Identification of Highly Sensitive Pleural Effusion Protein Biomarkers for Malignant Pleural Mesothelioma by Affinity-Based Quantitative Proteomics
Abstract
:Simple Summary
Abstract
1. Introduction
2. Materials and Methods
2.1. Patients and Patient Samples
2.2. Sample Processing
2.3. Isobaric Labelling of Tryptic Peptides
2.4. Proteome Analysis
2.4.1. Off-Line Fractionation
2.4.2. Orbitrap Mass Spectrometry
2.4.3. Targeted Analysis of Mesothelin and Fibulin-3 by Multiple-Reaction-Monitoring Mass Spectrometry
2.4.4. Raw Data Processing
2.5. Statistical Analysis
3. Results
3.1. Identification of Biomarkers for Malignant Mesothelioma
3.2. Analysis of the Previously Identified MPM Protein Biomarkers Fibulin-3 and Mesothelin
3.3. Identification of Subtype-Specific Proteins for Differentiating MPM Subtypes
4. Discussion
5. Conclusions
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Acknowledgments
Conflicts of Interest
References
- Robinson, B.M. Malignant pleural mesothelioma: An epidemiological perspective. Ann. Cardiothorac. Surg. 2012, 1, 491–496. [Google Scholar] [CrossRef] [PubMed]
- Liu, G.; Cheresh, P.; Kamp, D.W. Molecular basis of asbestos-induced lung disease. Annu. Rev. Pathol. 2013, 8, 161–187. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Thompson, J.K.; Westbom, C.M.; Shukla, A. Malignant mesothelioma: Development to therapy. J. Cell. Biochem. 2014, 115, 1–7. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Robinson, B.W.; Musk, A.W.; Lake, R.A. Malignant mesothelioma. Lancet 2005, 366, 397–408. [Google Scholar] [CrossRef] [PubMed]
- Creaney, J.; Segal, A.; Olsen, N.; Dick, I.M.; Musk, A.W.; Skates, S.J.; Robinson, B.W. Pleural fluid mesothelin as an adjunct to the diagnosis of pleural malignant mesothelioma. Dis. Markers 2014, 2014, 413946. [Google Scholar] [CrossRef] [Green Version]
- Hollevoet, K.; Reitsma, J.B.; Creaney, J.; Grigoriu, B.D.; Robinson, B.W.; Scherpereel, A.; Cristaudo, A.; Pass, H.I.; Nackaerts, K.; Rodriguez Portal, J.A.; et al. Serum mesothelin for diagnosing malignant pleural mesothelioma: An individual patient data meta-analysis. J. Clin. Oncol. 2012, 30, 1541–1549. [Google Scholar] [CrossRef] [Green Version]
- Pass, H.I.; Levin, S.M.; Harbut, M.R.; Melamed, J.; Chiriboga, L.; Donington, J.; Huflejt, M.; Carbone, M.; Chia, D.; Goodglick, L.; et al. Fibulin-3 as a blood and effusion biomarker for pleural mesothelioma. N. Engl. J. Med. 2012, 367, 1417–1427. [Google Scholar] [CrossRef] [Green Version]
- Pei, D.; Li, Y.; Liu, X.; Yan, S.; Guo, X.; Xu, X.; Guo, X. Diagnostic and prognostic utilities of humoral fibulin-3 in malignant pleural mesothelioma: Evidence from a meta-analysis. Oncotarget 2017, 8, 13030–13038. [Google Scholar] [CrossRef] [Green Version]
- Kao, S.C.; Kirschner, M.B.; Cooper, W.A.; Tran, T.; Burgers, S.; Wright, C.; Korse, T.; van den Broek, D.; Edelman, J.; Vallely, M.; et al. A proteomics-based approach identifies secreted protein acidic and rich in cysteine as a prognostic biomarker in malignant pleural mesothelioma. Br. J. Cancer 2016, 114, 524–531. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Palstrom, N.B.; Rasmussen, L.M.; Beck, H.C. Affinity Capture Enrichment versus Affinity Depletion: A Comparison of Strategies for Increasing Coverage of Low-Abundant Human Plasma Proteins. Int. J. Mol. Sci. 2020, 21, 5903. [Google Scholar] [CrossRef]
