Profiling proteoforms: Promising follow-up of proteomics for biomarker discovery

Expert Review of Proteomics

Volumn 11, Issue 1, 2014, Pages 121-129

  Lisitsa, Andrey ^a   Moshkovskii, Sergei ^a,b   Chernobrovkin, Aleksey ^a,c   Ponomarenko, Elena ^a   Archakov, Alexander ^a  

^a INSTITUTE OF BIOMEDICAL CHEMISTRY   (Russian Federation)

^b PIROGOV RUSSIAN NATIONAL RESEARCH MEDICAL UNIVERSITY   (Russian Federation)

^c KAROLINSKA INSTITUTE   (Sweden)

Author keywords

alternative splicing; biomarkers; cancer genome; cancer proteome; post translational modifications; proteoformics; selected reaction monitoring; targeted proteomics

Indexed keywords

BIOLOGICAL MARKER;

ALTERNATIVE RNA SPLICING; AMINO ACID SEQUENCE; BIOINFORMATICS; BODY FLUID; CANCER CELL; FOLLOW UP; GENOME; HUMAN; NEOPLASM; PROTEIN PROCESSING; PROTEOMICS; REVIEW; SOMATIC MUTATION; TANDEM MASS SPECTROMETRY;

ALTERNATIVE SPLICING; ANIMALS; BIOLOGICAL MARKERS; COMPUTATIONAL BIOLOGY; HUMANS; NEOPLASMS; PROTEIN PROCESSING, POST-TRANSLATIONAL; PROTEOME; PROTEOMICS;

EID: 84893135401     PISSN: 14789450     EISSN: 17448387     Source Type: Journal    
DOI: 10.1586/14789450.2014.878652     Document Type: Review

References (59)

