

乳腺癌(BC)是最常见的癌症,也是女性死亡的主要原因。BC 是一种复杂的疾病,需要探索多种 BC 组学数据,突出基因、扰动、信号和细胞机制。我们使用 cBioPortal 从 9555 个 BC 样本中收集了突变数据。我们将 1174 个 BC 基因(突变 ≥ 40 个样本)分为五个层次(BCtier_I-V),并使用 EnrichR 和 STRING 11 分别对它们进行途径和蛋白质相互作用网络分析。BCtier_I 拥有 12 个突变频率 > 5%的 BC 基因,只有 5 个基因的突变频率 > 10%,即 PIK3CA(35.7%)、TP53(34.3%)、GATA3(11.5%)、CDH1(11.4%)和 MUC16(11%),接下来的七个 BC 基因是 KMT2C(8.8%)、TTN(8%)、MAP3K1(8%)、SYNE1(7.2%)、AHNAK2(7%)、USH2A(5.5%)和 RYR2(5.4%)。我们的途径分析显示,前五个 BC 途径是 PI3K-AKT、TP53、NOTCH、HIPPO 和 RAS 途径。我们发现 BC 面板仅共享七个基因。这些发现表明,BC 是由 BC 信号和蛋白质网络中明显的遗传破坏引起的。

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本文引用的文献

1
Estrogen Receptor Mutations as Novel Targets for Immunotherapy in Metastatic Estrogen Receptor-positive Breast Cancer.雌激素受体突变作为转移性雌激素受体阳性乳腺癌免疫治疗的新靶点。
Cancer Res Commun. 2024 Feb 22;4(2):496-504. doi: 10.1158/2767-9764.CRC-23-0244.
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Application of single-cell sequencing to the research of tumor microenvironment.单细胞测序在肿瘤微环境研究中的应用。
Front Immunol. 2023 Oct 27;14:1285540. doi: 10.3389/fimmu.2023.1285540. eCollection 2023.
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Comparison of Mutation Prevalence in Breast Cancer Across Predicted Ancestry Populations.
乳腺癌中预测的祖源人群的突变率比较。
JCO Precis Oncol. 2022 Nov;6:e2200341. doi: 10.1200/PO.22.00341.
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Targeting HER2-positive breast cancer: advances and future directions.针对 HER2 阳性乳腺癌:进展与未来方向。
Nat Rev Drug Discov. 2023 Feb;22(2):101-126. doi: 10.1038/s41573-022-00579-0. Epub 2022 Nov 7.
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p53 signaling in cancer progression and therapy.p53信号通路在癌症进展与治疗中的作用
Cancer Cell Int. 2021 Dec 24;21(1):703. doi: 10.1186/s12935-021-02396-8.
6
Hotspot mutation profiles of AKT1 in Asian women with breast and endometrial cancers.亚洲女性乳腺癌和子宫内膜癌中 AKT1 的热点突变谱。
BMC Cancer. 2021 Oct 21;21(1):1131. doi: 10.1186/s12885-021-08869-3.
7
The many facets of Notch signaling in breast cancer: toward overcoming therapeutic resistance.Notch 信号在乳腺癌中的多方面作用:克服治疗抵抗。
Genes Dev. 2020 Nov 1;34(21-22):1422-1438. doi: 10.1101/gad.342287.120.
8
PIK3CA mutation confers resistance to chemotherapy in triple-negative breast cancer by inhibiting apoptosis and activating the PI3K/AKT/mTOR signaling pathway.PIK3CA突变通过抑制细胞凋亡和激活PI3K/AKT/mTOR信号通路,赋予三阴性乳腺癌对化疗的抗性。
Ann Transl Med. 2021 Mar;9(5):410. doi: 10.21037/atm-21-698.
9
The impact of CBP expression in estrogen receptor-positive breast cancer.CBP 表达对雌激素受体阳性乳腺癌的影响。
Clin Epigenetics. 2021 Apr 7;13(1):72. doi: 10.1186/s13148-021-01060-2.
10
The emerging role of KDM5A in human cancer.KDM5A 在人类癌症中的新兴作用。
J Hematol Oncol. 2021 Feb 17;14(1):30. doi: 10.1186/s13045-021-01041-1.