Multi-scale representation of proteomic data exhibits distinct microRNA regulatory modules in non-smoking female patients with lung adenocarcinoma

• Published in: Computers in biology and medicine 2018-11, Vol.102, p.51-56
• Main Authors: Chan, Lawrence W., Wang, Fengfeng, Meng, Fei, Wang, Lili, Wong, S.C. Cesar, Au, Joseph S., Yang, Sijun, Cho, William C.
• Format: Article
• Language: English
• Subjects: Adenocarcinoma; Bioinformatics; Biomarkers; Breast cancer; Cancer; Cell cycle; Clusters; Data processing; Discrete Wavelet Transform; Disease; Females; Genetic markers; Genomics; Ionization; Lasers; Lung adenocarcinoma; Lung cancer; Marker cluster; Markers; Mass spectra; Mass spectrometry; Mass spectroscopy; Medical research; microRNA; miRNA; Mortality; Multi-scale representation; Noise; Non-small cell lung carcinoma; Patients; Proteins; Proteomics; Regulatory modules; Ribonucleic acid; Risk analysis; Risk factors; RNA; Smoking; Subgroups; Wavelet transforms
• ISSN: 0010-4825; 1879-0534
• DOI: 10.1016/j.compbiomed.2018.09.005

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. •Proteomic markers of lung adenocarcinoma in female non-smokers were explored.•Novel approach combining FDR control and Wavelet Transforms identified six markers.•The markers represent a consistent cluster at multiple scales of mass spectrum.•The cluster corresponds to 7 proteins that identified cases with 87.6% accuracy.•Modules of miR-206 and miR-613 were predicted to regulate 3 of these proteins.