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Title: Multi-scale representation of proteomic data exhibits distinct microRNA regulatory modules in non-smoking female patients with lung adenocarcinoma
Authors: Chan, LW 
Wang, F 
Meng, F 
Wang, L 
Wong, SCC 
Au, JS
Yang, S
Cho, WC
Issue Date: 1-Nov-2018
Source: Computers in biology and medicine, 1 Nov. 2018, v. 102, p. 51-56
Abstract: Adenocarcinoma in female non-smokers is an under-explored subgroup of non-small cell lung cancer (NSCLC), in which the molecular mechanism and genetic risk factors remain unclear. We analyzed the protein profiles of plasma samples of 45 patients in this subgroup and 60 non-cancer subjects using surface-enhanced laser desorption/ionization time-of- flight mass spectrometry. Among 85 peaks of mass spectra, the differential expression analysis identified 15 markers based on False Discovery Rate control and the Discrete Wavelet Transforms further selected a cluster of 6 markers that were consistently observed at multiple scales of mass-charge ratios. This marker cluster, corresponding to 7 unique proteins, was able to distinguish the female non-smokers with adenocarcinoma from non-cancer subjects with a value of accuracy of 87.6%. We also predicted the role of competing endogenous RNAs (ceRNAs) in 3 out of these 7 proteins. Other studies reported that these ceRNAs and their targeting microRNAs, miR-206 and miR-613, were significantly associated with NSCLC. This study paves a crucial path for further investigating the genetic markers and molecular mechanism of this special NSCLC subgroup.
Keywords: Lung adenocarcinoma
Marker cluster
Mass spectrometry
MicroRNA
Multi-scale representation
Regulatory modules
Publisher: Pergamon Press
Journal: Computers in biology and medicine 
ISSN: 0010-4825
EISSN: 1879-0534
DOI: 10.1016/j.compbiomed.2018.09.005
Rights: © 2018 Elsevier Inc. All rights reserved.
© 2018. This manuscript version is made available under the CC-BY-NC-ND 4.0 license https://creativecommons.org/licenses/by-nc-nd/4.0/
The following publication Chan, L. W., Wang, F., Meng, F., Wang, L., Wong, S. C., Au, J. S., ... & Cho, W. C. (2018). Multi-scale representation of proteomic data exhibits distinct microRNA regulatory modules in non-smoking female patients with lung adenocarcinoma. Computers in Biology and Medicine, 102, 51-56 is available at https://doi.org/10.1016/j.compbiomed.2018.09.005.
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