Abstract
Although advances in genomics and transcriptomics techniques have led to significant improvements in cancer, proteomics techniques have recently become very important in cancer research. Proteomics has proven to be extremely useful and popular in cancer research, providing more comprehensive information on carcinogenesis and the identification of cancer-associated protein patterns. Although the effectiveness of clinical proteomics for patient management and clinical decision-making currently appears to be low, the search for cancer-related biomarkers using proteomics has a great potential for improving risk assessment, early detection, diagnosis, prognosis, treatment selection, and surveillance. Proteomics is a collection of technologies that focuses on all forms of proteins expressed in a cell, organ, or organism as a function of time, age, situation, and external factors. It plays an important role as a bridge between genomics and biology by providing information about what actually happens in the organism. As a result, there is an increasing interest in the use of proteomics techniques in cancer research. This section provides a detailed summary of proteomics technologies and applications used in current cancer research. However, this chapter also reviews an overview of lessons learned from currently validated protein biomarkers and previous proteomics research, what the limitations and challenges are in clinical proteomics applications, and how proteomics studies can be successfully transformed into clinical practice.
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Abajian A, Murali N, Savic LJ, Laage-Gaupp FM, Nezami N, Duncan JS et al (2018) Predicting treatment response to intra-arterial therapies for hepatocellular carcinoma with the use of supervised machine learning—an artificial intelligence concept. J Vasc Interv Radiol 29(6):850–857
Aebersold R, Mann M (2003) Mass spectrometry-based proteomics. Nature 422(6928):198–207
Almendro V, Marusyk A, Polyak K (2013) Cellular heterogeneity and molecular evolution in cancer. Annu Rev Pathol Mech Dis 8:277–302
Anderson NL, Anderson NG (1998) Proteome and proteomics: new technologies, new concepts, and new words. Electrophoresis 19(11):1853–1861
Angel TE, Aryal UK, Hengel SM, Baker ES, Kelly RT, Robinson EW, Smith RD (2012) Mass spectrometry-based proteomics: existing capabilities and future directions. Chemical Society Reviews 41(10):3912–3928
Azuaje F, Kim SY, Perez Hernandez D, Dittmar G (2019) Connecting histopathology imaging and proteomics in kidney cancer through machine learning. J Clin Med 8(10):1535
Bai YH, Zhan YB, Yu B, Wang WW, Wang L, Zhou JQ et al (2018) A novel tumor-suppressor, CDH18, inhibits glioma cell invasiveness via UQCRC2 and correlates with the prognosis of glioma patients. Cell Physiol Biochem 48(4):1755–1770
Bodzon-Kulakowska A, Bierczynska-Krzysik A, Dylag T, Drabik A, Suder P, Noga M, Silberring J (2007) Methods for samples preparation in proteomic research. Journal of Chromatography B 849(1):1–31
Brünner N, Holten-Andersen M, Sweep F, Foekens J, Schmitt M, Duffy MJ (2008) New tumor biomarkers. Cancer Proteomics Humana Press, pp 189–207
Budnik B, Levy E, Harmange G, Slavov N (2018) SCoPE-MS: mass spectrometry of single mammalian cells quantifies proteome heterogeneity during cell differentiation. Genome Biol 19(1):1–12
