The role of proteomics in the modern diagnosis of cervical cancer
- Authors: Hamadyanova A.U.1, Sultanmuratova A.S.1, Disbiyanova A.K.1, Akhmadeyeva S.N.1, Yadgarov N.O.1, Burangulova L.E.1
-
Affiliations:
- Bashkir State Medical University
- Issue: Vol 71, No 2 (2022)
- Pages: 113-122
- Section: Reviews
- URL: https://journals.rcsi.science/jowd/article/view/83961
- DOI: https://doi.org/10.17816/JOWD83961
- ID: 83961
Cite item
Abstract
Cervical cancer is a leading global health problem and the second most common form of cancer in women living in developing countries. Despite the available methods of diagnosis and treatment, cervical cancer is still the cause of a large number of deaths among vulnerable groups of the female population, which makes further research relevant. The aim of this study was to summarize new technological developments and scientific information about proteomics, which will allow for deepening the understanding of the pathogenesis of cervical cancer and developing new methods of diagnosis and treatment of this pathology. Recent achievements in the field of analytical research methods and bioinformatics provide a wide range of alternatives in the field of proteomic research. To date, proteomic analysis can be performed on almost any biological sample (tumor tissue, blood, urine, saliva, vaginal secretions). Each type of biological sample represents a potential source of diagnostic and prognostic biomarkers, as well as potential targets for therapy. The main limitation of proteomic studies aimed at finding potential biomarkers of the disease is the high variability of the results depending on the specific laboratory. There is variability in concentrations and even in the type of biomarker identified, even though research teams are working with the same samples.
Keywords
Full Text
##article.viewOnOriginalSite##About the authors
Aida U. Hamadyanova
Bashkir State Medical University
Author for correspondence.
Email: sagidullin12@bk.ru
ORCID iD: 0000-0001-6197-195X
Cand. Sci. (Med.), Assistant Professor
Russian Federation, UfaAzalia S. Sultanmuratova
Bashkir State Medical University
Email: azalka.sultanmuratova@mail.ru
ORCID iD: 0000-0003-1497-8475
Russian Federation, Ufa
Aliya Kh. Disbiyanova
Bashkir State Medical University
Email: aliyadis@yandex.ru
ORCID iD: 0000-0002-1044-2190
Russian Federation, Ufa
Svetlana N. Akhmadeyeva
Bashkir State Medical University
Email: akhmadeva98@bk.ru
ORCID iD: 0000-0003-2363-7680
Russian Federation, Ufa
Nikita O. Yadgarov
Bashkir State Medical University
Email: stemm1001@gmail.com
ORCID iD: 0000-0002-4229-4313
Russian Federation, Ufa
Liana E. Burangulova
Bashkir State Medical University
Email: liandoklianchuk@gmail.com
ORCID iD: 0000-0002-2357-781X
Russian Federation, Ufa
References
- Zhukova AB. Squamous intraepithelial lesions of the cervix: a modern view of etiology, pathogenesis, and diagnosis. Journal of obstetrics and women’s diseases. 2019;68(6):87–98. (In Russ.). doi: 10.17816/JOWD68687-98
- Pestrikova TY, Ismaylova AF, Kiselev SN. Cervical cancer: monitoring of the main indicators characterizing this pathology in Khabarovsk Krai (2009–2019). Gynecology. 2021;23(2):155–160. (In Russ.). doi: 10.26442/20795696.2021.2.200775
- 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(3):209–249. doi: 10.3322/caac.21660
- Hu Z, Ma D. The precision prevention and therapy of HPV-related cervical cancer: new concepts and clinical implications. Cancer Med. 2018;7(10):5217–5236. doi: 10.1002/cam4.1501
- Wang D, Eraslan B, Wieland T, et al. A deep proteome and transcriptome abundance atlas of 29 healthy human tissues. Mol Syst Biol. 2019;15(2):e8503. doi: 10.15252/msb.20188503
- Rao VS, Srinivas K, Sujini GN, Kumar GN. Protein-protein interaction detection: methods and analysis. Int J Proteomics. 2014;2014:147648. doi: 10.1155/2014/147648
- Droit A, Poirier GG, Hunter JM. Experimental and bioinformatic approaches for interrogating protein-protein interactions to determine protein function. J Mol Endocrinol. 2005;34(2):263–280. doi: 10.1677/jme.1.01693
- Pascovici D, Wu JX, McKay MJ, et al. Clinically relevant post-translational modification analyses-maturing workflows and bioinformatics tools. Int J Mol Sci. 2018;20(1):16. doi: 10.3390/ijms20010016
- O’Farrell PH. High resolution two-dimensional electrophoresis of proteins. J Biol Chem. 1975;250(10):4007–4021.
