Mass spectrometry-based characterisation of the secretome of pancreatic cancer cell lines

Schiarea, Silvia (2010). Mass spectrometry-based characterisation of the secretome of pancreatic cancer cell lines. PhD thesis The Open University.



The cancer secretome represents a rich repository where to mine potentially useful information for both cancer biology and clinical oncology. A global proteomic analysis of multiple cancer secretomes can help identify protein patterns representing signatures of malignancy, among which to find candidate therapeutic targets and cancer biomarkers. In this study a mass spectrometry-based workflow has been set up and applied to the characterization and comparison of secretomes from four human pancreatic ductal adenocarcinoma cell lines (PT45, Panc1, MiaPaCa2, Aspc1) and their normal counterpart HPDE6. Early diagnosis and efficacious therapies are in fact urgently needed for pancreatic cancer, whose death/incidence ratio is among the worst for any tumour.

Proteins in conditioned media were concentrated and separated by IDE. Each gel lane was cut into 24 bands and in-gel digested. The digests were analysed by liquid chromatography-tandem mass spectrometry with a high resolution mass spectrometer (LTQ Orbitrap XL). The MS/MS data were analyzed by two search engines with very strict parameters, and further filtered to obtain high-confidence protein identification. emPAI was used to calculate the fold change of proteins dysregulated in cancer vs normal cell lines. MetaCore's GeneGo network enrichment analysis was performed on all the proteins dysregulated by at least four fold.

The final identification list comprised 300-500 proteins per cell line (overall, 790 unique proteins), among which 11 were over- and 93 under-expressed (>4 fold) in all four cancer cell lines. Twelve networks, all related to processes relevant for cancer progression (e.g. cell-cell adhesion, cell-matrix adhesion, extracellular matrix remodelling, inflammation and protein folding) were significantly perturbed in all four cancer cell lines. This analysis highlighted novel potential signatures of malignancy that could be worth further analysis.

In conclusion, this study has provided a protocol for the proteomic/functional characterization and comparison of multiple cell line secretomes, a large high-confidence protein dataset describing the secretome of normal and neoplastic pancreatic cell lines, and a comparative functional analysis of dysregulated proteins highlighting networks relevant to cancer biology.

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