- Andersen, L.C.; Palstrom, N.B.; Diederichsen, A.; Lindholt, J.S.; Rasmussen, L.M.; Beck, H.C. Determining Plasma Protein Variation Parameters as a Prerequisite for Biomarker Studies-A TMT-Based LC-MSMS Proteome Investigation. Proteomes 2021, 9, 47. [Google Scholar] [CrossRef] [PubMed]
- Overgaard, M.; Cangemi, C.; Jensen, M.L.; Argraves, W.S.; Rasmussen, L.M. Total and isoform-specific quantitative assessment of circulating fibulin-1 using selected reaction monitoring MS and time-resolved immunofluorometry. Proteom. Clin. Appl. 2015, 9, 767–775. [Google Scholar] [CrossRef] [PubMed]
- Shen, J.; Pagala, V.R.; Breuer, A.M.; Peng, J.; Bin, M.; Wang, X. Spectral Library Search Improves Assignment of TMT Labeled MS/MS Spectra. J. Proteome Res. 2018, 17, 3325–3331. [Google Scholar] [CrossRef] [PubMed]
- MacLean, B.; Tomazela, D.M.; Shulman, N.; Chambers, M.; Finney, G.L.; Frewen, B.; Kern, R.; Tabb, D.L.; Liebler, D.C.; MacCoss, M.J. Skyline: An open source document editor for creating and analyzing targeted proteomics experiments. Bioinformatics 2010, 26, 966–968. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Debrabant, B.; Halekoh, U.; Soerensen, M.; Moller, J.E.; Hassager, C.; Frydland, M.; Palstrom, N.; Hjelmborg, J.; Beck, H.C.; Rasmussen, L.M. STEMI, Cardiogenic Shock, and Mortality in Patients Admitted for Acute Angiography: Associations and Predictions from Plasma Proteome Data. Shock 2021, 55, 41–47. [Google Scholar] [CrossRef]
- Palstrom, N.B.; Matthiesen, R.; Beck, H.C. Data Imputation in Merged Isobaric Labeling-Based Relative Quantification Datasets. Methods Mol. Biol. 2020, 2051, 297–308. [Google Scholar] [CrossRef]
- Beck, H.C.; Jensen, L.O.; Gils, C.; Ilondo, A.M.M.; Frydland, M.; Hassager, C.; Moller-Helgestad, O.K.; Moller, J.E.; Rasmussen, L.M. Proteomic Discovery and Validation of the Confounding Effect of Heparin Administration on the Analysis of Candidate Cardiovascular Biomarkers. Clin. Chem. 2018, 64, 1474–1484. [Google Scholar] [CrossRef] [Green Version]
- Creaney, J.; Dick, I.M.; Meniawy, T.M.; Leong, S.L.; Leon, J.S.; Demelker, Y.; Segal, A.; Musk, A.W.; Lee, Y.C.; Skates, S.J.; et al. Comparison of fibulin-3 and mesothelin as markers in malignant mesothelioma. Thorax 2014, 69, 895–902. [Google Scholar] [CrossRef] [Green Version]
- Kirschner, M.B.; Pulford, E.; Hoda, M.A.; Rozsas, A.; Griggs, K.; Cheng, Y.Y.; Edelman, J.J.; Kao, S.C.; Hyland, R.; Dong, Y.; et al. Fibulin-3 levels in malignant pleural mesothelioma are associated with prognosis but not diagnosis. Br. J. Cancer 2015, 113, 963–969. [Google Scholar] [CrossRef] [Green Version]
- Xu, W.; Ying, Y.; Shan, L.; Feng, J.; Zhang, S.; Gao, Y.; Xu, X.; Yao, Y.; Zhu, C.; Mao, W. Enhanced expression of cohesin loading factor NIPBL confers poor prognosis and chemotherapy resistance in non-small cell lung cancer. J. Transl. Med. 2015, 13, 153. [Google Scholar] [CrossRef]
