A network-based method for identifying prognostic gene modules in lung squamous carcinoma

被引：11

作者：

Feng, Lin ^{[1
,2
]}

Tong, Run ^{[3
]}

Liu, Xiaohong ^{[4
]}

Zhang, Kaitai ^{[1
,2
]}

Wang, Guiqi ^{[5
]}

Zhang, Lei ^{[5
]}

An, Ning ^{[1
,2
]}

Cheng, Shujun ^{[1
,2
]}

机构：

[1] Peking Union Med Coll, Dept Etiol & Carcinogenesis, State Key Lab Mol Oncol, Beijing 100021, Peoples R China

[2] Chinese Acad Med Sci, Canc Inst Hosp, Beijing 100730, Peoples R China

[3] China Japan Friendship Hosp, Dept Resp & Crit Care Med, Beijing, Peoples R China

[4] Maternal & Child Hlth Care Hosp Haidian, Dept Gynecol & Obstet, Beijing, Peoples R China

[5] Chinese Acad Med Sci, Canc Hosp, Dept Endoscopy, Beijing 100730, Peoples R China

来源：

ONCOTARGET | 2016年 / 7卷 / 14期

基金：

国家高技术研究发展计划(863计划);

关键词：

lung squamous carcinoma; multi-stage carcinogenesis; network-based; greedy searching; prognostic module; STEM-CELLS; CANCER; SURVIVAL; EXPRESSION; CARCINOGENESIS; MECHANISMS; TRANSITION; EVOLUTION; EMT; BAD;

D O I：

10.18632/oncotarget.7632

中图分类号：

R73 [肿瘤学];

学科分类号：

100214 ;

摘要：

Similarities in gene expression between both developing embryonic and precancerous tissues and cancer tissues may help identify much-needed biomarkers and therapeutic targets in lung squamous carcinoma. In this study, human lung samples representing ten successive time points, from embryonic development to carcinogenesis, were used to construct global gene expression profiles. Differentially expressed genes with similar expression in precancerous and cancer samples were identified. Using a network-based greedy searching algorithm to analyze the training cohort (n = 69) and three independent testing cohorts, we successfully identified a significant 22-gene module in which expression levels were correlated with overall survival in lung squamous carcinoma patients.

引用

页码：18006 / 18020

页数：15

共 56 条

[1]

An N, 2015, PLOS ONE, V10

[2] Epithelial Plasticity: A Common Theme in Embryonic and Cancer Cells [J].

Angela Nieto, M. .

SCIENCE, 2013, 342 (6159) :708-+

[3] An automated method for finding molecular complexes in large protein interaction networks [J].

Bader, GD ;

Hogue, CW .

BMC BIOINFORMATICS, 2003, 4 (1)

[4]

BALE AE, 1995, P ASSOC AM PHYSICIAN, V107, P253

[5] Network medicine: a network-based approach to human disease [J].

Barabasi, Albert-Laszlo ;

Gulbahce, Natali ;

Loscalzo, Joseph .

NATURE REVIEWS GENETICS, 2011, 12 (01) :56-68

[6] Crypt stem cells as the cells-of-origin of intestinal cancer [J].

Barker, Nick ;

Ridgway, Rachel A. ;

van Es, Johan H. ;

van de Wetering, Marc ;

Begthel, Harry ;

van den Born, Maaike ;

Danenberg, Esther ;

Clarke, Alan R. ;

Sansom, Owen J. ;

Clevers, Hans .

NATURE, 2009, 457 (7229) :608-U119

[7] Non-small-cell lung cancer molecular signatures recapitulate lung developmental pathways [J].

Borczuk, AC ;

Gorenstein, L ;

Walter, KL ;

Assaad, AA ;

Wang, LQ ;

Powell, CA .

AMERICAN JOURNAL OF PATHOLOGY, 2003, 163 (05) :1949-1960

[8] Multi-step evolution of lung cancer [J].

Braithwaite, KL ;

Rabbitts, PH .

SEMINARS IN CANCER BIOLOGY, 1999, 9 (04) :255-265

[9] Prognostic and Predictive Value of a Malignancy-Risk Gene Signature in Early-Stage Non-Small Cell Lung Cancer [J].

Chen, Dung-Tsa ;

Hsu, Ying-Lin ;

Fulp, William J. ;

Coppola, Domenico ;

Haura, Eric B. ;

Yeatman, Timothy J. ;

Cress, W. Douglas .

JNCI-JOURNAL OF THE NATIONAL CANCER INSTITUTE, 2011, 103 (24) :1859-1870

[10] Tumor heterogeneity and resistance to EGFR-targeted therapy in advanced nonsmall cell lung cancer: challenges and perspectives [J].

Cheng, Xinghua ;

Chen, Haiquan .

ONCOTARGETS AND THERAPY, 2014, 7 :1689-1704

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