Biomarker

A biomarker is a measurable and quantifiable biological parameter that serves as an indicator of a particular physiological state or of pharmacologic responses to a therapeutic intervention. In a medical context, a biomarker is a substance whose detection indicates a particular disease state, for example, the presence of specific pathological entities, cytological or histological characteristics, gene or chromosome mutations, particular transcripts of proteins, posttranslational variants, or alterations in the level of messenger ribonucleic acid (mRNA) and protein expression. Several decades of intensive research have produced molecular markers as tools for health-related assessments, epidemiologic studies, and the diagnosis of degenerative and disabling diseases, such as cancer, cardiovascular, neurological, and inflammatory diseases.

The ability to effectively treat and cure a disease is often directly dependent on the capability to detect it at its earliest stage. Especially for cancer, there is an urgent need to improve early diagnostics, as it is often diagnosed in advanced stages, delaying timely treatment and leading to a poor prognosis. A cancer biomarker refers to a molecule that is indicative of the presence of cancer. It can be a specific response of the body or it can be secreted by the malignancy itself.

With the recent developments in the fields of genomics and proteomics, there is an increasing interest in cancer risk assessment, monitoring progression, predicting recurrence, and determining the efficacy of therapeutic treatment. New technologies such as DNA and tissue microarray, two-dimensional gel electrophoresis, mass spectrometry, and protein assays coupled with advanced bioinformatic tools are being applied to complex biosystems in order to uncover molecular mechanisms associated with cancer that may lead to new diagnostic tests and improvements in therapeutics. For clinical implementation and routine use, the ideal biomarker should be highly specific for a particular disease condition and should be measurable in easily accessible body fluids such as saliva, serum, or urine. Examples of routinely used biomarkers include CA 15–3 (breast cancer), CA 125 (ovarian cancer), and PSA (prostate cancer).

However, such biomarkers are rare, and most candidate biomarkers are found in many different types of disease. In this case, biomarker pattern proteome analysis can be used to study the expression profiles of hundreds of proteins in parallel. Thus, several relatively nonspecific biomarkers can be combined in order to provide a more specific disease index.

Proteomic pattern analysis based on mass spectrometry using the ProteinChip/SELDI-TOF platform holds special promise for the discovery of novel bio-markers as it distinguishes disease and disease-free states with high sensitivity and specificity. It allows an analysis of complex protein mixtures by combining two formerly well-established methods—solid phase chromatography and TOF-MS—for the conduction of expression difference mapping applications on one platform. Applying computational methods, the generated multiple proteomic spectra are superimposed to detect changes in protein expression and their association to disease conditions.

Recent mass spectrometry technologic developments with high-throughput protein expression measurements permit the large-scale comparison of proteomic expression patterns of different clinical specimens. Up to now, investigators using these technologies in search of biomarkers, in particular for different types of cancer, mainly report on concentration changes and molecular modifications of abundant host response serum proteins. Recent studies on posttranslationally modified host response proteins and degradation products indicate that the identified modifications and degradation products are disease-specific signatures.

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