Carter B, Zhao K (2021) The epigenetic basis of cellular heterogeneity. Nat Rev Genet 22(4):235–250
Chandran VI, Welinder C, Månsson AS, Offer S, Freyhult E, Pernemalm M et al (2019) Ultrasensitive immunoprofiling of plasma extracellular vesicles identifies syndecan-1 as a potential tool for minimally invasive diagnosis of glioma. Clin Cancer Res 25(10):3115–3127
Cho WC (2007) Contribution of oncoproteomics to cancer biomarker discovery. Mol Cancer 6(1):1–13
Choi D, Montermini L, Kim DK, Meehan B, Roth FP, Rak J (2018) The impact of oncogenic EGFRvIII on the proteome of extracellular vesicles released from glioblastoma cells. Mol Cell Proteomics 17(10):1948–1964
Clark DJ, Dhanasekaran SM, Petralia F, Pan J, Song X, Hu Y et al (2019) Integrated proteogenomic characterization of clear cell renal cell carcinoma. Cell 179(4):964–983
Clark DJ, Dhanasekaran SM, Petralia F, Pan J, Song X, Hu Y et al (2020) Integrated proteogenomic characterization of clear cell renal cell carcinoma. Cell 180(1):207
Cohen JD, Li L, Wang Y, Thoburn C, Afsari B, Danilova L et al (2018) Detection and localization of surgically resectable cancers with a multi-analyte blood test. Science 359(6378):926–930
Costa-Pinheiro P, Montezuma D, Henrique R, Jerónimo C (2015) Diagnostic and prognostic epigenetic biomarkers in cancer. Epigenomics 7(6):1003–1015
Cree IA, Uttley L, Woods HB, Kikuchi H, Reiman A, Harnan S et al (2017) The evidence base for circulating tumour DNA blood-based biomarkers for the early detection of cancer: a systematic mapping review. BMC Cancer 17(1):1–17
D’Amore B, Smolinski-Zhao S, Daye D, Uppot RN (2021) Role of machine learning and artificial intelligence in interventional oncology. Curr Oncol Rep 23(6):1–8
Daoud SS (ed) (2007) Cancer proteomics: from bench to bedside
Deracinois B, Flahaut C, Duban-Deweer S, Karamanos Y (2013) Comparative and quantitative global proteomics approaches: an overview. Proteomes 1(3):180–218
Diamandis EP (2002) Tumor markers: past, present, and future. In: Diamandis EP, Fritsche H Jr, Lilja H, Chan D, Schwartz M (eds) Tumor markers: physiology, pathobiology, technology, and clinical applications. American Association for Clinical Chemistry (AACC) Press, Washington, DC, pp 3–8
Doll S, Gnad F, Mann M (2019) The case for proteomics and phospho-proteomics in personalized cancer medicine. Proteom Clin Appl 13(2):1800113
Donnelly N, Storchová Z (2014) Dynamic karyotype, dynamic proteome: buffering the effects of aneuploidy. Biochimica et Biophysica Acta (BBA)-Mol Cell Res 1843(2):473–481
Dou Y, Kawaler EA, Zhou DC, Gritsenko MA, Huang C, Blumenberg L et al (2020) Proteogenomic characterization of endometrial carcinoma. Cell 180(4):729–748
Duffy MJ (2005) Predictive markers in breast and other cancers: a review. Clin Chem 51(3):494–503
Duffy MJ (2020) Biomarkers for prostate cancer: prostate-specific antigen and beyond. Clin Chem Lab Med (CCLM) 58(3):326–339
Duffy MJ, McGowan PM, Harbeck N, Thomssen C, Schmitt M (2014) uPA and PAI-1 as biomarkers in breast cancer: validated for clinical use in level-of-evidence-1 studies. Breast Cancer Res 16(4):1–10
Eckert MA, Coscia F, Chryplewicz A, Chang JW, Hernandez KM, Pan S et al (2019) Proteomics reveals NNMT as a master metabolic regulator of cancer-associated fibroblasts. Nature 569(7758):723–728
Edwards NJ, Oberti M, Thangudu RR, Cai S, McGarvey PB, Jacob S et al (2015) The CPTAC data portal: a resource for cancer proteomics research. J Proteome Res 14(6):2707–2713
