Biomarker (medicine)

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For other uses, see Biomarker (disambiguation).

In medicine, a biomarker is a term often used to refer to a protein measured in blood whose concentration reflects the severity or presence of some disease state. More generally a biomarker is anything that can be used as an indicator of a particular disease state or some other biological state of an organism.

A biomarker can be a substance that is introduced into an organism as a means to examine organ function or other aspects of health. For example, rubidium chloride is used as a radioactive isotope to evaluate perfusion of heart muscle. It can also be a substance whose detection indicates a particular disease state, for example, the presence of an antibody may indicate an infection. More specifically, a biomarker indicates a change in expression or state of a protein that correlates with the risk or progression of a disease, or with the susceptibility of the disease to a given treatment. Biomarkers are characteristic biological properties that can be detected and measured in parts of the body like the blood or tissue. They may indicate either normal or diseased processes in the body.[1] Biomarkers can be specific cells, molecules, or genes, gene products, enzymes, or hormones. Complex organ functions or general characteristic changes in biological structures can also serve as biomarkers. Although the term biomarker is relatively new, biomarkers have been used in pre-clinical research and clinical diagnosis for a considerable time.[2] For example, body temperature is a well-known biomarker for fever. Blood pressure is used to determine the risk of stroke. It is also widely known that cholesterol values are a biomarker and risk indicator for coronary and vascular disease, and that C-reactive protein (CRP) is a marker for inflammation.

A biomarker is a parameter that can be used to measure the progress of disease or the effects of treatment. The parameter can be chemical, physical or biological. In molecular terms biomarker is "the subset of markers that might be discovered using genomics, proteomics technologies or imaging technologies. Biomarkers plays major role in medicinal biology. Biomarker brings the future things in our hand by helping in early diagnosis, disease prevention, drug target identification, drug response etc. Several diseased based biomarker had been identified for many diseases such as serum LDL for cholesterol, blood pressure, P53 gene[3] and MMPs [4] for cancer etc. Gene based biomarker is found to be an effective and acceptable marker in the present scientific world.

Disease-related Biomarkers and Drug-related Biomarkers

It is necessary to distinguish between disease-related and drug-related biomarkers. Disease-related biomarkers give an indication of whether there is a threat of disease (risk indicator or predictive biomarkers), if a disease already exists (diagnostic biomarker), or how such a disease may develop in an individual case (prognostic biomarker). In contrast, drug-related biomarkers indicate whether a drug will be effective in a specific patient and how the patient’s body will process it.

In addition to long-known parameters, such as those included and objectively measured in a blood count, there are numerous novel biomarkers used in the various medical specialties. Currently, intensive work is taking place on the discovery and development of innovative and more effective biomarkers. These "new" biomarkers have become the basis for preventive medicine, meaning medicine that recognises diseases or the risk of disease early, and takes specific countermeasures to prevent the development of disease. Biomarkers are also seen as the key to personalised medicine, treatments individually tailored to specific patients for highly efficient intervention in disease processes. Often, such biomarkers indicate changes in metabolic processes.

The "classic" biomarker in medicine is a laboratory parameter that the doctor can use to help make decisions in making a diagnosis and selecting a course of treatment. For example, the detection of certain autoantibodies in patient blood is a reliable biomarker for autoimmune disease, and the detection of rheumatoid factors has been an important diagnostic marker for rheumatoid arthritis (RA) for over 50 years.[5][6] For the diagnosis of this autoimmune disease the antibodies against the bodies own citrullinated proteins are of particular value. These ACPAs, (ACPA stands for Anti-citrullinated protein/peptide antibody) can be detected in the blood before the first symptoms of RA appear. They are thus valuable and highly predictive biomarkers for the early diagnosis of this autoimmune disease.[7] In addition, they indicate if the disease threatens to be severe with serious damage to the bones and joints,[8][9] which is an important tool for the doctor when providing a diagnosis and developing a treatment plan.

There are also more and more indications that ACPAs can be very useful in monitoring the success of treatment for RA.[10] This would make possible the accurate use of modern treatments with biologicals. Physicians hope to soon be able to individually tailor rheumatoid arthritis treatments for each patient.

According to Häupl T. et al. prediction of response to treament will become the most important aim of biomarker research in medicine. With the growing number of new biological agents, there is increasing pressure to identify molecular parameters such as ACPAs that will not only guide the therapeutic decision but also help to define the most important targets for which new biological agents should be tested in clinical studies.[11]

An NIH study group committed to the following definition in 1998: "a characteristic that is objectively measured and evaluated as an indicator of normal biologic processes, pathogenic processes, or pharmacologic responses to a therapeutic intervention." In the past, biomarkers were primarily physiological indicators such as blood pressure or heart rate. More recently, biomarker is becoming a synonym for molecular biomarker, such as elevated prostate specific antigen as a molecular biomarker for prostate cancer, or using enzyme assays as liver function tests. There has recently been heightened interest in the relevance of biomarkers in oncology, including the role of KRAS in CRC and other EGFR-associated cancers. In patients whose tumors express the mutated KRAS gene, the KRAS protein, which forms part of the EGFR signaling pathway, is always ‘turned on’. This overactive EGFR signaling means that signaling continues downstream – even when the upstream signaling is blocked by an EGFR inhibitor, such as cetuximab (Erbitux) – and results in continued cancer cell growth and proliferation. Testing a tumor for its KRAS status (wild-type vs. mutant) helps to identify those patients who will benefit most from treatment with cetuximab.

