Biomarkers are the foundation of cancer detection and monitoring. Most of today's licensed tests for disease detection are protein-based assays.
Low-throughput proteomics approaches, such as 2D-PAGE (two-dimensional polyacrylamide gel electrophoresis) coupled with mass spectrometry for protein identification, have proven useful for cancer biomarker discovery, particularly when laser capture microdissection (LCM) is used to isolate cell populations of interest for analysis.
Technologies such as multidimensional separation systems directly coupled to mass spectrometry analysis represent improvements in sensitivity and throughput when compared with traditional 2D-PAGE analysis for biomarker discovery.
Mass-spectrometry-driven proteomic analysis is a key development for the rapid detection of cancer-specific biomarkers and proteomic patterns of tissue and body fluids.
Proteomic pattern diagnostics combines proteomic pattern profiling of tissue and body fluids by mass spectrometry with sophisticated bioinformatics tools to identify patterns within the complex proteomic profile that discriminate between normal, benign or disease states.
Proteomic pattern diagnostics has been successfully applied to the problems of early detection for a number of different types of cancer.
A number of feasibility, reproducibility and standardization issues need to be addressed before proteomic pattern diagnostics can be incorporated into routine clinical practice.
Mass spectrometry might become the preferred detection platform and clinical analyser for routine clinical and medical diagnostics.
The ability of physicians to effectively treat and cure cancer is directly dependent on their ability to detect cancers at their earliest stages. Proteomic analyses of early-stage cancers have provided new insights into the changes that occur in the early phases of tumorigenesis and represent a new resource of candidate biomarkers for early-stage disease. Studies that profile proteomic patterns in body fluids also present new opportunities for the development of novel, highly sensitive diagnostic tools for the early detection of cancer.
Subscribe to Journal
Get full journal access for 1 year
only $22.08 per issue
All prices are NET prices.
VAT will be added later in the checkout.
Rent or Buy article
Get time limited or full article access on ReadCube.
All prices are NET prices.
Srinivas, P. R., Kramer, B. S. & Srivastava, S. Trends in biomarker research for cancer detection. Lancet Oncol. 2, 698–704 (2001).
Sidransky, D. Emerging molecular markers of cancer. Nature Rev. Cancer 2, 210–219 (2002).
Kiviat, N. B. & Critchlow, C. W. Novel approaches to identification of biomarkers for detection of early stage cancer. Dis. Markers 18, 73–81 (2002).
Adam, B.-L., Vlahou, A., Semmes, O. J. & Wright, G. L. Jr. Proteomic approaches to biomarker discovery in prostate and bladder cancers. Proteomics 1, 1264–1270 (2001).
Carter, D. et al. Purification and characterization of the mammaglobin/lipophilin B complex, a promising diagnostic marker for breast cancer. Biochemistry 41, 6714–6722 (2002).
Rosty, C. et al. Identification of hepatocarcinoma-intestine-pancreas/pancreatitis-associated protein I as a biomarker for pancreatic ductal adenocarcinoma by protein biochip technology. Cancer Res. 62, 1868–1875 (2002).
Xiao, Z. et al. Quantitation of serum prostate-specific membrane antigen by a novel protein biochip immunoassay discriminates benign from malignant prostate disease. Cancer Res. 61, 6029–6033 (2001).
Kim, J.-H. et al. Osteopontin as a potential diagnostic biomarker for ovarian cancer. JAMA 287, 1671–1679 (2002).
Gorg, A. et al. The current state of two-dimensional electrophoresis with immobilized pH gradients. Electrophoresis 21, 1037–1053 (2000).
Hanash, S. M. Biomedical applications of two-dimensional electrophoresis using immobilized pH gradients: current status. Electrophoresis 21, 1202–1209 (2000).
Soldes, O. et al. Differential expression of Hsp27 in normal oesophagus, Barrett's metaplasia and oesophageal adenocarcinomas. Br. J. Cancer 79, 595–603 (1999).
Seow, T. K., Liang, R. C., Leow, C. K. & Chung, M. C. Hepatocellular carcinoma: from bedside to proteomics. Proteomics 1, 1249–1263 (2001).
Celis, J. E. et al. Proteomics and immunohistochemistry define some of the steps involved in the squamous differentiation of the bladder transitional epithelium: a novel strategy for identifying metaplastic lesions. Cancer Res. 59, 3003–3009 (1999).