- Ween, M.P.; Oehler, M.K.; Ricciardelli, C. Transforming growth Factor-Beta-Induced Protein (TGFBI)/(betaig-H3): A matrix protein with dual functions in ovarian cancer. Int. J. Mol. Sci. 2012, 13, 10461–10477. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Tanrıverdi, Z.; Meteroglu, F.; Yüce, H.; Şenyiğit, A.; Işcan, M.; Unüvar, S. The usefulness of biomarkers in diagnosis of asbestos-induced malignant pleural mesothelioma. Hum. Exp. Toxicol. 2021, 40, 1817–1824. [Google Scholar] [CrossRef] [PubMed]
- Giusti, L.; Da Valle, Y.; Bonotti, A.; Donadio, E.; Ciregia, F.; Ventroni, T.; Foddis, R.; Giannaccini, G.; Guglielmi, G.; Cristaudo, A.; et al. Comparative proteomic analysis of malignant pleural mesothelioma evidences an altered expression of nuclear lamin and filament-related proteins. Proteom. Clin. Appl. 2014, 8, 258–268. [Google Scholar] [CrossRef]
- Boccellino, M.; Pinto, F.; Ieluzzi, V.; Giovane, A.; Quagliuolo, L.; Fariello, C.; Coppola, M.; Carlucci, A.; Santini, M.; Ferati, K.; et al. Proteomics analysis of human serum of patients with non-small-cell lung cancer reveals proteins as diagnostic biomarker candidates. J. Cell. Physiol. 2019, 234, 23798–23806. [Google Scholar] [CrossRef] [PubMed]
- Singhal, S.; Wiewrodt, R.; Malden, L.D.; Amin, K.M.; Matzie, K.; Friedberg, J.; Kucharczuk, J.C.; Litzky, L.A.; Johnson, S.W.; Kaiser, L.R.; et al. Gene expression profiling of malignant mesothelioma. Clin. Cancer Res. 2003, 9, 3080–3097. [Google Scholar] [PubMed]
- Lin, T.Y.; Yang, C.H.; Chou, H.C.; Cheng, C.M.; Liu, Y.W.; Wang, J.Y.; Huang, L.R.; Tsai, S.F.; Huang, S.F.; Chen, Y.R. EGFR Mutation-Harboring Lung Cancer Cells Produce CLEC11A with Endothelial Trophic and Tumor-Promoting Activities. Cancers 2022, 14, 1356. [Google Scholar] [CrossRef]
- Cordeiro, Y.G.; Mulder, L.M.; van Zeijl, R.J.M.; Paskoski, L.B.; van Veelen, P.; de Ru, A.; Strefezzi, R.F.; Heijs, B.; Fukumasu, H. Proteomic Analysis Identifies FNDC1, A1BG, and Antigen Processing Proteins Associated with Tumor Heterogeneity and Malignancy in a Canine Model of Breast Cancer. Cancers 2021, 13, 5901. [Google Scholar] [CrossRef]
- Pappas, A.G.; Magkouta, S.; Pateras, I.S.; Skianis, I.; Moschos, C.; Vazakidou, M.E.; Psarra, K.; Gorgoulis, V.G.; Kalomenidis, I. Versican modulates tumor-associated macrophage properties to stimulate mesothelioma growth. Oncoimmunology 2019, 8, e1537427. [Google Scholar] [CrossRef] [Green Version]
- Tu, H.; Li, J.; Lin, L.; Wang, L. COL11A1 Was Involved in Cell Proliferation, Apoptosis and Migration in Non-Small Cell Lung Cancer Cells. J. Investig. Surg. 2021, 34, 664–669. [Google Scholar] [CrossRef]
- Liao, X.; Wang, W.; Yu, B.; Tan, S. Thrombospondin-2 acts as a bridge between tumor extracellular matrix and immune infiltration in pancreatic and stomach adenocarcinomas: An integrative pan-cancer analysis. Cancer Cell Int. 2022, 22, 213. [Google Scholar] [CrossRef]
- Battolla, E.; Canessa, P.A.; Ferro, P.; Franceschini, M.C.; Fontana, V.; Dessanti, P.; Pinelli, V.; Morabito, A.; Fedeli, F.; Pistillo, M.P.; et al. Comparison of the Diagnostic Performance of Fibulin-3 and Mesothelin in Patients with Pleural Effusions from Malignant Mesothelioma. Anticancer Res. 2017, 37, 1387–1391. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Schillebeeckx, E.; van Meerbeeck, J.P.; Lamote, K. Clinical utility of diagnostic biomarkers in malignant pleural mesothelioma: A systematic review and meta-analysis. Eur. Respir. Rev. 2021, 30, 210057. [Google Scholar] [CrossRef]
