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Rapid mass spectrometric conversion of tissue biopsy samples into permanent quantitative digital proteome maps

Abstract

Clinical specimens are each inherently unique, limited and nonrenewable. Small samples such as tissue biopsies are often completely consumed after a limited number of analyses. Here we present a method that enables fast and reproducible conversion of a small amount of tissue (approximating the quantity obtained by a biopsy) into a single, permanent digital file representing the mass spectrometry (MS)-measurable proteome of the sample. The method combines pressure cycling technology (PCT) and sequential window acquisition of all theoretical fragment ion spectra (SWATH)-MS. The resulting proteome maps can be analyzed, re-analyzed, compared and mined in silico to detect and quantify specific proteins across multiple samples. We used this method to process and convert 18 biopsy samples from nine patients with renal cell carcinoma into SWATH-MS fragment ion maps. From these proteome maps we detected and quantified more than 2,000 proteins with a high degree of reproducibility across all samples. The measured proteins clearly distinguished tumorous kidney tissues from healthy tissues and differentiated distinct histomorphological kidney cancer subtypes.

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Figure 1: PCT-SWATH method flow chart.
Figure 2: Yield and efficiency of PCT-assisted tissue lysis and protein digestion.
Figure 3: Reproducibility of PCT-SWATH.
Figure 4: Protein markers for RCC quantified in SWATH-MS maps.
Figure 5: Variation analysis of human kidney tissue proteomes by SWATH-MS.
Figure 6: Comparative proteomic analysis of clear cell RCC tissues.

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Acknowledgements

We thank N. Roesch and M. Stoffel for providing test mouse tissues, H.P. Schmid and D. Engeler for their help with human tissue collection, A. Leitner and K. Novy for help in Orbitrap analysis, A. Leitner for assistance in setting up the Barocycler, the ETH Brutus team for computational support, and O.L. Kon for critical reading of the manuscript. The work was supported by the SystemsX.ch project PhosphoNetX (to R.A.), the Swiss National Science Foundation (grant no. 3100A0-688 107679 to R.A.), and the European Research Council (grant no. ERC-2008-AdG 233226 to R.A.). P.K. was supported by a fellowship from the Finnish Cultural Foundation. We thank the PRIDE team for support in mass spectrometry data deposition.

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Authors and Affiliations

Authors

Contributions

R.A. conceived the idea. T.G. developed the method. S.G., M.J. and W.J. designed the clinical cohort and collected the clinical tissue samples. T.G., P.K. and C.C.K. performed the analysis of the tissues. L.C.G. and T.G. performed the MS measurements. T.G. performed the data analysis, with critical inputs from W.E.W., C.C.K., H.L.R., G.R., B.C.C. and L.C.B. T.G. and R.A. wrote the manuscript. C.C.K., M.J. and all the other authors contributed to the revision of the manuscript. R.A. supervised the project.

Corresponding author

Correspondence to Ruedi Aebersold.

Ethics declarations

Competing interests

R.A. holds shares of Biognosys AG, which operates in the field covered by the article. The research group of R.A. is supported by AB SCIEX, which provides access to prototype instrumentation, and Pressure Biosciences, which provides access to advanced sample preparation instrumentation.

Supplementary information

Supplementary Text and Figures

Supplementary Figures 1–3 (PDF 440 kb)

Supplementary Table 1

Protein quantification of 12 test kidney tissues (XLS 1002 kb)

Supplementary Table 2

Clinicopathological characteristics of renal cell carcinomas (XLS 25 kb)

Supplementary Table 3

Protein quantification of 9 paired kidney biopsies analyzed in duplicates (XLS 1351 kb)

Supplementary Table 4

Significantly regulated proteins between tumorous and nontumorous biopsies from six ccRCC patients (XLS 238 kb)

Supplementary Table 5

Significantly regulated proteins between tumorous ccRCC and pRCC (XLS 175 kb)

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Guo, T., Kouvonen, P., Koh, C. et al. Rapid mass spectrometric conversion of tissue biopsy samples into permanent quantitative digital proteome maps. Nat Med 21, 407–413 (2015). https://doi.org/10.1038/nm.3807

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