Fenn JB, Mann M, Meng CK, Wong SF, Whitehouse CM (1989) Electrospray ionization for mass spectrometry of large biomolecules. Science 246(4926):64–71
Gao Q, Zhu H, Dong L, Shi W, Chen R, Song Z et al (2019) Integrated proteogenomic characterization of HBV-related hepatocellular carcinoma. Cell 179(2):561–577
Gezici S (2017) Proteomics techniques and their applications in cancer research. Türk Bilimsel Derlemeler Dergisi 10(2):54–61
Gezici S, Ozaslan M, Akpinar G, Kasap M, Sanli M, Elbeyli L (2017) Comparative proteomics and bioinformatics analysis of tissue from non-Small cell lung cancer patients. Curr Proteom 14(1):58–77
Gonçalves E, Fragoulis A, Garcia-Alonso L, Cramer T, Saez-Rodriguez J, Beltrao P (2017) Widespread post-transcriptional attenuation of genomic copy-number variation in cancer. Cell Syst 5(4):386–398
Groth SFDS, Webster RG, Datyner A (1963) Two new staining procedures for quantitative estimation of proteins on electrophoretic strips. Biochimica et Biophysica Acta 71:377–391
Gupta MK, Polisetty RV, Sharma R, Ganesh RA, Gowda H, Purohit AK et al (2019) Altered transcriptional regulatory proteins in glioblastoma and YBX1 as a potential regulator of tumor invasion. Sci Rep 9(1):1–15
Hallal S, Russell BP, Wei H, Lee MYT, Toon CW, Sy J et al (2019) Extracellular vesicles from neurosurgical aspirates identifies chaperonin containing TCP1 subunit 6A as a potential glioblastoma biomarker with prognostic significance. Proteomics 19(1–2):1800157
Han C, Lu X, Nagrath D (2018) Regulation of protein metabolism in cancer. Mol Cell Oncol 5(5):e1285384
Hanahan D (2022) Hallmarks of cancer: new dimensions. Cancer Discov 12(1):31–46
Hanahan D, Weinberg RA (2000) The hallmarks of cancer. cell 100(1):57–70
Hao P, Guo T, Li X, Adav SS, Yang J, Wei M, Sze SK (2010) Novel application of electrostatic repulsion-hydrophilic interaction chromatography (ERLIC) in shotgun proteomics: comprehensive profiling of rat kidney proteome. Journal of Proteome Research 9(7):3520–3526
Hardcastle JD, Chamberlain JO, Robinson MH, Moss SM, Amar SS, Balfour TW et al (1996) Randomised controlled trial of faecal-occult-blood screening for colorectal cancer. Lancet 348(9040):1472–1477
Hayes DF, Bast RC, Desch CE, Fritsche H Jr, Kemeny NE, Jessup JM et al (1996) Tumor marker utility grading system: a framework to evaluate clinical utility of tumor markers. JNCI J Natl Cancer Inst 88(20):1456–1466
Henry NL, Hayes DF (2012) Cancer biomarkers. Mol Oncol 6(2):140–146
Holten-Andersen MN, Stephens RW, Nielsen HJ, Murphy G, Christensen IJ, Stetler-Stevenson W, Brünner N (2000) High preoperative plasma tissue inhibitor of metalloproteinase-1 levels are associated with short survival of patients with colorectal cancer. Clin Cancer Res 6(11):4292–4299
Honda K, Ono M, Shitashige M, Masuda M, Kamita M, Miura N, Yamada T (2013) Proteomic approaches to the discovery of cancer biomarkers for early detection and personalized medicine. Jpn J Clin Oncol 43(2):103–109
Huang S, Yang J, Fong S, Zhao Q (2020) Artificial intelligence in cancer diagnosis and prognosis: opportunities and challenges. Cancer Lett 471:61–71
Huss R (2015) Biomarkers. In: Translational regenerative medicine. Academic, pp 235–241
Iqbal MJ, Javed Z, Sadia H, Qureshi IA, Irshad A, Ahmed R et al (2021) Clinical applications of artificial intelligence and machine learning in cancer diagnosis: looking into the future. Cancer Cell Int 21(1):1–11
