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

Guo T, Kouvonen P, Koh CC, Gillet LC, Wolski WE, Röst HL, Rosenberger G, Collins BC, Blum LC, Gillessen S, Joerger M, Jochum W, Aebersold R - Nat. Med. (2015)

Bottom Line: 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.From these proteome maps we detected and quantified more than 2,000 proteins with a high degree of reproducibility across all samples.

View Article: PubMed Central - PubMed

Affiliation: Department of Biology, Institute of Molecular Systems Biology, Eidgenössische Technische Hochschule (ETH) Zurich, Zurich, Switzerland.

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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Protein markers for RCC quantified in SWATH-MS mapsHeat map shows relative abundance of 21 proteotypic proteins across 18 kidney tissue SWATH maps. Abundance values of each protein were normalized to a scale of 0 to 1, followed by unsupervised clustering of protein expression pattern. Box-and-whisker plots on the right side shows distribution of relative abundance for each protein. AMACR, alpha-methylacyl-CoA racemase; CA9, carbonate dehydratase IX; CAV1, caveolin 1; CDH1, E-cadherin; CDH16, cadherin 16; GSTA1/2, glutathione S-transferase alpha 1/2; KRTs, keratins; MME, membrane metallo-endopeptidase; PODXL, podocalyxin-like protein 1; PVALB, parvalbumin alpha; S100A1, S100 calcium binding protein A1; SDHB, succinate dehydrogenase; VIM, vimentin.
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Figure 4: Protein markers for RCC quantified in SWATH-MS mapsHeat map shows relative abundance of 21 proteotypic proteins across 18 kidney tissue SWATH maps. Abundance values of each protein were normalized to a scale of 0 to 1, followed by unsupervised clustering of protein expression pattern. Box-and-whisker plots on the right side shows distribution of relative abundance for each protein. AMACR, alpha-methylacyl-CoA racemase; CA9, carbonate dehydratase IX; CAV1, caveolin 1; CDH1, E-cadherin; CDH16, cadherin 16; GSTA1/2, glutathione S-transferase alpha 1/2; KRTs, keratins; MME, membrane metallo-endopeptidase; PODXL, podocalyxin-like protein 1; PVALB, parvalbumin alpha; S100A1, S100 calcium binding protein A1; SDHB, succinate dehydrogenase; VIM, vimentin.

Mentions: Next, we searched the literature and identified 53 Swiss-Prot proteins presently used as diagnostic or prognostic biomarkers for renal cancers 21,22, of which 21 proteins, including the widely used biomarkers VIM and AMACR, were quantified in our data set (Fig. 4). As we used exclusively proteotypic peptides, i.e. peptides that are unique to a specific protein 23, we were able to independently quantify even highly concordant protein isoforms. This is exemplified by cytokeratin isoforms, some of which showed idiotypic quantitative patterns across samples. For example, after an unsupervised clustering, while most cytokeratins clustered together, while cytokeratin 8 displayed a unique pattern.


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

Guo T, Kouvonen P, Koh CC, Gillet LC, Wolski WE, Röst HL, Rosenberger G, Collins BC, Blum LC, Gillessen S, Joerger M, Jochum W, Aebersold R - Nat. Med. (2015)

Protein markers for RCC quantified in SWATH-MS mapsHeat map shows relative abundance of 21 proteotypic proteins across 18 kidney tissue SWATH maps. Abundance values of each protein were normalized to a scale of 0 to 1, followed by unsupervised clustering of protein expression pattern. Box-and-whisker plots on the right side shows distribution of relative abundance for each protein. AMACR, alpha-methylacyl-CoA racemase; CA9, carbonate dehydratase IX; CAV1, caveolin 1; CDH1, E-cadherin; CDH16, cadherin 16; GSTA1/2, glutathione S-transferase alpha 1/2; KRTs, keratins; MME, membrane metallo-endopeptidase; PODXL, podocalyxin-like protein 1; PVALB, parvalbumin alpha; S100A1, S100 calcium binding protein A1; SDHB, succinate dehydrogenase; VIM, vimentin.
© Copyright Policy
Related In: Results  -  Collection

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getmorefigures.php?uid=PMC4390165&req=5

Figure 4: Protein markers for RCC quantified in SWATH-MS mapsHeat map shows relative abundance of 21 proteotypic proteins across 18 kidney tissue SWATH maps. Abundance values of each protein were normalized to a scale of 0 to 1, followed by unsupervised clustering of protein expression pattern. Box-and-whisker plots on the right side shows distribution of relative abundance for each protein. AMACR, alpha-methylacyl-CoA racemase; CA9, carbonate dehydratase IX; CAV1, caveolin 1; CDH1, E-cadherin; CDH16, cadherin 16; GSTA1/2, glutathione S-transferase alpha 1/2; KRTs, keratins; MME, membrane metallo-endopeptidase; PODXL, podocalyxin-like protein 1; PVALB, parvalbumin alpha; S100A1, S100 calcium binding protein A1; SDHB, succinate dehydrogenase; VIM, vimentin.
Mentions: Next, we searched the literature and identified 53 Swiss-Prot proteins presently used as diagnostic or prognostic biomarkers for renal cancers 21,22, of which 21 proteins, including the widely used biomarkers VIM and AMACR, were quantified in our data set (Fig. 4). As we used exclusively proteotypic peptides, i.e. peptides that are unique to a specific protein 23, we were able to independently quantify even highly concordant protein isoforms. This is exemplified by cytokeratin isoforms, some of which showed idiotypic quantitative patterns across samples. For example, after an unsupervised clustering, while most cytokeratins clustered together, while cytokeratin 8 displayed a unique pattern.

Bottom Line: 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.From these proteome maps we detected and quantified more than 2,000 proteins with a high degree of reproducibility across all samples.

View Article: PubMed Central - PubMed

Affiliation: Department of Biology, Institute of Molecular Systems Biology, Eidgenössische Technische Hochschule (ETH) Zurich, Zurich, Switzerland.

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.

Show MeSH
Related in: MedlinePlus