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Clinical proteomics: translating benchside promise into bedside reality

Key Points

  • Early detection of cancer should increase the likelihood that treatments achieve a true cure. However, several cancers, such as ovarian cancer, lack a specific symptom and a specific biomarker, and accurate and reliable diagnostic non-invasive modalities.

  • The microenvironment of the tumor–host interaction is a potential source for biomarkers that could be shed into the serum proteome. However, looking for single proteins with expression levels in serum that are altered significantly as a result of the disease process is laborious and time consuming.

  • Analysis of serum proteomic patterns comprising many individual proteins, each of which independently were not able to differentiate diseased from healthy individuals, has recently been shown to provide a diagnostic end point for cancer detection.

  • Analysing the proteins that change in actual diseased human tissue offers new opportunities for the identification of therapeutic targets.

  • Laser-capture microdissection (LCM) is a technology for procuring pure cell populations from a stained tissue section under direct microscopic visualization, and has been applied to discover new protein targets that are either a cause, or consequence, of the disease process in the actual tissue.

  • A new type of protein array — the reverse-phase protein array — is particularly suited to analysing protein signalling pathways using small numbers of human tissue cells microdissected from biopsy specimens procured during clinical trials.

  • In summary, clinical proteomics could have significant potential in the following crucial elements of patient care and management:

  • early detection of the disease using proteomic patterns of body fluid samples;

  • diagnosis based on proteomic signatures as a complement to histopathology;

  • individualized selection of therapeutic combinations that best target the patient's entire disease-specific protein network;

  • real-time assessment of therapeutic efficacy and toxicity;

  • rational redirection of therapy based on changes in the diseased protein network that are associated with drug resistance.

  • Combinatorial therapy, in which the signalling pathway itself is viewed as the target rather than any single 'node' in the pathway, might offer new opportunities at increasing efficacy while decreasing toxicity.

Abstract

The ultimate goal of proteomics is to characterize the information flow through protein networks. This information can be a cause, or a consequence, of disease processes. Clinical proteomics is an exciting new subdiscipline of proteomics that involves the application of proteomic technologies at the bedside, and cancer, in particular, is a model disease for studying such applications. Here, we describe proteomic technologies that are being developed to detect cancer earlier, to discover the next generation of targets and imaging biomarkers, and finally to tailor the therapy to the patient.

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Figure 1: Example of a protein signalling pathway.
Figure 2: Tumour–host interaction.
Figure 3: SELDI mass spectrometry.
Figure 4: Two-colour 2D-gel methodology.
Figure 5: Protein microarray.
Figure 6: Reverse-phase arrays.
Figure 7: Whole-body array.
Figure 8: Combinatorial therapy.
Figure 9: Proteomic technology applied to cancer-patient management.

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Correspondence to Emanuel F. Petricoin.

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DATABASES

Cancer.gov

breast cancer

colon cancer

lung cancer

ovarian cancer

prostate cancer

LocusLink

ABL

AKT

aurora 2

ERBB1

ERBB2

GFAP

myoglobin

PSA

Medscape DrugInfo

Gleevec

Herceptin

FURTHER INFORMATION

Clinical Proteomics Program Databank

National Cancer Institute

Glossary

METASTASIS

The movement or spreading of cancer cells from one organ or tissue to another. Cancer cells usually spread through the bloodstream or lymph system.

PERITONEAL CAVITY

The peritoneum is the thin membrane that lines the abdominal cavity.

TRAINING

A process in which a computer-driven system is provided data from a training set in which the outcome is known and is unblinded.

2D-PAGE

A method for separating proteins by mass and charge.

pI GRADIENTS

Isoelectric gradients are formed by subjecting a defined set of small molecules with specific net charges to an electric current, which allows the separation of proteins within the gradient, even if the proteins only differ in charge by one-thousandth of a pH unit.

CY3/CY5

Cy3 and Cy5 are water-soluble cyanine dyes that can be used as fluorescent labels for proteins and modified oligonucleotides.

REMATING

A computer-driven data-analysis process that is performed by combining solutions to select and retain the best elements of each solution, and discard those elements that do not solve the problem.

SELECTIVE PRESSURE

The ability of a computer-driven data-analysis process to restrict the solution output to those that pass a fixed criteria — in this case, the ability to distinguish normal from cancerous samples.

ICAT

A method in which proteins are labelled using isotope-coded affinity tags, which allows them to be systematically identified and quantified.

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Petricoin, E., Zoon, K., Kohn, E. et al. Clinical proteomics: translating benchside promise into bedside reality. Nat Rev Drug Discov 1, 683–695 (2002). https://doi.org/10.1038/nrd891

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