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Protein levels of clusterin and glutathione synthetase in platelets allow for early detection of colorectal cancer

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Abstract

Colorectal cancer (CRC) is one of the most frequent malignancies in the Western world. Early tumor detection and intervention are important determinants on CRC patient survival. During early tumor proliferation, dissemination and angiogenesis, platelets store and segregate proteins actively and selectively. Hence, the platelet proteome is a potential source of biomarkers denoting early malignancy. By comparing protein profiles of platelets between healthy volunteers (n = 12) and patients with early- (n = 7) and late-stage (n = 5) CRCs using multiplex fluorescence two-dimensional gel electrophoresis (2D-DIGE), we aimed at identifying differentially regulated proteins within platelets. By inter-group comparisons, 94 differentially expressed protein spots were detected (p < 0.05) between healthy controls and patients with early- and late-stage CRCs and revealed distinct separations between all three groups in principal component analyses. 54 proteins of interest were identified by mass spectrometry and resulted in high-ranked Ingenuity Pathway Analysis networks associated with Cellular function and maintenance, Cellular assembly and organization, Developmental disorder and Organismal injury and abnormalities (p < 0.0001 to p = 0.0495). Target proteins were validated by multiplex fluorescence-based Western blot analyses using an additional, independent cohort of platelet protein samples [healthy controls (n = 15), early-stage CRCs (n = 15), late-stage CRCs (n = 15)]. Two proteins—clusterin and glutathione synthetase (GSH-S)—featured high impact and were subsequently validated in this independent clinical cohort distinguishing healthy controls from patients with early- and late-stage CRCs. Thus, the potential of clusterin and GSH-S as platelet biomarkers for early detection of CRC could improve existing screening modalities in clinical application and should be confirmed in a prospective multicenter trial.

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Abbreviations

2D-DIGE:

Two-dimensional multiplex fluorescence gel electrophoresis

BHT:

Butylated hydroxytoluene

CLU:

Clusterin

CRC:

Colorectal cancer

DTT:

Dithiothreitol

EDTA:

Ethylenediaminetetraacetate

EMT:

Epithelial-to-mesenchymal transition

FC:

Fold change

GSH-S:

Glutathione synthetase

IEF:

Isoelectric focusing

IPA:

Ingenuity Pathway Analysis

IPG:

Immobilized pH gradient

MALDI-TOF MS:

Matrix-assisted laser desorption/ionization time of flight mass spectrometry

PBS:

Phosphate-buffered saline

PCA:

Principal component analysis

PMSF:

Phenylmethylsulfonyl fluoride

PTMs:

Posttranslational modifications

SDS-PAGE:

Sodium dodecyl sulfate polyacrylamide gel electrophoresis

TBS:

Tris-buffered saline

UICC:

International Union Against Cancer

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Acknowledgements

Grants from the Werner and Clara Kreitz Foundation and the Ad Infinitum Foundation are gratefully acknowledged. This study was performed in connection with the Surgical Center for Translational Oncology—Lübeck (SCTO-L) and the North German Tumorbank of Colorectal Cancer (ColoNet), the latter being generously supported by the German Cancer Aid Foundation (DKH e.V. #108446).

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Author notes

  1. Sarah Strohkamp and Timo Gemoll contributed equally.

Authors and Affiliations

  1. Section for Translational Surgical Oncology and Biobanking, Department of Surgery, University of Lübeck and University Medical Center Schleswig-Holstein, Campus Lübeck, Ratzeburger Allee 160, 23538, Lübeck, Germany

    Sarah Strohkamp, Timo Gemoll, Sina Humborg, Uwe J. Roblick, Hans-Peter Bruch, Tobias Keck & Jens K. Habermann

  2. Institute of Clinical Biochemistry and Pathobiochemistry, Leibniz Center for Diabetes Research, German Diabetes Center at the Heinrich-Heine-University Düsseldorf, Düsseldorf, Germany

    Sonja Hartwig & Stefan Lehr

  3. German Center for Diabetes Research (DZD), München-Neuherberg, Germany

    Sonja Hartwig & Stefan Lehr

  4. Institute of Medical Informatics and Statistics, University Medical Center Schleswig-Holstein, Campus Kiel, Kiel, Germany