- Fuhrman, C.; Duche, J.C.; Chouaid, C.; Abd Alsamad, I.; Atassi, K.; Monnet, I.; Tillement, J.P.; Housset, B. Use of tumor markers for differential diagnosis of mesothelioma and secondary pleural malignancies. Clin. Biochem. 2000, 33, 405–410. [Google Scholar] [CrossRef] [PubMed]
- Wang, X.F.; Wu, Y.H.; Wang, M.S.; Wang, Y.S. CEA, AFP, CA125, CA153 and CA199 in malignant pleural effusions predict the cause. Asian Pac. J. Cancer Prev. 2014, 15, 363–368. [Google Scholar] [CrossRef] [Green Version]
- Filiberti, R.; Parodi, S.; Libener, R.; Ivaldi, G.P.; Canessa, P.A.; Ugolini, D.; Bobbio, B.; Marroni, P. Diagnostic value of mesothelin in pleural fluids: Comparison with CYFRA 21-1 and CEA. Med. Oncol. 2013, 30, 543. [Google Scholar] [CrossRef]
- Alatas, F.; Alatas, O.; Metintas, M.; Colak, O.; Harmanci, E.; Demir, S. Diagnostic value of CEA, CA 15-3, CA 19-9, CYFRA 21-1, NSE and TSA assay in pleural effusions. Lung Cancer 2001, 31, 9–16. [Google Scholar] [CrossRef] [PubMed]
- Otoshi, T.; Kataoka, Y.; Ikegaki, S.; Saito, E.; Matsumoto, H.; Kaku, S.; Shimada, M.; Hirabayashi, M. Pleural effusion biomarkers and computed tomography findings in diagnosing malignant pleural mesothelioma: A retrospective study in a single center. PLoS One 2017, 12, e0185850. [Google Scholar] [CrossRef]
Variables | MPM (n = 40) | Benign (n = 44) |
---|---|---|
Age (mean ± SD) | 71.54 ± 8.61 | 68.88 ± 8.82 |
Gender | ||
Male (%) | 35 (87.5) | 36 (81.8) |
Female (%) | 5 (12.5) | 8 (18.2) |
MM Histology (%) | ||
Biphasic | 10 (25) | - |
Epithelioid | 26 (65) | - |
Unknown | 4 (10) | - |
Benign Histology (%) | ||
Fibrosis | 8 (18) | |
Inflammation | 11 (25) | |
Nonspecific reactive change | 19 (43) | |
Others * | 6 (14) |
SwissProt ID | Protein Name | Gene Name | Fold-Change | p-Value | Importance Score |
---|---|---|---|---|---|
Q08380 | Galectin-3-binding protein | LGALS3BP | 1.51 #/1.69 * | 1.44 × 10−5 #/8.22 × 10−12 * | 10.31 #/29.27 * |
Q15063 | Periostin | POSTN | 1.31 | 0.018 | 8.09 |
P00738 | Haptoglobin | HP | 1.22 | 0.0011 | 6.90 |
P02774 | Vitamin D-binding protein | GC | 1.08 | 0.0036 | 6.54 |
Q12805 | Fibulin-3 | EFEMP1 | 1.12 | 0.004 | 6.46 |
Q92563 | Testican-2 | SPOCK2 | 2.78 | 1.33 × 10−11 | 23.67 |
Q15582 | Beta ig-h3 | TGFBI | 1.56 | 6.44 × 10−7 | 15.16 |
P02760 | Protein AMBP | AMBP | 1.35 | 5.28 × 10−10 | 12.79 |
Q6KC79 | Nipped-B-like protein | NIPBL | 1.64 | 0.00037 | 7.26 |
P21741 | Midkine | MDK | 1.63 | 0.0013 | 7.21 |
Q96GQ7 | DEAD box protein 27 | DDX27 | 1.40 | 0.01 | 6.94 |
Q6ZRQ5 | Protein MMS22-like | MMS22L | 1.80 | 0.0015 | 6.94 |
Q99715 | Collagen alpha-1(XII) chain | COL12A1 | 1.42 | 0.00290 | 6.31 |
Q8WWA0 | Intelectin-1 | ITLN1 | 2.26 | 0.0049 | 5.70 |
O00468-6 | Agrin | AGRN | 1.56 | 0.00051 | 5.21 |
Variables | Sensitivity | Specificity | PPV | NPV | Accuracy | AUC (95% CI) |
---|---|---|---|---|---|---|
Higher abundant proteins Protein accession (gene name) Q08380 (LGALS3BP), P00738 (HP), Q15063 (POSTN) | 0.97 | 0.93 | 0.93 | 0.97 | 0.95 | 0.99 (0.98–1.00) |