Celis, J. E., Wolf, H. & Ostergaard, M. Bladder squamous cell carcinoma biomarkers derived from proteomics. Electrophoresis 21, 2115–2121 (2000).
Celis, J. E. et al. Proteomic strategies to reveal tumor heterogeneity among urothelial papillomas. Mol. Cell Proteomics 1, 269–279 (2002).
Chen, G. et al. Proteomic analysis of lung adenocarcinoma: identification of a highly expressed set of proteins in tumors. Clin. Cancer Res. 8, 2298–2305 (2002).
Meehan, K. L., Holland, J. W. & Dawkins, H. J. Proteomic analysis of normal and malignant prostate tissue to identify novel proteins lost in cancer. Prostate 50, 54–63 (2002).
Franzen, B. et al. Analysis of polypeptide expression in benign and malignant human breast lesions. Electrophoresis 18, 582–587 (1997).
Bini, L. et al. Protein expression profiles in human breast ductal carcinoma and histologically normal tissue. Electrophoresis 18, 2832–2841 (1997).
Emmert-Buck, M. R. et al. Laser capture microdissection. Science 274, 998–1001 (1996).
Banks, R. E. et al. The potential use of laser capture microdissection to selectively obtain distinct populations of cells for proteomic analysis: preliminary findings. Electrophoresis 20, 689–700 (1999).
Ahram, M. et al. Proteomic analysis of human prostate cancer. Mol. Carcinog. 33, 9–15 (2002).
Liotta, L. & Petricoin, E. Molecular profiling of human cancer. Nature Rev. Genet. 1, 48–56 (2000).
Craven, R. A., Totty, N., Harnden, P., Selby, P. J. & Banks, R. E. Laser capture microdissection and two-dimensional polyacrylamide gel electrophoresis. Evaluation of tissue preparation and sample limitations. Am. J. Pathol. 160, 815–822 (2002).
Jones, M. B. et al. Proteomic analysis and identification of new biomarkers and therapeutic targets for invasive ovarian cancer. Proteomics 2, 76–84 (2002).
Ornstein, D. K. et al. Characterization of intracellular prostate-specific antigen from laser capture microdissected benign and malignant prostatic epithelium. Clin. Cancer Res. 6, 353–356 (2000).
Paweletz, C. P. et al. Loss of annexin 1 correlates with early onset of tumorigenesis in esophageal and prostate cancer. Cancer Res. 60, 6293–6297 (2000).
Wulfkuhle, J. D. et al. Proteomics of human breast ductal carcinoma in situ. Cancer Res. 62, 6740–6749 (2002). Reports the first proteomic analysis of microdissected cell populations from patient-matched normal breast epithelial tissue and ductal carcinoma in situ lesions. Differentially expressed proteins were identified by 2D-PAGE followed by mass spectrometry sequencing and 14 proteomic trends were verified by immunohistochemical analysis in a small, independent breast tumour cohort.
Storm, F., Gilchrist, K., Warner, T. & Mahvi, D. Distribution of Hsp27 and HER-2/neu in in situ and invasive ductal breast carcinomas. Ann. Surg. Oncol. 2, 43–48 (1995).
Shields, J. M., Rogers-Graham, K. & Der, C. J. Loss of transgelin in breast and colon tumors and in RIE-1 cells by Ras deregulation of gene expression through Raf-independent pathways. J. Biol. Chem. 277, 9790–9799 (2002).
Unlu, M., Morgan, M. E. & Minden, J. S. Difference gel electrophoresis: a single gel method for detecting changes in protein extracts. Electrophoresis 18, 2071–2077 (1997).
Zhou, G. et al. 2D differential in-gel electrophoresis for the identification of esophageal scans cell cancer-specific protein markers. Mol. Cell Proteomics 1, 117–124 (2002).
Le Naour, F. et al. Proteomics-based identification of RS/DJ-1 as a novel circulating tumor antigen in breast cancer. Clin. Cancer Res. 7, 3328–3335 (2001).
Le Naour, F. et al. A distinct repertoire of autoantibodies in hepatocellular carcinoma identified by proteomic analysis. Mol. Cell Proteomics 1, 197–203 (2002).
Brichory, F., Beer, D., Le Naour, F., Giordano, T. & Hanash, S. Proteomics-based identification of protein gene product 9.5 as a tumor antigen that induces a humoral immune response in lung cancer. Cancer Res. 61, 7908–7912 (2001). Describes the use of a proteomics-based approach to identify tumour antigens that induce a humoral immune response in lung cancer. Antibodies against PGP9.5 were identified in 9 of 64 sera from newly diagnosed lung cancer patients, but only 1 of 71 sera from non-lung cancer patients.
