4.6 Review

A global view of regulatory networks in lung cancer: An approach to understand homogeneity and heterogeneity

Journal

SEMINARS IN CANCER BIOLOGY
Volume 42, Issue -, Pages 31-38

Publisher

ACADEMIC PRESS LTD- ELSEVIER SCIENCE LTD
DOI: 10.1016/j.semcancer.2016.11.004

Keywords

Lung cancer; Regulatory network; Transcriptional factor; Subtype; Bioinformatics

Categories

Funding

  1. Shanghai Leading Academic Discipline Project [B115]
  2. Zhongshan Distinguished Professor Grant (XDW)
  3. National Nature Science Foundation of China [91230204, 81270099, 81320108001, 81270131, 81400035, 81570075, 81500058, 81500025, 31400713]
  4. Shanghai Committee of Science and Technology [12JC1402200, 12431900207, 11410708600]
  5. Zhejiang Provincial Natural Science Foundation [Z15H010002]
  6. Zhejiang Provincial Science Technology Department Foundation [WKJ-ZJ-1526]

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A number of new biotechnologies are used to identify potential biomarkers for the early detection of lung cancer, enabling a personalized therapy to be developed in response. The combinatorial cross-regulation of hundreds of biological function-specific transcription factors (TFs) is defined as the understanding of regulatory networks of molecules within the cell. Here we integrated global databases with 537 patients with lung adenocarcinoma (ADC), 140 with lung squamous carcinoma (SCC), 9 with lung large-cell carcinoma (LCC), 56 with small-cell lung cancer (SCLC), and 590 without cancer with the understanding of TF functions. The present review aims at the homogeneity or heterogeneity of gene expression profiles among subtypes of lung cancer. About 5,136, 52, or 16 up-regulated or 19, 24,122, or 97down-regulated type-special TF genes were identified in ADC, SCC, LCC or SCLC, respectively. DNA-binding and transcription regulator activity associated genes play a dominant role in the differentiation of subtypes in lung cancer. Subtype-specific TF gene regulatory networks with elements should be an alternative for diagnostic and therapeutic targets for early identification of lung cancer and can provide insightful clues to etiology and pathogenesis. (C) 2016 Elsevier Ltd. All rights reserved.

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