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本文引用的文献

1
Cancer metabolism: new validated targets for drug discovery.癌症代谢:药物研发的新验证靶点
Oncotarget. 2013 Aug;4(8):1309-16. doi: 10.18632/oncotarget.1182.
2
Oncogenes induce the cancer-associated fibroblast phenotype: metabolic symbiosis and "fibroblast addiction" are new therapeutic targets for drug discovery.癌基因诱导癌症相关成纤维细胞表型:代谢共生和“成纤维细胞成瘾”是药物发现的新治疗靶点。
Cell Cycle. 2013 Sep 1;12(17):2723-32. doi: 10.4161/cc.25695. Epub 2013 Jul 30.
3
Oncogenes and inflammation rewire host energy metabolism in the tumor microenvironment: RAS and NFκB target stromal MCT4.癌基因和炎症重塑肿瘤微环境中的宿主能量代谢:RAS 和 NFκB 靶向基质 MCT4。
Cell Cycle. 2013 Aug 15;12(16):2580-97. doi: 10.4161/cc.25510. Epub 2013 Jul 8.
4
JNK regulates compliance-induced adherens junctions formation in epithelial cells and tissues.JNK 调节上皮细胞和组织中顺应性诱导的黏附连接形成。
J Cell Sci. 2013 Jun 15;126(Pt 12):2718-29. doi: 10.1242/jcs.122903. Epub 2013 Apr 16.
5
Stiff collagen matrices increase tumorigenic prolactin signaling in breast cancer cells.刚性胶原蛋白基质增加乳腺癌细胞中致瘤性催乳素信号传导。
J Biol Chem. 2013 May 3;288(18):12722-32. doi: 10.1074/jbc.M112.447631. Epub 2013 Mar 24.
6
Metabolic alterations in lung cancer-associated fibroblasts correlated with increased glycolytic metabolism of the tumor.肺癌相关成纤维细胞的代谢改变与肿瘤糖酵解代谢增加相关。
Mol Cancer Res. 2013 Jun;11(6):579-92. doi: 10.1158/1541-7786.MCR-12-0437-T. Epub 2013 Mar 8.
7
Inhibition of JNK mitochondrial localization and signaling is protective against ischemia/reperfusion injury in rats.抑制 JNK 的线粒体定位和信号传递可预防大鼠的缺血/再灌注损伤。
J Biol Chem. 2013 Feb 8;288(6):4000-11. doi: 10.1074/jbc.M112.406777. Epub 2012 Dec 20.
8
Genetic induction of the Warburg effect inhibits tumor growth.瓦伯格效应的基因诱导抑制肿瘤生长。
Oncotarget. 2012 Nov;3(11):1266-7. doi: 10.18632/oncotarget.739.
9
Mitochondria "fuel" breast cancer metabolism: fifteen markers of mitochondrial biogenesis label epithelial cancer cells, but are excluded from adjacent stromal cells.线粒体“为”乳腺癌代谢“供能”:十五个线粒体生物发生的标记物标记上皮癌细胞,但被排除在相邻的基质细胞之外。
Cell Cycle. 2012 Dec 1;11(23):4390-401. doi: 10.4161/cc.22777. Epub 2012 Nov 21.
10
c-Jun N-Terminal Kinase in Inflammation and Rheumatic Diseases.炎症与风湿性疾病中的c-Jun氨基末端激酶
Open Rheumatol J. 2012;6:220-31. doi: 10.2174/1874312901206010220. Epub 2012 Sep 7.

JNK1应激信号在乳腺密度高和肿瘤基质中过度激活:将纤维化、炎症和干性联系起来以预防癌症。

JNK1 stress signaling is hyper-activated in high breast density and the tumor stroma: connecting fibrosis, inflammation, and stemness for cancer prevention.

作者信息

Lisanti Michael P, Tsirigos Aristotelis, Pavlides Stephanos, Reeves Kimberley Jayne, Peiris-Pagès Maria, Chadwick Amy L, Sanchez-Alvarez Rosa, Lamb Rebecca, Howell Anthony, Martinez-Outschoorn Ubaldo E, Sotgia Federica

机构信息

Breakthrough Breast Cancer Research Unit and the Manchester Breast Centre; Institute of Cancer Sciences; University of Manchester; Manchester, UK; Manchester Centre for Cellular Metabolism (MCCM); University of Manchester; Manchester, UK.

Computational Biology Center; IBM T.J. Watson Research Center; Yorktown Heights, NY USA.

出版信息

Cell Cycle. 2014;13(4):580-99. doi: 10.4161/cc.27379. Epub 2013 Dec 5.

