Proteomic profiles of human lung adeno and squamous cell carcinoma using super-SILAC and label-free quantification approaches

• Published in: Proteomics (Weinheim) Vol. 14; no. 6; pp. 795 - 803
• Main Authors: Zhang, Wen, Wei, Yuhong, Ignatchenko, Vladimir, Li, Lei, Sakashita, Shingo, Pham, Nhu-An, Taylor, Paul, Tsao, Ming Sound, Kislinger, Thomas, Moran, Michael F.
• Format: Journal Article
• Language: English
• Published: Germany Blackwell Publishing Ltd 01.03.2014
• Subjects: Adenocarcinoma - metabolism; Adenocarcinoma - pathology; Biomedicine; Carcinoma, Squamous Cell - metabolism; Carcinoma, Squamous Cell - pathology; Cell Line, Tumor; Humans; Label-free; Lung - metabolism; Lung - pathology; Lung cancer; Lung Neoplasms - metabolism; Lung Neoplasms - pathology; Proteome - analysis; Proteome - metabolism; Proteomics - methods; Shotgun proteomics; Super-SILAC; Tandem Mass Spectrometry; Xenograft; Xenograft; Biomedicine; Shotgun proteomics; Super-SILAC; Label-free; Lung cancer
• ISSN: 1615-9853; 1615-9861
• DOI: 10.1002/pmic.201300382

Nonsmall cell lung cancer (NSCLC) accounts for 85% of lung cancers, and is subdivided into two major histological subtypes: adenocarcinoma (ADC) and squamous cell carcinoma (SCC). There is an unmet need to further subdivide NSCLC according to distinctive molecular features that may be associated with responsiveness to therapies. Four primary tumor‐derived xenograft proteomes (two‐each ADC and SCC) were quantitatively compared by using a super‐SILAC labeling approach together with ultrahigh‐resolution MS. Proteins highly differentially expressed in the two subtypes were identified, including 30 that were validated in an independent cohort of 12 NSCLC primary tumor‐derived xenograft tumors whose proteomes were quantified by an alternative, label‐free shotgun MS methodology. The 30‐protein signature contains metabolism enzymes including phosphoglycerate dehydrogenase, which is more highly expressed in SCC, as well as a comprehensive set of cytokeratins and other components of the epithelial barrier, which is therefore distinctly different between ADC and SCC. These results demonstrate the utility of the super‐SILAC method for the characterization of primary tissues, and compatibility with datasets derived from different MS‐based platforms. The validation of proteome signatures of NSCLC subtypes supports the further development and application of MS‐based quantitative proteomics as a basis for precision classifications and treatments of tumors. All MS data have been deposited in the ProteomeXchange with identifier PXD000438 (http://proteomecentral.proteomexchange.org/dataset/PXD000438).