- Folch J, Lees M, Sloane Stanley GH. A simple method for the isolation and purification of total lipides from animal tissues. J Biol Chem. 1957;226(1):497–509.
- Chen C, Hou J, Tanner JJ, Cheng J. Bioinformatics methods for mass spectrometry-based proteomics data analysis. Int J Mol Sci. 2020;21(8):2873. doi: 10.3390/ijms21082873
- Perkins RC. Making the case for functional proteomics. Methods Mol Biol. 2019;1871:1–40. doi: 10.1007/978-1-4939-8814-3_1
- Shin J, Lee W, Lee W. Structural proteomics by NMR spectroscopy. Expert Rev Proteomics. 2008;5(4):589–601. doi: 10.1586/14789450.5.4.589
- Boersema PJ, Kahraman A, Picotti P. Proteomics beyond large-scale protein expression analysis. Curr Opin Biotechnol. 2015;34:162–170. doi: 10.1016/j.copbio.2015.01.005
- Banach P, Suchy W, Dereziński P, et al. Mass spectrometry as a tool for biomarkers searching in gynecological oncology. Biomed Pharmacother. 2017;92:836–842. doi: 10.1016/j.biopha.2017.05.146
- Al-Wajeeh AS, Salhimi SM, Al-Mansoub MA, et al. Comparative proteomic analysis of different stages of breast cancer tissues using ultra high performance liquid chromatography tandem mass spectrometer. PLoS One. 2020;15(1):e0227404. doi: 10.1371/journal.pone.0227404
- Aslam B, Basit M, Nisar MA, et al. Proteomics: Technologies and their applications. J Chromatogr Sci. 2017;55(2):182–196. doi: 10.1093/chromsci/bmw167
- Boylan KLM, Afiuni-Zadeh S, Geller MA, et al. Evaluation of the potential of Pap test fluid and cervical swabs to serve as clinical diagnostic biospecimens for the detection of ovarian cancer by mass spectrometry-based proteomics. Clin Proteomics. 2021;18(1):4. doi: 10.1186/s12014-020-09309-3
- Chen G, Chen J, Liu H, et al. Comprehensive identification and characterization of human secretome based on integrative proteomic and transcriptomic data. Front Cell Dev Biol. 2019;7:299. doi: 10.3389/fcell.2019.00299
- Montaner J, Ramiro L, Simats A, et al. Multilevel omics for the discovery of biomarkers and therapeutic targets for stroke. Nat Rev Neurol. 2020;16(5):247–264. doi: 10.1038/s41582-020-0350-6
- Huang Z, Ma L, Huang C, et al. Proteomic profiling of human plasma for cancer biomarker discovery. Proteomics. 2017;17(6). doi: 10.1002/pmic.201600240
- Ren AH, Fiala CA, Diamandis EP, Kulasingam V. Pitfalls in cancer biomarker discovery and validation with emphasis on circulating tumor DNA. Cancer Epidemiol Biomarkers Prev. 2020;29(12):2568–2574. doi: 10.1158/1055-9965.EPI-20-0074
- Sobsey CA, Ibrahim S, Richard VR, et al. Targeted and untargeted proteomics approaches in biomarker development. Proteomics. 2020;20(9):e1900029. doi: 10.1002/pmic.201900029
- Higareda-Almaraz JC, Enríquez-Gasca Mdel R, Hernández-Ortiz M, et al. Proteomic patterns of cervical cancer cell lines, a network perspective. BMC Syst Biol. 2011;5:96. doi: 10.1186/1752-0509-5-96
- Pappa KI, Christou P, Xholi A, et al. Membrane proteomics of cervical cancer cell lines reveal insights on the process of cervical carcinogenesis. Int J Oncol. 2018;53(5):2111–2122. doi: 10.3892/ijo.2018.4518
- Xia C, Yang F, He Z, Cai Y. iTRAQ-based quantitative proteomic analysis of the inhibition of cervical cancer cell invasion and migration by metformin. Biomed Pharmacother. 2020;123:109762. doi: 10.1016/j.biopha.2019.109762