DOI:10.4161/cc.27379
PMID:24434780
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC3988118/
Abstract

Mammography is an important screening modality for the early detection of DCIS and breast cancer lesions. More specifically, high mammographic density is associated with an increased risk of breast cancer. However, the biological processes underlying this phenomenon remain largely unknown. Here, we re-interrogated genome-wide transcriptional profiling data obtained from low-density (LD) mammary fibroblasts (n = 6 patients) and high-density (HD) mammary fibroblasts (n = 7 patients) derived from a series of 13 female patients. We used these raw data to generate a "breast density" gene signature consisting of>1250 transcripts that were significantly increased in HD fibroblasts, relative to LD fibroblasts. We then focused on the genes that were increased by ≥ 1.5-fold (P<0.05) and performed gene set enrichment analysis (GSEA), using the molecular signatures database (MSigDB). Our results indicate that HD fibroblasts show the upregulation and/or hyper-activation of several key cellular processes, including the stress response, inflammation, stemness, and signal transduction. The transcriptional profiles of HD fibroblasts also showed striking similarities to human tumors, including head and neck, liver, thyroid, lung, and breast cancers. This may reflect functional similarities between cancer-associated fibroblasts (CAFs) and HD fibroblasts. This is consistent with the idea that the presence of HD fibroblasts may be a hallmark of a pre-cancerous phenotype. In these biological processes, GSEA predicts that several key signaling pathways may be involved, including JNK1, iNOS, Rho GTPase(s), FGF-R, EGF-R, and PDGF-R-mediated signal transduction, thereby creating a pro-inflammatory, pro-proliferative, cytokine, and chemokine-rich microenvironment. HD fibroblasts also showed significant overlap with gene profiles derived from smooth muscle cells under stress (JNK1) and activated/infected macrophages (iNOS). Thus, HD fibroblasts may behave like activated myofibroblasts and macrophages, to create and maintain a fibrotic and inflammatory microenvironment. Finally, comparisons between the HD fibroblast gene signature and breast cancer tumor stroma revealed that JNK1 stress signaling is the single most significant biological process that is shared between these 2 data sets (with P values between 5.40E-09 and 1.02E-14), and is specifically associated with tumor recurrence. These results implicate "stromal JNK1 signaling" in the pathogenesis of human breast cancers and the transition to malignancy. Augmented TGF-β signaling also emerged as a common feature linking high breast density with tumor stroma and breast cancer recurrence (P = 5.23E-05). Similarities between the HD fibroblast gene signature, wound healing, and the cancer-associated fibroblast phenotype were also noted. Thus, this unbiased informatics analysis of high breast density provides a novel framework for additional experimental exploration and new hypothesis-driven breast cancer research, with a focus on cancer prevention and personalized medicine.

摘要

乳腺钼靶摄影是早期检测导管原位癌(DCIS)和乳腺癌病灶的重要筛查方式。更具体地说,乳腺钼靶高密度与乳腺癌风险增加相关。然而,这一现象背后的生物学过程在很大程度上仍不清楚。在此,我们重新分析了从13名女性患者的一系列样本中获取的低密度(LD)乳腺成纤维细胞(n = 6例患者)和高密度(HD)乳腺成纤维细胞(n = 7例患者)的全基因组转录谱数据。我们利用这些原始数据生成了一个“乳腺密度”基因特征,该特征由超过1250个转录本组成,相对于LD成纤维细胞,这些转录本在HD成纤维细胞中显著增加。然后,我们聚焦于那些增加≥1.5倍(P<0.05)的基因,并使用分子特征数据库(MSigDB)进行基因集富集分析(GSEA)。我们的结果表明,HD成纤维细胞显示出几个关键细胞过程的上调和/或过度激活,包括应激反应、炎症、干性和信号转导。HD成纤维细胞的转录谱也与人类肿瘤(包括头颈癌、肝癌、甲状腺癌、肺癌和乳腺癌)有显著相似性。这可能反映了癌症相关成纤维细胞(CAF)和HD成纤维细胞之间的功能相似性。这与HD成纤维细胞的存在可能是癌前表型标志的观点一致。在这些生物学过程中,GSEA预测可能涉及几个关键信号通路,包括JNK1、诱导型一氧化氮合酶(iNOS)、Rho鸟苷三磷酸酶(Rho GTPase)、成纤维细胞生长因子受体(FGF-R)、表皮生长因子受体(EGF-R)和血小板衍生生长因子受体(PDGF-R)介导的信号转导,从而形成一个促炎、促增殖、富含细胞因子和趋化因子的微环境。HD成纤维细胞也与应激下平滑肌细胞(JNK1)和活化/感染巨噬细胞(iNOS)的基因谱有显著重叠。因此,HD成纤维细胞可能表现得像活化的肌成纤维细胞和巨噬细胞,以创建和维持纤维化和炎症微环境。最后,HD成纤维细胞基因特征与乳腺癌肿瘤基质之间的比较显示,JNK1应激信号是这两个数据集之间共同的最显著生物学过程(P值在5.40E - 09至1.02E - 14之间),并且与肿瘤复发特别相关。这些结果表明“基质JNK1信号”在人类乳腺癌发病机制及向恶性转变中起作用。增强的转化生长因子-β(TGF-β)信号也作为将高乳腺密度与肿瘤基质和乳腺癌复发联系起来的一个共同特征出现(P = 5.23E - 05)。还注意到HD成纤维细胞基因特征、伤口愈合和癌症相关成纤维细胞表型之间的相似性。因此,这种对高乳腺密度的无偏信息学分析为进一步的实验探索和新的基于假设的乳腺癌研究提供了一个新框架,重点在于癌症预防和个性化医学。