Robinson, W. H. et al. Autoantigen microarrays for multiplex characterization of autoantibody responses. Nature Med. 8, 295–301 (2002).
Chaurand, P., Schwartz, S. A. & Caprioli, R. M. Imaging mass spectrometry: a new tool to investigate the spatial organization of peptides and proteins in mammalian tissue sections. Curr. Opin. Chem. Biol. 6, 676–681 (2002).
Chaurand, P. & Caprioli, R. M. Direct profiling and imaging of peptides and proteins from mammalian cells and tissue sections by mass spectrometry. Electrophoresis 23, 3125–3135 (2002).
Stoeckli, M., Chaurand, P., Hallahan, D. E. & Caprioli, R. M. Imaging mass spectrometry: a new technology for the analysis of protein expression in mammalian tissues. Nature Med. 7, 493–496 (2001). Description of a technology that allows for direct mapping of protein expression in a tissue section by mass spectrometry. A frozen tissue section is placed directly in a mass spectrometer and a pulsed laser desorbs and ionizes analytes from any number of regions of the tissue section and m/z values are determined by a time-of-flight analyser. A rasterized image of peak intensities for any given m/z value can be overlayed on the tissue section to generate a three-dimensional expression map.
Li, J., Wang, C., Kelly, J. F., Harrison, D. J. & Thibault, P. Rapid and sensitive separation of trace level protein digests using microfabricated devices coupled to a quadrupole-time-of-flight mass spectrometer. Electrophoresis 21, 198–210 (2001).
Shen, Y. et al. High-throughput proteomics using high-efficiency multiple-capillary liquid chromatography with on-line high-performance ESI FTICR mass spectrometry. Anal. Chem. 73, 3011–3021 (2001).
Gygi, S. P. et al. Quantitative analysis of complex protein mixtures using isotope-coded affinity tags. Nature Biotechnol. 17, 994–999 (1999).
Krutchinsky, A. N., Kalkum, M. & Chait, B. T. Automatic identification of proteins with a MALDI-quadrupole ion trap mass spectrometer. Anal. Chem. 73, 5066–5077 (2001).
Washburn, M. P., Wolters, D. & Yates, J. R. Large scale analysis of the yeast proteome by multidimensional protein identification technology. Nature Biotechnol. 19, 242–247 (2001). An approach for rapid and large-scale proteomic analysis by multidimensional laser capture coupled with tandem mass spectrometry, termed multidimensional protein identification technology (MudPIT). This method was applied to yeast proteomic analysis and 1,484 proteins were detected and identified.
Washburn, M. P., Ulaszek, R., Deciu, C., Schieltz, D. M. & Yates, J. R. Analysis of quantitative proteomic data generated via multidimensional protein identification technology. Anal. Chem. 74, 1650–1657 (2002).
Paweletz, C. P. et al. Proteomic patterns of nipple aspirate fluids obtained by SELDI-TOF: potential for new biomarkers to aid in the diagnosis of breast cancer. Dis. Markers 17, 301–307 (2001).
Sauter, E. et al. Proteomic analysis of nipple aspirate fluid to detect biologic markers of breast cancer. Br. J. Cancer 86, 1440–1443 (2002).
Paweletz, C. P. et al. Rapid protein display profiling of cancer progression directly from human tissue using a protein biochip. Drug Dev. Res. 49, 34–42 (2000). First report in which laser capture microdissection is coupled to SELDI-TOF mass spectrometry for proteomic fingerprinting and pattern analysis of cancer tissue. Proteomic portraits from microdissected patient-matched normal, premalignant, malignant and metastatic cell populations for a variety of cancers were shown. Consistent sets of defined protein changes were identified in the transition from normal prostatic epithelium to malignancy and specific molecular portraits of different cancer types were discovered.
Cazares, L. H. et al. Normal, benign, preneoplastic and malignant prostate cells have distinct protein expression profiles resolved by surface enhanced laser desorption/ionization mass spectrometry. Clin. Cancer Res. 8, 2541–2552 (2002).
Liotta, L. A. & Kohn, E. C. The microenvironment of the tumour-host interface. Nature 411, 375–379 (2001).
Petricoin, E. F., Zoon, K. C., Kohn, E. C., Barrett, J. C. & Liotta, L. A. Clinical proteomics: translating benchside promise into bedside reality. Nat Rev Drug Discov 1, 683–695 (2002).