1. Zhang Z, Bast RC, Yu Y, et al. Three biomarkers identified from serum proteomic analysis for the detection of early stage ovarian cancer. Cancer Res 2004;64(16): 5882-90
2. Li XJ, Hayward C, Fong PY, et al. A blood-based proteomic classifier for the molecular characterization of pulmonary nodules. Sci Transl Med 2013;5(207): 207ra142
3. Smith LM, Kelleher NL. Proteoform: a single term describing protein complexity. Nat Methods 2013;10(3):186-7 . A paper where the term 'proteoform' is used for the first time to designate each of many molecular species originating from one protein-coding gene.
4. Tang W, Fei Y, Page M. Biological significance of RNA editing in cells. Mol Biotechnol 2012;52(1):91-100
5. Stratton M, Campbell P, Futreal P. The cancer genome. Nature 2009;458(7239): 719-24
6. Li J, Su Z, Ma Z-Q, et al. A bioinformatics workflow for variant peptide detection in shotgun proteomics. Mol Cell Proteomics 2011;10(5):M110.006536 . One of the first attempts to identify proteins from bottom-up proteomics of trypsinized samples using cancer genome database with somatic mutations that influence the protein sequence.
7. Tran JC, Zamdborg L, Ahlf DR, et al. Mapping intact protein isoforms in discovery mode using top-down proteomics. Nature 2011;480(7376):254-8 . A pioneer work in the field of large-scale top-down proteomics analyzing the intact proteins by extremely high-resolution mass spectrometry.
8. Nedelkov D, Kiernan UA, Niederkofler EE, et al. Population proteomics: the concept, attributes, and potential for cancer biomarker research. Mol Cell Proteomics 2006;5(10):1811-18
9. Nedelkov D, Kiernan UA, Niederkofler EE, et al. Investigating diversity in human plasma proteins. Proc Natl Acad Sci USA 2005;102(31):10852-7 . An origin of proteoformics. Variants of proteins were measured in human blood plasma by MALDI-TOF.
10. Li M, Durbin KR, Sweet SMM, et al. Oncogene-induced cellular senescence elicits an anti-Warburg effect. Proteomics 2013; 13(17):2585-96
11. Archakov A, Zgoda V, Kopylov A, et al. Chromosome-centric approach to overcoming bottlenecks in the Human Proteome Project. Exp Rev Proteomics 2012;9(6):667-76
12. Veenstra TD. Where are all the biomarkers? Exp Rev Proteomics 2011;8(6):681-3
13. Ning K, Nesvizhskii AI. The utility of mass spectrometry-based proteomic data for validation of novel alternative splice forms reconstructed from RNA-Seq data: a preliminary assessment. BMC Bioinformatics 2010;11(Suppl 1):S14
14. Whiteaker JR, Zhao L, Anderson L, Paulovich AG. An automated and multiplexed method for high throughput peptide immunoaffinity enrichment and multiple reaction monitoring mass spectrometry-based quantification of protein biomarkers. Mol Cell Proteomics 2010;9(1): 184-96
15. Kopylov AT, Zgoda VG, Lisitsa AV, Archakov AI. Combined use of irreversible binding and MRM technology for low- and ultralow copy-number protein detection and quantitation. Proteomics 2013;13(5): 727-42
16. Wis'niewski JR, Ostasiewicz P, Duś K, et al. Extensive quantitative remodeling of the proteome between normal colon tissue and adenocarcinoma. Mol Syst Biol 2012;8:611
17. Ingram VM. Gene mutations in human haemoglobin: the chemical difference between normal and sickle cell haemoglobin. Nature 1957;180(4581): 326-8
18. Coelho Graça D, Lescuyer P, Clerici L, et al. Electron transfer dissociation mass spectrometry of hemoglobin on clinical samples. J Am Soc Mass Spectrom 2012; 23(10):1750-6
19. Bunger MK, Cargile BJ, Sevinsky JR, et al. Detection and validation of non-synonymous coding SNPs from orthogonal analysis of shotgun proteomics data. J Proteome Res 2007;6(6):2331-40
20. Wheeler DA, Wang L. From human genome to cancer genome: the first decade. Genome Res 2013;23(7):1054-62
21. Li J, Duncan DT, Zhang B. CanProVar: a human cancer proteome variation database. Hum Mutat 2010;31(3):219-28
22. Shepherd R, Forbes SA, Beare D, et al. Data mining using the Catalogue of Somatic Mutations in Cancer BioMart. Database 2011;2011:bar018
23. Jennings J, Hudson TJ. Reflections on the founding of the International Cancer Genome Consortium. Clin Chem 2013; 59(1):18-21
24. Wu J-R, Zeng R. Molecular basis for population variation: from SNPs to SAPs. FEBS Lett 2012;586(18):2841-5
25. Takeshita H, Fujihara J, Ueki M, et al. Nonsynonymous single-nucleotide polymorphisms of the human apoptosis-related endonuclease-DNA fragmentation factor beta polypeptide, endonuclease G, and Flap endonuclease-1- genes show a low degree of genetic heterogeneity. DNA Cell Biol 2012;31(1): 36-42
26. Su Z-D, Sun L, Yu D-X, et al. Quantitative detection of single amino acid polymorphisms by targeted proteomics. J Mol Cell Biol 2011;3(5):309-15
27. Wang Q, Chaerkady R, Wu J, et al. Mutant proteins as cancer-specific biomarkers. Proc Natl Acad Sci USA 2011; 108(6):2444-9 . The paper illustrates the idea of cancer-specific mutated proteins as biomarkers with absolute specificity. Mutated RAS protein is exemplified as marker and its levels are measured using selected reaction monitoring in clinical samples.
28. The Cancer Genome Atlas Network. Comprehensive molecular characterization of human colon and rectal cancer. Nature 2012;487(7407):330-7
29. Xin F, Radivojac P. Post-translational modifications induce significant yet not extreme changes to protein structure. Bioinformatics 2012;28(22):2905-13