Lower abundant proteins Q92563 (SPOCK2), Q6KC79 (NIPBL), Q15582 (TGFBI), P02760 (AMBP) | 0.90 | 0.89 | 0.88 | 0.91 | 0.89 | 0.97 (0.94–1.00) |
Combined Q92563 (SPOCK2), P00738 (HP), Q15582 (TGFBI), P02760 (AMBP), Q08380 (LGALS3BP) | 1.00 | 0.98 | 0.98 | 1.00 | 0.99 | 0.99 (0.99–1.00) |
SwissProt ID | Protein Name | Gene | Fold-Change (Biphasic/Epithelioid) | p-Value |
---|---|---|---|---|
Higher abundant proteins | ||||
Q9HC84 | Mucin-5B | MUC5B | 1.49 | 0.00068 |
P23381 | Tryptophan-tRNA ligase | WARS1 | 1.42 | 0.0023 |
Q15582 | Beta ig-h3 | TGFBI | 1.31 | 0.0025 |
P04217 | Alpha-1B-glycoprotein | A1BG | 1.10 | 0.0043 |
Q9Y240 | C-type lectin domain F11A | CLEC11A | 1.62 | 0.0054 |
Lower abundant proteins | ||||
Q4ZHG4 | Fibronectin type III protein 1 | FNDC1 | 2.23 | 2.47 × 10−5 |
P13611 | Versican core protein | VCAN | 2.12 | 0.00064 |
P12107 | Collagen alpha-1(XI) chain | COL11A1 | 1.83 | 0.00075 |
P35442 | Thrombospondin-2 | THBS2 | 1.67 | 0.0017 |
Q16363 | Laminin subunit alpha-4 | LAMA4 | 1.62 | 0.0018 |
SwissProt ID | Protein ID | Gene | Cancer-Related | Biological Process |
---|---|---|---|---|
Q08380 | Galectin-3-binding protein | LGALS3BP | Yes [25] | cell adhesion |
Q15063 | Periostin | POSTN | Yes [22] | cell adhesion |
P00738 | Haptoglobin | HP | Yes [23] | acute-phase response |
Q92563 | Testican-2 | SPOCK2 | No | extracellular matrix organization |
Q15582 | Beta ig-h3 | TGFBI | Yes [21] | angiogenesis |
P02760 | Protein AMBP | AMBP | Yes [24] | cell adhesion |
Q6KC79 | Nipped-B-like protein | NIPBL | Yes [20] | cellular response to DNA damage |
Q9HC84 | Mucin-5B | MUC5B | No | |
P23381 | Tryptophan--tRNA ligase | WARS1 | No | angiogenesis |
P04217 | Alpha-1B-glycoprotein | A1BG | No | |
Q9Y240 | C-type lectin domain F11A | CLEC11A | Yes [26] | ossification |
Q4ZHG4 | Fibronectin type III protein 1 | FNDC1 | Yes [27] | |
P13611 | Versican core protein | VCAN | Yes [28] | cell adhesion |
P12107 | Collagen alpha-1(XI) chain | COL11A1 | Yes [29] | cartilage condensation |
P35442 | Thrombospondin-2 | THBS2 | Yes [30] | cell adhesion |
Q16363 | Laminin subunit alpha-4 | LAMA4 | No | cell adhesion |
Disclaimer/Publisher’s Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content. |
© 2023 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
Share and Cite
Palstrøm, N.B.; Overgaard, M.; Licht, P.; Beck, H.C. Identification of Highly Sensitive Pleural Effusion Protein Biomarkers for Malignant Pleural Mesothelioma by Affinity-Based Quantitative Proteomics. Cancers 2023, 15, 641. https://doi.org/10.3390/cancers15030641
Palstrøm NB, Overgaard M, Licht P, Beck HC. Identification of Highly Sensitive Pleural Effusion Protein Biomarkers for Malignant Pleural Mesothelioma by Affinity-Based Quantitative Proteomics. Cancers. 2023; 15(3):641. https://doi.org/10.3390/cancers15030641
Chicago/Turabian StylePalstrøm, Nicolai B., Martin Overgaard, Peter Licht, and Hans C. Beck. 2023. "Identification of Highly Sensitive Pleural Effusion Protein Biomarkers for Malignant Pleural Mesothelioma by Affinity-Based Quantitative Proteomics" Cancers 15, no. 3: 641. https://doi.org/10.3390/cancers15030641