Landscape of transcriptional deregulation in lung cancer.
Landscape of transcriptional deregulation in lung cancer.
复制标题
肺癌转录失调的情况
DOI:
10.1186/s12864-018-4828-1
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发表时间:
2018-06-05
期刊:
影响因子:
4.4
通讯作者:
Fang Z
中科院分区:
文献类型:
--
作者:
Zhang S;Li M;Ji H;Fang Z
Lung cancer is a very heterogeneous disease that can be pathologically classified into different subtypes including small-cell lung carcinoma (SCLC), lung adenocarcinoma (LUAD), lung squamous cell carcinoma (LUSC) and large-cell carcinoma (LCC). Although much progress has been made towards the oncogenic mechanism of each subtype, transcriptional circuits mediating the upstream signaling pathways and downstream functional consequences remain to be systematically studied. Here we trained a one-class support vector machine (OC-SVM) model to establish a general transcription factor (TF) regulatory network containing 325 TFs and 18724 target genes. We then applied this network to lung cancer subtypes and identified those deregulated TFs and downstream targets. We found that the TP63/SOX2/DMRT3 module was specific to LUSC, corresponding to squamous epithelial differentiation and/or survival. Moreover, the LEF1/MSC module was specifically activated in LUAD and likely to confer epithelial-to-mesenchymal transition, known important for cancer malignant progression and metastasis. The proneural factor, ASCL1, was specifically up-regulated in SCLC which is known to have a neuroendocrine phenotype. Also, ID2 was differentially regulated between SCLC and LUSC, with its up-regulation in SCLC linking to energy supply for fast mitosis and its down-regulation in LUSC linking to the attenuation of immune response. We further described the landscape of TF regulation among the three major subtypes of lung cancer, highlighting their functional commonalities and specificities. Our approach uncovered the landscape of transcriptional deregulation in lung cancer, and provided a useful resource of TF regulatory network for future studies. The online version of this article (10.1186/s12864-018-4828-1) contains supplementary material, which is available to authorized users.
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DOI:
10.1093/bioinformatics/btr064
发表时间:
2011-04-01
期刊:
Bioinformatics (Oxford, England)
影响因子:
--
作者:
Grant CE;Bailey TL;Noble WS
通讯作者:
Noble WS
影响因子:
158.5
作者:
Lynch, TJ;Bell, DW;Haber, DA
通讯作者:
Haber, DA
影响因子:
4.6
作者:
Han H;Shim H;Shin D;Shim JE;Ko Y;Shin J;Kim H;Cho A;Kim E;Lee T;Kim H;Kim K;Yang S;Bae D;Yun A;Kim S;Kim CY;Cho HJ;Kang B;Shin S;Lee I
通讯作者:
Lee I
影响因子:
5.3
作者:
Lo, Ken C.;Stein, Leighton C.;Hawthorn, Lesleyann
通讯作者:
Hawthorn, Lesleyann
影响因子:
64.8
作者:
Andersson, Lisa S.;Larhammar, Martin;Memic, Fatima;Wootz, Hanna;Schwochow, Doreen;Rubin, Carl-Johan;Patra, Kalicharan;Arnason, Thorvaldur;Wellbring, Lisbeth;Hjalm, Goran;Imsland, Freyja;Petersen, Jessica L.;McCue, Molly E.;Mickelson, James R.;Cothran, Gus;Ahituv, Nadav;Roepstorff, Lars;Mikko, Sofia;Vallstedt, Anna;Lindgren, Gabriella;Andersson, Leif;Kullander, Klas
通讯作者:
Kullander, Klas