Biomarkers also cover the use of molecular indicators of environmental exposure in epidemiologic studies such as human papilloma virus or certain markers of tobacco exposure such as 4-(methylnitrosamino)-1-(3-pyridyl)-1-butanone (NNK). To date no biomarkers have been established for SCCHN.

Biomarkers in Drug Development

Once a proposed biomarker has been validated, it can be used to diagnose disease risk, presence of disease in an individual, or to tailor treatments for the disease in an individual (choices of drug treatment or administration regimes). In evaluating potential drug therapies, a biomarker may be used as a surrogate for a natural endpoint such as survival or irreversible morbidity. If a treatment alters the biomarker, which has a direct connection to improved health, the biomarker serves as a surrogate endpoint for evaluating clinical benefit. Some of the main areas in which molecular biomarkers are used in the drug development process are: Early drug development studies, Safety studies, Proof of concept studies, Molecular profiling.

Molecular biomarkers are often used in early drug development studies. For instance, they are used in phase I study for establishing doses and dosing regimen for future phase II studies. PD biomarkers are commonly observed to respond (either decrease or increase) proportionally with dose. This data, in conjunction with safety data, help determine doses for phase II studies. In addition, Safety molecular biomarkers have been used for decades both in preclinical and clinical research. Since these tests have become mainstream tests, they have been fully automated for both animal and human testing. Among the most common safety tests are those of liver function(eg, transaminases, bilirubin, alkaline phosphatase) and kidney function(eg, serum creatinine, creatinine clearance, cystatin C). Others include markers of skeletal muscle(eg, myoglobin) or cardiac muscle injury(eg, CK-MB, troponin I or T), as well as bone biomarkers(eg, bone-specific alkaline phosphatase).

Biomarker requirements

For chronic diseases, whose treatment may require patients to take medications for years, accurate diagnosis is particularly important, especially when strong side effects are expected from the treatment. In these cases, biomarkers are becoming more and more important, because they can confirm a difficult diagnosis or even make it possible in the first place.[12] A number of diseases, such as Alzheimer’s disease or rheumatoid arthritis, often begin with an early, symptom-free phase. In such symptom-free patients there may be more or less probability of actually developing symptoms. In these cases, biomarkers help to identify high-risk individuals reliably and in a timely manner so that they can either be treated before onset of the disease or as soon as possible thereafter.[13][14]

In order to use a biomarker for diagnostics, the sample material must be as easy to obtain as possible. This may be a blood sample taken by a doctor, a urine or saliva sample, or a drop of blood like those diabetes patients extract from their own fingertips for regular blood-sugar monitoring.

For rapid initiation of treatment, the speed with which a result is obtained from the biomarker test is critical. A rapid test, which delivers a result after only a few minutes, is optimal. This makes it possible for the physician to discuss with the patient how to proceed and if necessary to start treatment immediately after the test.

Naturally, the detection method for a biomarker must be accurate and as easy to carry out as possible. The results from different laboratories may not differ significantly from each other, and the biomarker must naturally have proven its effectiveness for the diagnosis, prognosis, and risk assessment of the affected diseases in independent studies.

Biomarker classification and application

Biomarkers can be classified based on different parameters. They can be classified based on their characteristics such as imaging biomarkers (CT, PET, MRI) or molecular biomarkers. Molecular biomarkers can be used to refer to nonimaging biomarkers that have biophysical properties, which allow their measurements in biological samples (eg, plasma, serum, cerebrospinal fluid, bronchoalveolar lavage, biopsy) and include nucleic acids-based biomarkers such as gene mutations or polymorphisms and quantitative gene expression analysis, peptides, proteins, lipids metabolites, and other small molecules. Biomarkers can also be classified based on their application such as diagnostic biomarkers (ie, cardiac troponin for the diagnosis of myocardial infarction), staging of disease biomarkers (ie, brain natriuretic peptide for congestive heart failure), disease prognosis biomarkers (cancer biomarkers), and biomarkers for monitoring the clinical response to an intervention (HbAlc for antidiabetic treatment). Another category of biomarkers includes those used in decision making in early drug development. For instance, pharmacodynamic (PD) biomarkers are markers of a certain pharmacological response, which are of special interest in dose optimization studies.

Types

Biomarkers validated by genetic and molecular biology methods can be classified into three types.

