Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/96954
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dc.contributorDepartment of Health Technology and Informaticsen_US
dc.creatorChan, LWen_US
dc.creatorWang, Fen_US
dc.creatorMeng, Fen_US
dc.creatorWang, Len_US
dc.creatorWong, SCCen_US
dc.creatorAu, JSen_US
dc.creatorYang, Sen_US
dc.creatorCho, WCen_US
dc.date.accessioned2023-01-09T01:11:18Z-
dc.date.available2023-01-09T01:11:18Z-
dc.identifier.issn0010-4825en_US
dc.identifier.urihttp://hdl.handle.net/10397/96954-
dc.language.isoenen_US
dc.publisherPergamon Pressen_US
dc.rights© 2018 Elsevier Inc. All rights reserved.en_US
dc.rights© 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/en_US
dc.rightsThe 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.en_US
dc.subjectLung adenocarcinomaen_US
dc.subjectMarker clusteren_US
dc.subjectMass spectrometryen_US
dc.subjectMicroRNAen_US
dc.subjectMulti-scale representationen_US
dc.subjectRegulatory modulesen_US
dc.titleMulti-scale representation of proteomic data exhibits distinct microRNA regulatory modules in non-smoking female patients with lung adenocarcinomaen_US
dc.typeJournal/Magazine Articleen_US
dc.identifier.spage51en_US
dc.identifier.epage56en_US
dc.identifier.volume102en_US
dc.identifier.doi10.1016/j.compbiomed.2018.09.005en_US
dcterms.abstractAdenocarcinoma 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.en_US
dcterms.accessRightsopen accessen_US
dcterms.bibliographicCitationComputers in biology and medicine, 1 Nov. 2018, v. 102, p. 51-56en_US
dcterms.isPartOfComputers in biology and medicineen_US
dcterms.issued2018-11-01-
dc.identifier.scopus2-s2.0-85053753956-
dc.identifier.pmid30245277-
dc.identifier.eissn1879-0534en_US
dc.description.validate202301 bckwen_US
dc.description.oaAccepted Manuscripten_US
dc.identifier.FolderNumberHTI-0091-
dc.description.fundingSourceOthersen_US
dc.description.fundingTextHealth and Medical Research Fund; PolyU Central Research Granten_US
dc.description.pubStatusPublisheden_US
dc.identifier.OPUS20816546-
dc.description.oaCategoryGreen (AAM)en_US
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