1. Sung H, Ferlay J, Siegel RL, et al. Global cancer statistics 2020:
GLOBOCAN estimates of incidence and mortality worldwide for
36 cancers in 185 countries. CA Cancer J Clin. 2021;71:209-249.
2. Amin MB, Greene FL, Edge SB, et al. The eighth edition AJCC
cancer staging manual: continuing to build a bridge from a
population-based to a more "personalized" approach to cancer
staging. CA Cancer J Clin. 2017;67:93-99.
3. Guinney J, Dienstmann R, Wang X, et al. The consensus molecular subtypes of colorectal cancer. Nat Med. 2015;21:1350-1356.
4. Vaidyanathan R, Soon RH, Zhang P, Jiang K, Lim CT. Cancer
diagnosis: from tumor to liquid biopsy and beyond. Lab Chip.
2018;19:11-34.
5. Hoshino A, Kim HS, Bojmar L, et al. Extracellular vesicle
and particle biomarkers define multiple human cancers. Cell.
2020;182:1044-1061.e18.
6. van Niel G, D'Angelo G, Raposo G. Shedding light on the
cell biology of extracellular vesicles. Nat Rev Mol Cell Biol.
2018;19:213-228.
7. Masuda T, Mori A, Ito S, Ohtsuki S. Quantitative and targeted
proteomics-based identification and validation of drug efficacy
biomarkers. Drug Metab Pharmacokinet. 2021;36:100361.
8. Vasaikar S, Huang C, Wang X, et al. Proteogenomic analysis
of human colon cancer reveals new therapeutic opportunities.
Cell. 2019;177(1035–1049):e1019.
9. Picotti P, Bodenmiller B, Aebersold R. Proteomics meets the scientific method. Nat Methods. 2013;10:24-27.
10. Brun V, Masselon C, Garin J, Dupuis A. Isotope dilution
strategies for absolute quantitative proteomics. J Proteomics.
2009;72:740-749.
11. Shiromizu T, Kume H, Ishida M, et al. Quantitation of putative
colorectal cancer biomarker candidates in serum extracellular
vesicles by targeted proteomics. Sci Rep. 2017;7:12782.
12. Kume H, Muraoka S, Kuga T, et al. Discovery of colorectal
cancer biomarker candidates by membrane proteomic analysis and subsequent verification using selected reaction monitoring (SRM) and tissue microarray (TMA) analysis. Mol Cell
Proteomics. 2014;13:1471-1484.
13. Ishizaki J, Takemori A, Suemori K, et al. Targeted proteomics
reveals promising biomarkers of disease activity and organ involvement in antineutrophil cytoplasmic antibody-associated
vasculitis. Arthritis Res Ther. 2017;19:218.
14. Kim Y, Jeon J, Mejia S, et al. Targeted proteomics identifies
liquid-biopsy signatures for extracapsular prostate cancer. Nat
Commun. 2016;7:11906.
15. You J, Kao A, Dillon R, et al. A large-scale and robust dynamic
MRM study of colorectal cancer biomarkers. J Proteomics.
2018;187:80-92.
16. Chen Y, Xie Y, Xu L, et al. Protein content and functional characteristics of serum-purified exosomes from patients with colorectal cancer revealed by quantitative proteomics. Int J Cancer.
2017;140:900-913.
20457634, 0, Downloaded from https://onlinelibrary.wiley.com/doi/10.1002/cam4.5442 by Cochrane Japan, Wiley Online Library on [17/11/2022]. See the Terms and Conditions (https://onlinelibrary.wiley.com/terms-and-conditions) on Wiley Online Library for rules of use; OA articles are governed by the applicable Creative Commons License
10 17. Narumi R, Shimizu Y, Ukai-
Tadenuma M, et al. Mass
spectrometry-based absolute quantification reveals rhythmic
variation of mouse circadian clock proteins. Proc Natl Acad Sci
U S A. 2016;113:E3461-E3467.
18. Narumi R, Masuda K, Tomonaga T, Adachi J, Ueda HR,
Shimizu Y. Cell-free synthesis of stable isotope-labeled internal standards for targeted quantitative proteomics. Synth Syst
Biotechnol. 2018;3:97-104.
19. Mathivanan S, Fahner CJ, Reid GE, Simpson RJ. ExoCarta
2012: database of exosomal proteins, RNA and lipids. Nucleic
Acids Res. 2012;40:D1241-D1244.
20. Kusebauch U, Campbell DS, Deutsch EW, et al. Human
SRMAtlas: a resource of targeted assays to quantify the complete human proteome. Cell. 2016;166:766-778.
21. Shimizu Y, Inoue A, Tomari Y, et al. Cell-free translation reconstituted with purified components. Nat Biotechnol. 2001;19:751-755.
22. Hayes DN, Monti S, Parmigiani G, et al. Gene expression profiling reveals reproducible human lung adenocarcinoma subtypes in multiple independent patient cohorts. J Clin Oncol.
2006;24:5079-5090.
23. Verhaak RG, Hoadley KA, Purdom E, et al. Integrated genomic
analysis identifies clinically relevant subtypes of glioblastoma
characterized by abnormalities in PDGFRA, IDH1, EGFR, and
NF1. Cancer Cell. 2010;17:98-110.
24. Wei R, Wang J, Su M, et al. Missing value imputation approach for
mass spectrometry-based metabolomics data. Sci Rep. 2018;8:663.
25. Senbabaoglu Y, Michailidis G, Li JZ. Critical limitations of consensus clustering in class discovery. Sci Rep. 2014;4:6207.