Vlahou, A. et al. Development of a novel proteomic approach for the detection of transitional cell carcinoma of the bladder in urine. Am. J. Pathol. 158, 1491–1502 (2001).
Petricoin, E. F. et al. Use of proteomic patterns in serum to identify ovarian cancer. Lancet 359, 572–577 (2002). Describes the first report and outlines the development of a new model for the diagnosis of disease based on pattern analysis of serum proteomic profiles. The method uses an artificial-intelligence-based computer algorithm to evaluate mass spectral patterns from low-resolution high-throughput mass spectrometry and was successful in discriminating normal serum samples from those of early-stage ovarian cancer patients.
Menon, U. & Jacobs, I. J. in Principles and Practice of Gynecologic Oncology (eds Hoskins, W. J., Perez, C. A. & Young, R. C.) 165–182 (Lippincott, Williams and Wilkins, Philadelphia, 2000).
Friedlander, M. L. Prognostic factors in ovarian cancer. Semin. Oncol. 25, 305–314 (1998).
Jacobs, I. J. et al. Screening for ovarian cancer: a pilot randomised controlled trial. Lancet 353, 1207–1210 (1999).
Menon, U. & Jacobs, I. Screening for ovarian cancer. Best Pract. Res. Clin. Obstet. Gynaecol. 16, 469–482 (2002).
McGuire, V., Jesser, C. A. & Whittemore, A. S. Survival among US women with invasive epithelial ovarian cancer. Gynecol. Oncol. 84, 399–403 (2002).
Li, J., Zhang, Z., Rosenzweig, J., Wang, Y. Y. & Chan, D. W. Proteomics and bioinformatics approaches for identification of serum biomarkers to detect breast cancer. Clin. Chem. 48, 1296–1304 (2002).
Arcangeli, C. G., Ornstein, D. K., Keetch, D. W. & Andriole, G. L. Prostate-specific antigen as a screening test for prostate cancer. The United States experience. Urol Clin North Am 24, 299–306 (1997).
Adam, B.-L. et al. Serum protein fingerprinting coupled with a pattern-matching algorithm distinguishes prostate cancer from benign prostate hyperplasia and healthy men. Cancer Res. 62, 3609–3614 (2002). Follows and confirms the model first described in reference 53 to see if proteomic pattern analysis could differentiate serum of prostate cancer patients from non-cancer cohorts. A test set of serum samples yielded a sensitivity of 83% and specificity of 97% for the study population when comparing the prostate cancer versus the benign disease/normal groups.
Qu, Y. et al. Boosted decision tree analysis of surface-enhanced laser desorption/ionization mass spectral serum profiles discriminates prostate cancer from noncancer patients. Clin. Chem. 48, 1835–1843 (2002).
Petricoin, E. F. et al. Serum proteomic patterns for detection of prostate cancer. J. Natl Cancer Inst. 94, 1576–1578 (2002).
Link, A. J. Multidimensional peptide separations in proteomics. Trends Biotechnol. 20, S8–S13 (2002).
Schweitzer, B. & Kingsmore, S. F. Measuring proteins on microarrays. Curr. Opin. Biotechnol. 13, 14–19 (2002).
Mendoza, L. G. et al. High-throughput microarray-based enzyme-linked immunosorbent assay (ELISA). Biotechniques 27, 778–780 (1999).
Cahill, D. J. Protein and antibody arrays and their medical applications. J. Immunol. Methods 250, 81–91 (2001).
Knezevic, V. et al. Proteomic profiling of the cancer microenvironment by antibody arrays. Proteomics 1, 1271–1278 (2001).
de Wildt, R. M. T., Mundy, C. R., Gorick, B. D. & Tomlinson, I. M. Antibody arrays for high-throughput screening of antibody-antigen interactions. Nature Biotechnol. 18, 989–994 (2000).
Lueking, A. et al. Protein microarrays for gene expression and antibody screening. Anal. Biochem. 270, 103–111 (1999).
Madoz-Gurpide, J., Wang, H., Misek, D. E., Brichory, F. & Hanash, S. M. Protein based microarrays: a tool for probing the proteome of cancer cells and tissues. Proteomics 1, 1279–1287 (2001).
Ball, G. et al. An integrated approach utilizing artificial neural networks and SELDI mass spectrometry for the classification of human tumours and rapid identification of potential biomarkers. Bioinformatics 18, 395–404 (2002).
