Lipidomes of lung cancer and tumour-free lung tissues reveal distinct molecular signatures for cancer differentiation, age, inflammation, and pulmonary emphysema
Little is known about the human lung lipidome, its variability in different physiological states, its alterations during carcinogenesis and the development of pulmonary emphysema. We investigated how health status might be mirrored in the lung lipidome. Tissues were sampled for both lipidomic and histological analysis. Using a screening approach, we characterised lipidomes of lung cancer tissues and corresponding tumour-free alveolar tissues. We quantified 311 lipids from 11 classes in 43 tissue samples from 26 patients. Tumour tissues exhibited elevated levels of triacylglycerols and cholesteryl esters, as well as a significantly lower abundance of phosphatidylglycerols, which are typical lung surfactant components. Adenocarcinomas and squamous cell carcinomas were distinguished with high specificity based on lipid panels. Lipidomes of tumour biopsy samples showed clear changes depending on their histology and, in particular, their proportion of active tumour cells and stroma. Partial least squares regression showed correlations between lipid profiles of tumour-free alveolar tissues and the degree of emphysema, inflammation status, and the age of patients. Unsaturated long-chain phosphatidylserines and phosphatidylinositols showed a positive correlation with a worsened emphysema status and ageing. This work provides a resource for the human lung lipidome and a systematic data analysis strategy to link clinical characteristics and histology.
Lipidomics encompasses analytical approaches that aim to identify and quantify the complete set of lipids, defined as lipidome in a given cell, tissue or organism as well as their interactions with other molecules. The majority of lipidomics workflows is based on mass spectrometry and has been proven as a powerful tool in system biology in concert with other Omics disciplines. Unfortunately, bioinformatics infrastructures for this relatively young discipline are limited only to some specialists. Search engines, quantification algorithms, visualization tools and databases developed by the ‘Lipidomics Informatics for Life-Science’ (LIFS) partners will be restructured and standardized to provide broad access to these specialized bioinformatics pipelines. There are many medical challenges related to lipid metabolic alterations that will be fostered by capacity building suggested by LIFS. LIFS as member of the ‘German Network for Bioinformatics’ (de.NBI) node for ‘Bioinformatics for Proteomics’ (BioInfra.Prot) and will provide access to the described software as well as to tutorials and consulting services via a unified web-portal.
Shotgun lipidomics offers fast and reproducible identification and quantification of lipids in clinical samples. Lipid extraction procedures based on the methyl tert-butyl protocol are well established for performing shotgun lipidomics in biomedical research. Here, we describe a shotgun lipidomics workflow that is well suited for the analysis of clinical samples such as tissue samples, blood plasma, and peripheral blood mononuclear cells.
Software-aided quality control of parallel reaction monitoring based quantitation of lipid mediators
We characterized the performance of a micro-flow LC-ESI-MS2 approach to analyze lipid mediators (LMs) and polyunsaturated fatty acids (PUFA) that was optimized for SPE free lipid extraction. Tandem mass spectrometry was exclusively performed in parallel reaction monitoring (PRM) mode using TOF and Orbitrap analyzers. This acquisition strategy allowed in addition to quantitation by specific quantifier ions to perform spectrum comparisons using full MS2 spectra information of the analyte. Consequently, we developed a dedicated software SpeCS that allows to 1) process raw peak lists, 2) generate customized spectral libraries, 3) test specificity of quantifier ions and 4) perform spectrum comparisons. The dedicated scoring algorithm is based on signal matching and Spearman's rank correlation of intensities of matched signal. The algorithm was evaluated in respect of its specificity to distinguish structural related LMs on both instrument platforms. We show how high resolution mass spectrometry is beneficial to distinguish co-eluted LM isomers and provide a generalized quality control procedure for PRM. The applicability of the approach was evaluated analyzing the lipid mediator response during M. tuberculosis infection in the mouse lung.
Wutkowski, A. et al. Software-aided quality control of parallel reaction monitoring based quantitation of lipid mediators. Analytica Chimica Acta (2018). doi:10.1016/j.aca.2018.01.044