26. Siegel RL, Miller KD, Goding Sauer A, et al. Colorectal cancer
statistics, 2020. CA Cancer J Clin. 2020;70:145-164.
27. Koncina E, Haan S, Rauh S, Letellier E. Prognostic and predictive molecular biomarkers for colorectal cancer: updates and
challenges. Cancers (Basel). 2020;12:319.
28. Fu Y, Lin L, Xia L. MiR-107 function as a tumor suppressor
gene in colorectal cancer by targeting transferrin receptor 1.
Cell Mol Biol Lett. 2019;24:31.
29. Perego M, Tyurin VA, Tyurina YY, et al. Reactivation of dormant
tumor cells by modified lipids derived from stress-activated
neutrophils. Sci Transl Med. 2020;12:eabb5817.
30. Kajino-Sakamoto R, Fujishita T, Taketo MM, Aoki M. Synthetic
lethality between MyD88 loss and mutations in Wnt/beta-
catenin pathway in intestinal tumor epithelial cells. Oncogene.
2021;40:408-420.
31. Kasprzak A, Adamek A. Insulin-like growth factor 2 (IGF2)
signaling in colorectal cancer-from basic research to potential
clinical applications. Int J Mol Sci. 2019;20:4915.
32. Wu Q, Wang D, Zhang Z, et al. DEFB4A is a potential prognostic biomarker for colorectal cancer. Oncol Lett. 2020;20:114.
33. Ligresti G, Aplin AC, Dunn BE, Morishita A, Nicosia RF. The
acute phase reactant orosomucoid-1 is a bimodal regulator of
angiogenesis with time-and context-dependent inhibitory and
stimulatory properties. PLoS One. 2012;7:e41387.
34. Duche JC, Urien S, Simon N, Malaurie E, Monnet I, Barre J.
Expression of the genetic variants of human alpha-1-acid glycoprotein in cancer. Clin Biochem. 2000;33:197-202.
35. Ayyub A, Saleem M, Fatima I, Tariq A, Hashmi N,
Musharraf SG. Glycosylated Alpha-1-acid glycoprotein 1 as
11
a potential lung cancer serum biomarker. Int J Biochem Cell
Biol. 2016;70:68-75.
36. Li F, Yu Z, Chen P, et al. The increased excretion of urinary
orosomucoid 1 as a useful biomarker for bladder cancer. Am J
Cancer Res. 2016;6:331-340.
37. Chantaraamporn J, Champattanachai V, Khongmanee A, et al.
Glycoproteomic analysis reveals aberrant expression of complement C9 and fibronectin in the plasma of patients with colorectal cancer. Proteomes. 2020;8:26.
38. Saraswat M, Joenvaara S, Musante L, Peltoniemi H, Holthofer
H, Renkonen R. N-linked (N-) glycoproteomics of urinary exosomes. [corrected]. Mol Cell Proteomics. 2015;14:263-276.
39. Repetto O, Lovisa F, Elia C, et al. Proteomic exploration of
plasma exosomes and other small extracellular vesicles in pediatric Hodgkin lymphoma: a potential source of biomarkers for
relapse occurrence. Diagnostics (Basel). 2021;11:917.
40. Laine E, Couderc R, Roch-Arveiller M, Vasson MP, Giroud JP,
Raichvarg D. Modulation of human polymorphonuclear neutrophil functions by alpha 1-acid glycoprotein. Inflammation.
1990;14:1-9.
41. Elg SA, Mayer AR, Carson LF, Twiggs LB, Hill RB,
Ramakrishnan S. Alpha-1 acid glycoprotein is an immunosuppressive factor found in ascites from ovaria carcinoma. Cancer.
1997;80:1448-1456.
42. Snyder S, Coodley EL. Inhibition of platelet aggregation by
alpha1-acid glycoprotein. Arch Intern Med. 1976;136:778-781.
43. Muchitsch EM, Teschner W, Linnau Y, Pichler L. In vivo effect
of alpha 1-acid glycoprotein on experimentally enhanced capillary permeability in Guinea-pig skin. Arch Int Pharmacodyn
Ther. 1996;331:313-321.
44. Xie F, Zhou X, Fang M, et al. Extracellular vesicles in cancer
immune microenvironment and cancer immunotherapy. Adv
Sci (Weinh). 2019;6:1901779.
45. Sun Y, Wang F, Zhou Z, et al. Urinary proteomics identifying
novel biomarkers for the diagnosis of adult-onset Still's disease.
Front Immunol. 2020;11:2112.
46. Erozenci LA, Bottger F, Bijnsdorp IV, Jimenez CR. Urinary exosomal proteins as (pan-) cancer biomarkers: insights from the
proteome. FEBS Lett. 2019;593:1580-1597.
SUPPORTING INFORMATION
Additional supporting information can be found online in
the Supporting Information section at the end of this article.
How to cite this article: Kasahara K, Narumi R,
Nagayama S, et al. A large-scale targeted
proteomics of plasma extracellular vesicles shows
utility for prognosis prediction subtyping in
colorectal cancer. Cancer Med. 2022;00:1-11. doi:
10.1002/cam4.5442
20457634, 0, Downloaded from https://onlinelibrary.wiley.com/doi/10.1002/cam4.5442 by Cochrane Japan, Wiley Online Library on [17/11/2022]. See the Terms and Conditions (https://onlinelibrary.wiley.com/terms-and-conditions) on Wiley Online Library for rules of use; OA articles are governed by the applicable Creative Commons License
KASAHARA et al.
...
論文の公開元へ
