SPA: A Quantitation Strategy for MS Data in Patient-derived Xenograft Models

With the development of mass spectrometry (MS)-based proteomics technologies, patient-derived xenograft (PDX), which is generated from the primary tumor of a patient, is widely used for the proteome-wide analysis of cancer mechanism and biomarker identification of a drug. However, the proteomics data interpretation is still challenging due to complex data deconvolution from the PDX sample that is a cross-species mixture of human cancerous tissues and immunodeficient mouse tissues. In this study, by using the lab-assembled mixture of human and mouse cells with different mixing ratios as a benchmark, we developed and evaluated a new method, SPA (shared peptide allocation), for protein quantitation by considering the unique and shared peptides of both species. The results showed that SPA could provide more convenient and accurate protein quantitation in human-mouse mixed samples. Further validation on a pair of gastric PDX samples (one bearing FGFR2 amplification while the other one not) showed that our new method not only significantly improved the overall protein identification, but also detected the differential phosphorylation of FGFR2 and its downstream mediators (such as RAS and ERK) exclusively. The tool pdxSPA is freely available at https://github.com/Li-Lab-Proteomics/pdxSPA.