Jain KK (2008a) Innovations, challenges and future prospects of oncoproteomics. Mol Oncol 2(2):153–160
Jain KK (2008b) Oncoproteomics for personalized management of cancer. In: Cancer proteomics. Humana Press, pp 81–99
Jänicke F, Prechtl A, Thomssen C, Harbeck N, Meisner C, Untch M et al (2001) Randomized adjuvant chemotherapy trial in high-risk, lymph node-negative breast cancer patients identified by urokinase-type plasminogen activator and plasminogen activator inhibitor type 1. J Natl Cancer Inst 93(12):913–920
Jeon S, Kim DW, Lee DB, Cho JY (2020) NEDD4 plays roles in the maintenance of breast cancer stem cell characteristics. Front Oncol:1680
Jiang CY, Niu Z, Green MD, Zhao L, Raupp S, Pannecouk B et al (2021) It’s not ‘just a tube of blood’: principles of protocol development, sample collection, staffing and budget considerations for blood-based biomarkers in immunotherapy studies. J Immunother Cancer 9(7)
Joshi S, Tiwari AK, Mondal B, Sharma A (2011) Oncoproteomics. Clin Chim Acta 412(3–4):217–226
Kang UB (2021) Proteomic interrogation in cancer biomarker. In: Translational research in breast cancer. Springer, Singapore, pp 305–322
Kang J, Brajanovski N, Chan KT, Xuan J, Pearson RB, Sanij E (2021) Ribosomal proteins and human diseases: molecular mechanisms and targeted therapy. Signal Transduction and Targeted Therapy 6(1):323
Kellogg RA, Dunn J, Snyder MP (2018) Personal omics for precision health. Circ Res 122(9):1169–1171
Kelly RT (2020) Single-cell proteomics: progress and prospects. Mol Cell Proteomics 19(11):1739–1748
Khadir A, Tiss A (2013) Proteomics approaches towards early detection and diagnosis of cancer. J Carcinogene Mutagene S14
Kim M, Tagkopoulos I (2018) Data integration and predictive modeling methods for multi-omics datasets. Mol Omics 14(1):8–25
Kočevar N, Hudler P, Komel R (2013) The progress of proteomic approaches in searching for cancer biomarkers. New Biotechnol 30(3):319–326
Koh EY, You JE, Jung SH, Kim PH (2020) Biological functions and identification of novel biomarker expressed on the surface of breast cancer-derived cancer stem cells via proteomic analysis. Mol Cells 43(4):384
Kottakis F, Nicolay BN, Roumane A, Karnik R, Gu H, Nagle JM et al (2016) LKB1 loss links serine metabolism to DNA methylation and tumorigenesis. Nature 539(7629):390–395
Krug K, Mertins P, Zhang B, Hornbeck P, Raju R, Ahmad R et al (2019) A curated resource for Phosphosite-specific signature analysis*[S]. Mol Cell Proteomics 18(3):576–593
Kumar A, Kennecke HF, Renouf DJ, Lim HJ, Gill S, Woods R et al (2015) Adjuvant chemotherapy use and outcomes of patients with high-risk versus low-risk stage II colon cancer. Cancer 121(4):527–534
Kustatscher G, Grabowski P, Rappsilber J (2017) Pervasive coexpression of spatially proximal genes is buffered at the protein level. Mol Syst Biol 13(8):937
Kwon Y, Kim M, Kim Y, Jung HS, Jeoung D (2020) Exosomal microRNAs as mediators of cellular interactions between cancer cells and macrophages. Frontiers in immunology 11:1167
Kwon YW, Jo HS, Bae S, Seo Y, Song P, Song M, Yoon JH (2021) Application of proteomics in cancer: recent trends and approaches for biomarkers discovery. Front Med 8
Labib M, Kelley SO (2020) Single-cell analysis targeting the proteome. Nat Rev Chem 4(3):143–158