- Muñoz N, Bosch FX, de Sanjosé S, et al.; International Agency for Research on Cancer Multicenter Cervical Cancer Study Group. Epidemiologic classification of human papillomavirus types associated with cervical cancer. N Engl J Med. 2003;348(6):518–527. doi: 10.1056/NEJMoa021641
- Yang J, Chen L, Kong X, et al. Analysis of tumor suppressor genes based on gene ontology and the KEGG pathway. PLoS One. 2014;9(9):e107202. doi: 10.1371/journal.pone.0107202
- Su PH, Lin YW, Huang RL, et al. Epigenetic silencing of PTPRR activates MAPK signaling, promotes metastasis and serves as a biomarker of invasive cervical cancer. Oncogene. 2013;32(1):15–26. doi: 10.1038/onc.2012.29
- Ma Z, Chen J, Luan T, et al. Proteomic analysis of human cervical adenocarcinoma mucus to identify potential protein biomarkers. PeerJ. 2020;8:e9527. doi: 10.7717/peerj.9527
- Bae SM, Min HJ, Ding GH, et al. Protein expression profile using two-dimensional gel analysis in squamous cervical cancer patients. Cancer Res Treat. 2006;38(2):99–107. doi: 10.4143/crt.2006.38.2.99
- Gu Y, Wu SL, Meyer JL, et al. Proteomic analysis of high-grade dysplastic cervical cells obtained from ThinPrep slides using laser capture microdissection and mass spectrometry. J Proteome Res. 2007;6(11):4256–4268. doi: 10.1021/pr070319j
- Zhu X, Lv J, Yu L, et al. Proteomic identification of differentially-expressed proteins in squamous cervical cancer. Gynecol Oncol. 2009;112(1):248–256. doi: 10.1016/j.ygyno.2008.09.045
- Zhao Q, He Y, Wang XL, et al. Differentially expressed proteins among normal cervix, cervical intraepithelial neoplasia and cervical squamous cell carcinoma. Clin Transl Oncol. 2015;17(8):620–631. doi: 10.1007/s12094-015-1287-x
- Serafín-Higuera I, Garibay-Cerdenares OL, Illades-Aguiar B, et al. Differential proteins among normal cervix cells and cervical cancer cells with HPV-16 infection, through mass spectrometry-based Proteomics (2D-DIGE) in women from Southern México. Proteome Sci. 2016;14(1):10. doi: 10.1186/s12953-016-0099-4
- Jin Y, Kim SC, Kim HJ, et al. Use of protein-based biomarkers of exfoliated cervical cells for primary screening of cervical cancer. Arch Pharm Res. 2018;41(4):438–449. doi: 10.1007/s12272-018-1015-5
- Güzel C, Govorukhina NI, Wisman GBA, et al. Proteomic alterations in early stage cervical cancer. Oncotarget. 2018;9(26):18128–18147. doi: 10.18632/oncotarget.24773
- Hwang YJ, Lee SP, Kim SY, et al. Expression of heat shock protein 60 kDa is upregulated in cervical cancer. Yonsei Med J. 2009;50(3):399–406. doi: 10.3349/ymj.2009.50.3.399
- Choi CH, Chung JY, Kang JH, et al. Chemoradiotherapy response prediction model by proteomic expressional profiling in patients with locally advanced cervical cancer. Gynecol Oncol. 2020;157(2):437–443. doi: 10.1016/j.ygyno.2020.02.017
- Martínez-Rodríguez F, Limones-González JE, Mendoza-Almanza B, et al. Understanding cervical cancer through proteomics. Cells. 2021;10(8):1854. doi: 10.3390/cells10081854
- Boichenko AP, Govorukhina N, Klip HG, et al. A panel of regulated proteins in serum from patients with cervical intraepithelial neoplasia and cervical cancer. J Proteome Res. 2014;13(11):4995–5007. doi: 10.1021/pr500601w
- Guo X, Hao Y, Kamilijiang M, et al. Potential predictive plasma biomarkers for cervical cancer by 2D-DIGE proteomics and Ingenuity Pathway Analysis. Tumour Biol. 2015;36(3):1711–1720. doi: 10.1007/s13277-014-2772-5