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基于基因表达谱分析的乳腺癌转移分子机制。

Molecular mechanisms of breast cancer metastasis by gene expression profile analysis.

机构信息

Department of Chemotherapy, Cancer Center, Qilu Hospital of Shandong University, Jinan, Shandong 250012, P.R. China.

出版信息

Mol Med Rep. 2017 Oct;16(4):4671-4677. doi: 10.3892/mmr.2017.7157. Epub 2017 Aug 3.

Abstract

Metastasis is the main cause of breast cancer‑related mortalities. The present study aimed to uncover the relevant molecular mechanisms of breast cancer metastasis and to explore potential biomarkers that may be used for prognosis. Expression profile microarray data GSE8977, which contained 22 stroma samples (15 were from normal breast and 7 were from invasive ductal carcinoma tumor samples), were obtained from the Gene Expression Omnibus database. Following data preprocessing, differentially expressed genes (DEGs) were selected based on analyses conducted using the linear models for microarray analysis package from R and Bioconductor software. The resulting data were used in subsequent function and pathway enrichment analyses, as well as protein‑protein interaction (PPI) network and subnetwork analyses. Transcription factors (TFs) and tumor‑associated genes were also identified among the DEGs. A total of 234 DEGs were identified, which were enriched in immune response, cell differentiation and cell adhesion‑related functions and pathways. Downregulated DEGs included TFs, such as the proto‑oncogene SPI1, pre‑B‑cell leukemia homeobox 3 (PBX3) and lymphoid enhancer‑binding factor 1 (LEF1), as well as tumor suppressors (TSs), such as capping actin protein, gelsolin like (CAPG) and tumor protein p53‑inducible nuclear protein 1 (TP53INP1). Upregulated DEGs also included TFs and tumor suppressors, consisting of transcription factor 7‑like 2 (TCF7L2) and pleiomorphic adenoma gene‑like 1 (PLAGL1). DEGs that were identified at the hub nodes in the PPI network and the subnetwork were epidermal growth factor receptor (EGFR) and spleen‑associated tyrosine kinase (SYK), respectively. Several genes crucial in the metastasis of breast cancer were identified, which may serve as potential biomarkers, many of which were associated with cell adhesion, proliferation or immune response, and may influence breast cancer metastasis by regulating these function or pathways.

摘要

转移是乳腺癌相关死亡的主要原因。本研究旨在揭示乳腺癌转移的相关分子机制,并探索可能用于预后的潜在生物标志物。从基因表达综合数据库中获取包含 22 个基质样本(15 个来自正常乳房,7 个来自浸润性导管癌肿瘤样本)的表达谱微阵列数据 GSE8977。在进行数据预处理后,使用 R 和 Bioconductor 软件中的线性模型微阵列分析包进行分析,选择差异表达基因(DEGs)。将所得数据用于后续的功能和通路富集分析,以及蛋白质-蛋白质相互作用(PPI)网络和子网分析。还在 DEGs 中鉴定了转录因子(TFs)和肿瘤相关基因。鉴定出 234 个 DEGs,它们富集在免疫反应、细胞分化和细胞黏附相关功能和途径中。下调的 DEGs 包括原癌基因 SPI1、前 B 细胞白血病同源盒 3(PBX3)和淋巴增强结合因子 1(LEF1)等 TFs,以及 CAPG、TP53INP1 等肿瘤抑制因子。上调的 DEGs 还包括 TFs 和肿瘤抑制因子,包括转录因子 7 样 2(TCF7L2)和多形性腺瘤基因样 1(PLAGL1)。在 PPI 网络和子网的枢纽节点中鉴定出的 DEGs 分别是表皮生长因子受体(EGFR)和脾相关酪氨酸激酶(SYK)。鉴定出了几个在乳腺癌转移中至关重要的基因,它们可能作为潜在的生物标志物,其中许多与细胞黏附、增殖或免疫反应有关,可能通过调节这些功能或途径影响乳腺癌转移。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8d39/5647040/5d4150ff819b/MMR-16-04-4671-g00.jpg

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