Le Large TYS, El Hassouni B, Funel N, Kok B, Piersma SR, Pham TV et al (2019) Proteomic analysis of gemcitabine-resistant pancreatic cancer cells reveals that microtubule-associated protein 2 upregulation associates with taxane treatment. Therap Adv Med Oncol 11:1758835919841233
Leone RD, Powell JD (2020) Metabolism of immune cells in cancer. Nat Rev Cancer 20(9):516–531
Levy E, Slavov N (2018) Single cell protein analysis for systems biology. Essays Biochem 62(4):595–605
Lignitto L, LeBoeuf SE, Homer H, Jiang S, Askenazi M, Karakousi TR et al (2019) Nrf2 activation promotes lung cancer metastasis by inhibiting the degradation of Bach1. Cell 178(2):316–329
Lin JC, Liu TP, Andriani V, Athoillah M, Wang CY, Yang PM (2021) Bioinformatics analysis identifies precision treatment with paclitaxel for hepatocellular carcinoma patients harboring mutant tp53 or wild-type ctnnb1 gene. J Personal Medi 11(11):1199
Liu Y, Beyer A, Aebersold R (2016) On the dependency of cellular protein levels on mRNA abundance. Cell 165(3):535–550
Londhe VY, Bhasin B (2019) Artificial intelligence and its potential in oncology. Drug Discov Today 24(1):228–232
Madeddu C, Maccio A, Mantovani G (2011) Metabolic changes in cancer patients. Anti-Inflammatory & Anti-Allergy Agents in Medicinal Chemistry (Formerly Current Medicinal Chemistry-Anti-Inflammatory and Anti-Allergy Agents) 10(4):281–285
Maes E, Mertens I, Valkenborg D, Pauwels P, Rolfo C, Baggerman G (2015) Proteomics in cancer research: are we ready for clinical practice? Crit Rev Oncol Hematol 96(3):437–448
Mandrekar SJ, Sargent DJ (2009) Clinical trial designs for predictive biomarker validation: theoretical considerations and practical challenges. J Clin Oncol 27(24):4027
Maruvada P, Wang W, Wagner PD, Srivastava S (2005) Biomarkers in molecular medicine: cancer detection and diagnosis. BioTechniques 38(S4):S9–S15
Maryáš J, Faktor J, Dvořáková M, Struhárová I, Grell P, Bouchal P (2014) Proteomics in investigation of cancer metastasis: functional and clinical consequences and methodological challenges. Proteomics 14(4–5):426–440
Merril CR, Switzer RC, Van Keuren ML (1979) Trace polypeptides in cellular extracts and human body fluids detected by two-dimensional electrophoresis and a highly sensitive silver stain. Proceedings of the National Academy of Sciences 76(9):4335–4339
Minden JS, Dowd SR, Meyer HE, Stühler K (2009) Difference gel electrophoresis. Electrophoresis 30(S1):S156–S161
Miyauchi E, Furuta T, Ohtsuki S, Tachikawa M, Uchida Y, Sabit H et al (2018) Identification of blood biomarkers in glioblastoma by SWATH mass spectrometry and quantitative targeted absolute proteomics. PLoS One 13(3):e0193799
Mun DG, Bhin J, Kim S, Kim H, Jung JH, Jung Y et al (2019) Proteogenomic characterization of human early-onset gastric cancer. Cancer Cell 35(1):111–124
Myers SA, Rhoads A, Cocco AR, Peckner R, Haber AL, Schweitzer LD et al (2019) Streamlined protocol for deep proteomic profiling of FAC-sorted cells and its application to freshly isolated murine immune cells. Mol Cell Proteomics 18(5):995–1009
Ni Y, Zhang F, An M, Yin W, Gao Y (2018) Early candidate biomarkers found from urine of glioblastoma multiforme rat before changes in MRI. Sci China Life Sci 61:1–6
Nicolini A, Ferrari P, Masoni MC, Fini M, Pagani S, Giampietro O, Carpi A (2013) Malnutrition, anorexia and cachexia in cancer patients: a mini-review on pathogenesis and treatment. Biomed Pharmacother 67(8):807–817
