Comparative proteogenomics profiling of non-small and small lung carcinoma cell lines using mass spectrometry

• Main Authors: Jingyu Wu, Zhifang Hao, Chen Ma, Pengfei Li, Liuyi Dang, Shisheng Sun
• Format: Article
• Language: English
• Published: PeerJ Inc. 2020-04-01
• Series: PeerJ
• Subjects: Non-small cell lung cancer; Small cell lung cancer; Transcriptomics; Proteomics; Bioinformatics; Proteogenomics
• Online Access: https://peerj.com/articles/8779.pdf

Background Evidences indicated that non-small-cell lung cancer (NSCLC) and small-cell lung cancer (SCLC) might originate from the same cell type, which however ended up to be two different subtypes of lung carcinoma, requiring different therapeutic regimens. We aimed to identify the differences between these two subtypes of lung cancer by using integrated proteome and genome approaches. Methods and Materials Two representative cell lines for each lung cancer subtype were comparatively analysed by quantitative proteomics, and their corresponding transcriptomics data were obtained from the Gene Expression Omnibus database. The integrated analyses of proteogenomic data were performed to determine key differentially expressed proteins that were positively correlated between proteomic and transcriptomic data. Result The proteomics analysis revealed 147 differentially expressed proteins between SCLC and NSCLC from a total of 3,970 identified proteins. Combined with available transcriptomics data, we further confirmed 14 differentially expressed proteins including six known and eight new lung cancer related proteins that were positively correlated with their transcriptomics data. These proteins are mainly involved in cell migration, proliferation, and invasion. Conclusion The proteogenomic data on both NSCLC and SCLC cell lines presented in this manuscript is complementary to existing genomic and proteomic data related to lung cancers and will be crucial for a systems biology-level understanding of the molecular mechanism of lung cancers. The raw mass spectrometry data have been deposited to the ProteomeXchange Consortium via the PRIDE partner repository with the dataset identifier PXD015270.