Ting, K. L., Lee, R. C., Chang, C. L. & Guarino, A. M. The relationship between the mass spectra of drugs and their biological activity: an application of artificial intelligence to chemistry. Comput. Biol. Med. 4, 301–332 (1975).
Nicholson, J. K., Connelly, J., Lindon, J. C. & Holmes, E. Metabonomics: a platform for studying drug toxicity and gene function. Nat Rev Drug Discov 1, 153–161 (2002).
Alizadeh, A. A. et al. Distinct types of diffuse large B-cell lymphoma identified by gene expression profiling. Nature 403, 503–511 (2000).
Golub, T. R. et al. Molecular classification of cancer: class discovery and class prediction by gene expression monitoring. Science 286, 531–537 (1999).
Lindahl, D., Palmer, J. & Edenbrandt, L. Myocardial SPET: artificial neural networks describe extent and severity of perfusion defects. Clin. Physiol. 19, 497–503 (1999).
Lapuerta, P. et al. Neural network assessment of perioperative cardiac risk in vascular surgery patients. Med. Decis. Making 18, 70–75 (1998).
Holland, J. H. (ed.) Adaption in Natural and Artificial Systems: an Introductory Analysis with Applications to Biology, Control, and Artificial Intelligence (MIT Press, Cambridge, Massachusetts, 1994).
Kohonen, T. Self-organized formation of topologically correct feature maps. Biol. Cybern. 43, 59–63 (1982).
Kohonen, T. The self-organizing map. Proc. IEEE 78, 1464–1480 (1990).
Tou, J. T. & Gonzalez, R. in Pattern Recognition Principles (eds Tou, J. T. & Gonzalez, R.) 75–109 (Addison Weley, Reading, Massachusetts, 1974).
- PROSTATE-SPECIFIC ANTIGEN
The serum level of this protein increases in some men who have prostate cancer or certain benign prostate conditions.
- GENOMIC TECHNOLOGIES
Techniques for gene-expression analysis, including oligonucleotide arrays for determining relative levels of expression for thousands of genes between different samples (e.g. normal and tumour) that can lead to the identification of tumour-specific markers.
- ELISA (Enzyme-linked, immunosorbent assay).
A sensitive antibody-based method for the detection of an antigen such as a protein.
A method for separating proteins by both mass and charge.
- MASS SPECTROMETRY
A field that, in its biological applications, uses sophisticated analytical devices to determine the precise molecular weights (mass) of proteins and nucleic acids, as well as the amino-acid sequence of protein molecules.
- LASER CAPTURE MICRODISSECTION
A technology that is used for the rapid procurement of a microscopic and pure cellular subpopulation away from its complex tissue milieu, under direct microscopic visualization.
- MATRIX COMPOUND
A chemical compound (organic acid) that is used to absorb laser energy and transfer this to biomolecules that are present in the sample, causing them to become protonated and ionized.
- IMAGING MASS SPECTROMETRY
An application of a scanning type of mass spectrometry that allows for direct mapping of protein expression profiles that are present in tissue sections or individual cells.
- BENIGN PROSTATIC HYPERPLASIA
A non-cancerous condition in which an overgrowth of prostate tissue pushes against the urethra and the bladder, blocking the flow of urine.
- 'DISRUPTIVE' OR 'NON-LINEAR' TECHNOLOGY
A technology that represents a significant, unexpected change in an existing model that does not progress in a straightforward linear fashion, thereby polarizing the existing infrastructure.
About this article
Cite this article
Wulfkuhle, J., Liotta, L. & Petricoin, E. Proteomic applications for the early detection of cancer. Nat Rev Cancer 3, 267–275 (2003). https://doi.org/10.1038/nrc1043
High expression of olfactomedin-4 is correlated with chemoresistance and poor prognosis in pancreatic cancer
PLOS ONE (2020)
Analytical and Bioanalytical Chemistry (2020)
Highly sensitive microfluidic detection of carcinoembryonic antigen via a synergetic fluorescence enhancement strategy based on the micro/nanostructure optimization of ZnO nanorod arrays and in situ ZIF-8 coating
Chemical Engineering Journal (2020)
Rapid, quantitative and ultra-sensitive detection of cancer biomarker by a SERRS-based lateral flow immunoassay using bovine serum albumin coated Au nanorods
RSC Advances (2020)
Review—Recent Advances in Electrochemical Detection of Prostate Specific Antigen (PSA) in Clinically-Relevant Samples
Journal of The Electrochemical Society (2020)