Nusinow DP, Szpyt J, Ghandi M, Rose CM, McDonald ER III, Kalocsay M et al (2020) Quantitative proteomics of the cancer cell line encyclopedia. Cell 180(2):387–402
Obradović M, Hamelin B, Manevski N, Couto JP, Sethi A, Coissieux MM et al (2019) Glucocorticoids promote breast cancer metastasis. Nature 567(7749):540–544
Okawa S, Gagrica S, Blin C, Ender C, Pollard SM, Krijgsveld J (2017) Proteome and secretome characterization of glioblastoma-derived neural stem cells. Stem Cells 35(4):967–980
Oldenhuis CNAM, Oosting SF, Gietema JA, De Vries EGE (2008) Prognostic versus predictive value of biomarkers in oncology. Eur J Cancer 44(7):946–953
Pastwa E, Somiari SB, Czyz M, Somiari RI (2007) Proteomics in human cancer research. Proteomics Clin Appl 1(1):4–17
Patel PS, Telang SD, Rawal RM, Shah MH (2005) A review of proteomics in cancer research. Asian Pac J Cancer Prev 6(2):113–117
Peng J, Elias JE, Thoreen CC, Licklider LJ, Gygi SP (2003) Evaluation of multidimensional chromatography coupled with tandem mass spectrometry (LC/LC-MS/MS) for large-scale protein analysis: the yeast proteome. Journal of Proteome Research 2(1):43–50
Rabilloud T, Lelong C (2011) Two-dimensional gel electrophoresis in proteomics: a tutorial. Journal of Proteomics 74(10):1829–1841
Raffel S, Klimmeck D, Falcone M, Demir A, Pouya A, Zeisberger P et al (2020) Quantitative proteomics reveals specific metabolic features of acute myeloid leukemia stem cells. Blood 136(13):1507–1519
Rassy E, Assi T, Pavlidis N (2020) Exploring the biological hallmarks of cancer of unknown primary: where do we stand today?. British journal of cancer 122(8):1124–1132
Raynie DE (2010) Modern extraction techniques. Analytical Chemistry 82(12):4911–4916
Riederer BM (2008) Non-covalent and covalent protein labeling in two-dimensional gel electrophoresis. Journal of Proteomics 71(2):231–244
Ruhen O, Meehan K (2019) Tumor-derived extracellular vesicles as a novel source of protein biomarkers for cancer diagnosis and monitoring. Proteomics 19(1–2):1800155
Rusling JF, Kumar CV, Gutkind JS, Patel V (2010) Measurement of biomarker proteins for point-of-care early detection and monitoring of cancer. Analyst 135(10):2496–2511
Sallam RM (2015) Proteomics in cancer biomarkers discovery: challenges and applications. Dis Markers 2015:1–12
Santos A, Colaço AR, Nielsen AB, Niu L, Strauss M, Geyer PE et al (2022) A knowledge graph to interpret clinical proteomics data. Nat Biotechnol 40:1–11
Selby JV, Friedman GD, Quesenberry CP Jr, Weiss NS (1992) A case–control study of screening sigmoidoscopy and mortality from colorectal cancer. N Engl J Med 326(10):653–657
Shen J, Qi L, Zou Z, Du J, Kong W, Zhao L et al (2020) Identification of a novel gene signature for the prediction of recurrence in HCC patients by machine learning of genome-wide databases. Sci Rep 10(1):1–9
Shenoy A, Belugali Nataraj N, Perry G, Loayza Puch F, Nagel R, Marin I et al (2020) Proteomic patterns associated with response to breast cancer neoadjuvant treatment. Mol Syst Biol 16(9):e9443
Siegel RL, Miller KD, Goding Sauer A, Fedewa SA, Butterly LF, Anderson JC, ... & Jemal A (2020) Colorectal cancer statistics, 2020. CA: a cancer journal for clinicians, 70(3):145–164
Sinha A, Huang V, Livingstone J, Wang J, Fox NS, Kurganovs N et al (2019) The proteogenomic landscape of curable prostate cancer. Cancer Cell 35(3):414–427