30. Vizcai'no JA, Côté RG, Csordas A, et al. The proteomics identifications (PRIDE) database and associated tools: status in 2013. Nucleic Acids Res 2013; 41(Database issue):D1063-9
31. Gholami AM, Hahne H, Wu Z, et al. Global proteome analysis of the NCI-60 cell line panel. Cell Reports 2013;4(3): 609-20
32. Bollag G, Hirth P, Tsai J, et al. Clinical efficacy of a RAF inhibitor needs broad target blockade in BRAF-mutant melanoma. Nature 2010;467(7315):596-9
33. Miura K, Fujibuchi W, Unno M. Splice isoforms as therapeutic targets for colorectal cancer. Carcinogenesis 2012; 33(12):2311-19
34. Omenn GS, Menon R, Zhang Y. Innovations in proteomic profiling of cancers: alternative splice variants as a new class of cancer biomarker candidates and bridging of proteomics with structural biology. J Proteomics 2013;90:28-37 . The paper describes principles of search for alternative splicing product sites in bottom-up proteomics data and use them as candidate biomarkers.
35. Menon R, Omenn GS. Proteomic characterization of novel alternative splice variant proteins in human epidermal growth factor receptor 2/neu-induced breast cancers. Cancer Res 2010;70(9):3440-9
36. Menon R, Zhang Q, Zhang Y, et al. Identification of novel alternative splice isoforms of circulating proteins in a mouse model of human pancreatic cancer. Cancer Res 2009;69(1):300-9
37. Omenn GS, Yocum AK, Menon R. Alternative splice variants, a new class of protein cancer biomarker candidates: findings in pancreatic cancer and breast cancer with systems biology implications. Dis Markers 2010;28(4):241-51
38. Liu X, Jin Z, O'Brien R, et al. Constrained selected reaction monitoring: quantification of selected post-translational modifications and protein isoforms. Methods 2013;61(3): 304-12
39. Wu J, Pungaliya P, Kraynov E, Bates B. Identification and quantification of osteopontin splice variants in the plasma of lung cancer patients using immunoaffinity capture and targeted mass spectrometry. Biomarkers 2012;17(2):125-33
40. Madian AG, Rochelle NS, Regnier FE. Mass-linked immuno-selective assays in targeted proteomics. Anal Chem 2013; 85(2):737-48
41. Archakov A, Ivanov Y, Lisitsa A, Zgoda V. Biospecific irreversible fishing coupled with atomic force microscopy for detection of extremely low-abundant proteins. Proteomics 2009;9(5):1326-43
42. Liddy KA, White MY, Cordwell SJ. Functional decorations: post-translational modifications and heart disease delineated by targeted proteomics. Genome Med 2013; 5(2):20 . One of the first attempts of simulataneous use of the targeted proteomics such as selected reaction monitoring to quantify post-translational modification as a putative biomarker.
43. Yates JR, Kelleher NL. Top down proteomics. Anal Chem 2013;85(13):6151
44. Nedelkov D. Population proteomics: investigation of protein diversity in human populations. Proteomics 2008;8(4):779-86
45. Vaudel M, Sickmann A, Martens L. Introduction to opportunities and pitfalls in functional mass spectrometry based proteomics. Biochim Biophys Acta 2013; 1844(1 Pt A):12-20
46. Ossola R, Schiess R, Picotti P, et al. Biomarker validation in blood specimens by selected reaction monitoring mass spectrometry of N-glycosites. Methods Mol Biol 2011;728:179-94
47. Balasubramaniam D, Eissler CL, Stauffacher CV, Hall MC. Use of selected reaction monitoring data for label-free quantification of protein modification stoichiometry. Proteomics 2010;10(23): 4301-5
48. Mayor U, Peng J. Deciphering tissue-specific ubiquitylation by mass spectrometry. Methods Mol Biol 2012;832: 65-80
49. Kettenbach AN, Rush J, Gerber SA. Absolute quantification of protein and post-translational modification abundance with stable isotope-labeled synthetic peptides. Nat Protoc 2011;6(2):175-86 . A protocol to quantify post-translationally modified protein concentration by targeted proteomics with stable isotope-labeled standards.
50. Zhang P, Kirk JA, Ji W, et al. Multiple reaction monitoring to identify site-specific troponin I phosphorylated residues in the failing human heart. Circulation 2012; 126(15):1828-37
51. Agard NJ, Mahrus S, Trinidad JC, et al. Global kinetic analysis of proteolysis via quantitative targeted proteomics. Proc Natl Acad Sci USA 2012;109(6):1913-18
52. Espina V, Mueller C, Edmiston K, et al. Tissue is alive: new technologies are needed to address the problems of protein biomarker pre-analytical variability. Proteomics Clin Appl 2009;3(8):874-82
53. Rountree CB, Van Kirk CA, You H, et al. Clinical application for the preservation of phospho-proteins through in-situ tissue stabilization. Proteome Sci 2010;8:61
54. Ponomarenko EA, Lisitsa AV, Petrak J, et al. Identification of differentially expressed proteins using automatic meta-analysis of proteomics-related articles. Biomed Khim 2009;55(1):5-14
55. Gillery P, Jaisson S. Usefulness of non-enzymatic post-translational modification derived products (PTMDPs) as biomarkers of chronic diseases. J Proteomics 2013;92:228-38
56. Aebersold R, Burlingame AL, Bradshaw RA. Western blots vs. SRM assays: time to turn the tables? Mol Cell Proteomics 2013;12(9): 2381-2
57. Sherman J, Molloy MP, Burlingame AL. Why complexity and entropy matter: information, posttranslational modifications, and assay fidelity. Proteomics 2012;12(8): 1147-50
58. Domon B. Considerations on selected reaction monitoring experiments: implications for the selectivity and accuracy of measurements. Proteomics Clin Appl 2012;6(11-12):609-14
59. Biognosys AG. Available from: www. biognosys.ch