    Sandra Freitag-Wolf

  5. Karolinska Biomics Center, Karolinska Institutet, Stockholm, Sweden

    Susanne Becker, Bo Franzén & Gert Auer

  6. Clinic for Otorhinolaryngology, Head and Neck Surgery, University Medical Center Schleswig-Holstein, Campus Lübeck, Lübeck, Germany

    Ralph Pries & Barbara Wollenberg

  7. Interdisciplinary Center for Biobanking-Lübeck (ICB-L), University of Lübeck, Lübeck, Germany

    Jens K. Habermann

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  1. Sarah Strohkamp
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Corresponding authors

Correspondence to Timo Gemoll or Jens K. Habermann.

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Ethical standards

This study was approved by the local Ethics Committee of the University of Lübeck (#07-124). Blood samples of CRC patients and healthy volunteers were processed after informed consent and stored at the Interdisciplinary Centrum for Biobanking-Lübeck (ICB-L). The experiments comply with the current laws of the country in which they were performed.

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The authors declare that they have no conflicts of interest.

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18_2017_2631_MOESM1_ESM.pdf

Supplementary Fig. 1: Workflow of the study design. Supplementary Fig. 2 Preliminary in vitro platelet activation experiment. (A) Using a standard operating protocol, platelets were isolated from EDTA anticoagulated venous blood as a homogenous suspension. (B) After addition of 5 µg/ml collagen, 0.5 U/ml thrombin and 13.8 mmol/l CaCl2, artificially platelet activation was visible as white aggregates. Supplementary Fig. 3 Supervised PCA plots between (A) healthy controls (n = 12, pink) vs. late-stage CRCs (n = 5, purple) based on 44 significant spots, of (B) early-stage CRCs (n = 7, blue) vs. late-stage CRCs (n = 5, purple) based on 36 protein spots with significant changes (t test, p < 0.05) and between (C) healthy controls (n = 12, pink) vs. early-stage CRCs (n = 7, blue) vs. late-stage CRCs (n = 5, purple) based on 39 differentially expressed spots (1-way ANOVA, p < 0.05). Colored dots represent platelet samples from each group. Supplementary Fig. 4 2D-DIGE protein expression profiles of Clusterin (A), GSH-S (B) and Cofilin-1 (C) between healthy controls, early-stage CRCs and late-stage CRCs (PDF 1019 kb)

18_2017_2631_MOESM2_ESM.pdf

Supplementary Table 1 Clinical data of the evaluated patient cohort of the 2-D DIGE experiment. Supplementary Table 2 Clinical data of the evaluated patient cohort of the Western blot experiment. Supplementary Table 3 Summary of identified platelet proteins using MALDI-TOF/TOF–MS. Platelet protein identifications of 71 spots with significant differences in 2D-DIGE (t test, p < 0.05) using MALDI-TOF/TOF–MS and Mascot database. Mascot Scores marked with an asterisks (*) indicate MS data. Several spots are isoforms of the same protein. Arrows indicate significant protein down- (↓) or upregulation (↑) in CRC cancer samples compared to healthy controls (t test, p < 0.05 and 1-way ANOVA, p < 0.05). Supplementary Table 4 Summary of platelet protein pathway analyses of direct relationships using IPA. Supplemental Table 5 Diagnostic parameters for the Healthy volunteers vs. Early CRC comparison (top) and associated ROC-curve (bottom) for Clusterin (CLU). Supplemental Table 6 Diagnostic parameters for the Healthy volunteers vs. Early CRC comparison (top) and associated ROC-curve (bottom) for GSH-S. Supplemental Table 7 Diagnostic parameters for the Healthy volunteers vs. Early CRC comparison (top) and associated ROC-curve (bottom) for cofilin-1 (CFL-1) (PDF 809 kb)

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Strohkamp, S., Gemoll, T., Humborg, S. et al. Protein levels of clusterin and glutathione synthetase in platelets allow for early detection of colorectal cancer. Cell. Mol. Life Sci. 75, 323–334 (2018). https://doi.org/10.1007/s00018-017-2631-9

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