Small EJ, Roach M III (2002) Prostate-specific antigen in prostate cancer: a case study in the development of a tumor marker to monitor recurrence and assess response. Seminars in oncology 29(3):264–273. WB Saunders
Srinivas PR, Srivastava S, Hanash S, Wright GL Jr (2001) Proteomics in early detection of cancer. Clin Chem 47(10):1901–1911
Srinivas PR, Verma M, Zhao Y, Srivastava S (2002) Proteomics for cancer biomarker discovery. Clin Chem 48(8):1160–1169
Srivastava A, Creek DJ (2019) Discovery and validation of clinical biomarkers of cancer: a review combining metabolomics and proteomics. Proteomics 19(10):1700448
Suzuki H, Asakawa A, Amitani H, Fujitsuka N, Nakamura N, Inui A (2013) Cancer cachexia pathophysiology and translational aspect of herbal medicine. Jpn J Clin Oncol 43(7):695–705
Tan HT, Lee YH, Chung MC (2012) Cancer proteomics. Mass Spectrom Rev 31(5):583–605
Tătaru OS, Vartolomei MD, Rassweiler JJ, Virgil O, Lucarelli G, Porpiglia F et al (2021) Artificial intelligence and machine learning in prostate cancer patient management—current trends and future perspectives. Diagnostics 11(2):354
Vasaikar S, Huang C, Wang X, Petyuk VA, Savage SR, Wen B et al (2019) Proteogenomic analysis of human colon cancer reveals new therapeutic opportunities. Cell 177(4):1035–1049
Walther TC, Mann M (2010) Mass spectrometry–based proteomics in cell biology. The Journal of Cell Biology 190(4):491–500
Wang D, Bodovitz S (2010) Single cell analysis: the new frontier in ‘omics’. Trends Biotechnol 28(6):281–290
Wei Z, Liu X, Cheng C, Yu W, Yi P (2021) Metabolism of amino acids in cancer. Front Cell Develop Biol 1628
Wu C, Zhou F, Ren J, Li X, Jiang Y, Ma S (2019) A selective review of multi-level omics data integration using variable selection. High-Throughput 8(1):4
Xie F, Liu T, Qian WJ, Petyuk VA, Smith RD (2011) Liquid chromatography-mass spectrometry-based quantitative proteomics. Journal of Biological Chemistry 286(29):25443–25449
Yamashita M, Fenn JB (1984) Electrospray ion source. Another variation on the free-jet theme. The Journal of Physical Chemistry 88(20):4451–4459
Yi L, Tsai CF, Dirice E, Swensen AC, Chen J, Shi T et al (2019) Boosting to amplify signal with isobaric labeling (BASIL) strategy for comprehensive quantitative phosphoproteomic characterization of small populations of cells. Anal Chem 91(9):5794–5801
Zhang Z (2012) An in vitro diagnostic multivariate index assay (IVDMIA) for ovarian cancer: harvesting the power of multiple biomarkers. Rev Obstet Gynecol 5(1):35
Zhang J, Baran J, Cros A, Guberman JM, Haider S, Hsu J et al (2011) International Cancer Genome Consortium Data Portal—a one-stop shop for cancer genomics data. Database
Zhang J, Bajari R, Andric D, Gerthoffert F, Lepsa A, Nahal-Bose H et al (2019) The international cancer genome consortium data portal. Nat Biotechnol 37(4):367–369
Zhou S, Bailey MJ, Dunn MJ, Preedy VR, Emery PW (2005) A quantitative investigation into the losses of proteins at different stages of a two‐dimensional gel electrophoresis procedure. Proteomics 5(11):2739–2747
Zhou L, Li Q, Wang J, Huang C, Nice EC (2016) Oncoproteomics: trials and tribulations. Proteomics Clin Appl 10(4):516–515
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Gezici, S. (2023). Proteomics and Protein Biomarkers in Cancer Metastasis. In: Rezaei, N. (eds) Handbook of Cancer and Immunology. Springer, Cham. https://doi.org/10.1007/978-3-030-80962-1_150-1
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