Li Wen-Xing, He Kan, Tang Ling, Dai Shao-Xing, Li Gong-Hua, Lv Wen-Wen, Guo Yi-Cheng, An San-Qi, Wu Guo-Ying, Liu Dahai, Huang Jing-Fei
Institute of Health Sciences, Anhui University, Hefei 230601, Anhui, China.
State Key Laboratory of Genetic Resources and Evolution, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming 650223, Yunnan, China.
Oncotarget. 2017 Jan 24;8(4):6775-6786. doi: 10.18632/oncotarget.14286.
Breast cancer is the most commonly diagnosed malignancy in women. Several key genes and pathways have been proven to correlate with breast cancer pathology. This study sought to explore the differences in key transcription factors (TFs), transcriptional regulation networks and dysregulated pathways in different tissues in breast cancer. We employed 14 breast cancer datasets from NCBI-GEO and performed an integrated analysis in three different tissues including breast, blood and saliva. The results showed that there were eight genes (CEBPD, EGR1, EGR2, EGR3, FOS, FOSB, ID1 and NFIL3) down-regulated in breast tissue but up-regulated in blood tissue. Furthermore, we identified several unreported tissue-specific TFs that may contribute to breast cancer, including ATOH8, DMRT2, TBX15 and ZNF367. The dysregulation of these TFs damaged lipid metabolism, development, cell adhesion, proliferation, differentiation and metastasis processes. Among these pathways, the breast tissue showed the most serious impairment and the blood tissue showed a relatively moderate damage, whereas the saliva tissue was almost unaffected. This study could be helpful for future biomarker discovery, drug design, and therapeutic and predictive applications in breast cancers.
乳腺癌是女性中最常被诊断出的恶性肿瘤。几个关键基因和信号通路已被证明与乳腺癌病理相关。本研究旨在探索乳腺癌不同组织中关键转录因子(TFs)、转录调控网络及失调信号通路的差异。我们使用了来自NCBI-GEO的14个乳腺癌数据集,并在包括乳腺、血液和唾液在内的三种不同组织中进行了综合分析。结果显示,有8个基因(CEBPD、EGR1、EGR2、EGR3、FOS、FOSB、ID1和NFIL3)在乳腺组织中下调,但在血液组织中上调。此外,我们鉴定出了几种可能与乳腺癌相关的未报道的组织特异性TFs,包括ATOH8、DMRT2、TBX15和ZNF367。这些TFs的失调破坏了脂质代谢、发育、细胞黏附、增殖、分化和转移过程。在这些信号通路中,乳腺组织受损最为严重,血液组织受损相对较轻,而唾液组织几乎未受影响。本研究可能有助于未来乳腺癌的生物标志物发现、药物设计以及治疗和预测应用。