  • Type 0 - Natural history markers
  • Type 1 - Drug activity markers
  • Type 2 - Surrogate markers

Discovery of molecular biomarker

Main article: Biomarker discovery

Molecular biomarkers have been defined as biomarkers that can be discovered using basic and acceptable platforms such as genomics and proteomics.Many genomic and proteomics techniques are available for biomarker discovery and few recently using techniques are given below. Apart from genomics and proteomics platforms biomarker assay techniques. Metabolomics, Lipidomics, and Glycomics are also the most commonly used as techniques in identification of biomarker.

Genomic Approach

1.Northern blot

2.Gene expression

3.SAGE

4.DNA Microarray[15]

Proteomic Approach

1.2D-PAGE

2.LS/MS

3.SELDI-TOF

4.Ab Microarray

5.Tissue Microarray

Metabolomics Approach

The term metabolomics has been recently introduced to address the global analysis of all metabolites in a biological sample. A related term, metabonomics, was introduced to refer specifically to the analysis of metabolic responses to drugs or diseases. Metabonomics become a major area of research it is the complex system biological study,used as a to identify the biomarker for various disease. In general most of the disease case some of the metabolic pathway had been activate or deactivated,this parameter can be used as a marker for some diseases. Serotonin production pathway activated in alcoholic drinking person it can be metabolic marker of recent alcohol consumption.

Lipidomics Approach

Lipidomics refers to the analysis of lipids. Since lipids have unique physical properties, they have been traditionally difficult to study. However, improvements in new analytical platforms have made it possible to identify and to quantify most of lipids metabolites from a single sample. Three key platforms used for lipid profiling include mass spectrometry, chromatography, and nuclear magnetic resonance. Mass spectrometry was used to delineate the relative concentration and composition of high-density lipoproteins (HDL) particles from lipid extracts isolated from coronary bypass patients and healthy volunteers. They found that HDL particles from coronary bypass patients contained significantly less sphingomyelin relative to phosphadidylcholine and higher triglycerides relative to cholesterol esters. Lipidomic profiling was also used to study the effect of rosiglitazone, a PPARγ agonist, on lipid metabolism on mice. Rosiglitazone was observed to alter lipid composition in different organs. It increased triglycérides accumulation in the liver; altered free fatty acids in the heart, in the adipose tissue, and in the heart; and reduced triglyceride levels in plasma.

Imaging biomarkers

Many new biomarkers are being developed that involve imaging technology. Imaging biomarkers have many advantages. They are usually noninvasive, and they produce intuitive, multidimensional results. Yielding both qualitative and quantitative data, they are usually relatively comfortable for patients. When combined with other sources of information, they can be very useful to clinicians seeking to make a diagnosis.

Cardiac imaging is an active area of biomarker research. Coronary angiography, an invasive procedure requiring catheterization, has long been the gold standard for diagnosing arterial stenosis, but scientists and doctors hope to develop noninvasive techniques. Many believe that cardiac computed tomography (CT) has great potential in this area, but researchers are still attempting to overcome problems related to “calcium blooming,” a phenomenon in which calcium deposits interfere with image resolution. Other intravascular imaging techniques involving magnetic resonance imaging (MRI), optical coherence tomography (OCT), and near infrared spectroscopy are also being investigated.

Another new imaging biomarker involves radiolabeled fludeoxyglucose. Positron emission tomography (PET) can be used to measure where in the body cells take up glucose. By tracking glucose, doctors can find sites of inflammation because macrophages there take up glucose at high levels. Tumors also take up a lot of glucose, so the imaging strategy can be used to monitor them as well. Tracking radiolabeled glucose is a promising technique because it directly measures a step known to be crucial to inflammation and tumor growth.

Potential disadvantages

Not all biomarkers should be used as surrogate endpoints to assess clinical outcomes. Biomarkers can be difficult to validate and require different levels of validation depending on their intended use. If a biomarker is to be used to measure the success of a therapeutic intervention, the biomarker should reflect a direct effect of that intervention.

An example from the 1980s demonstrates the pitfalls of depending too heavily on biomarkers. In the mid-1980s two new drugs, flecainide and encainide, were introduced to reduce ventricular arrhythmias in patients with histories of heart disease. The drugs did indeed reduce arrhythmias. A large trial, the CAST trial, was undertaken to test the efficacy of the drugs, but the trial was stopped after a year because patients taking the drugs were found to be more than twice as likely to die as patients taking placebos. Flecainide and encainide were recalled in 1991. Their example demonstrates that improving a biomarker does not necessarily translate into increased survival.

See also

References

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External links

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  1. ↑ http://www.biomarkersconsortium.org
  2. ↑ http://www.biomarker.co.uk/whatisabiomarkers.html
  3. ↑ Loukopoulos P, Thornton JR , Robinson WF. Clinical and pathologic relevance of p53 index in canine osseous tumors. Veterinary Pathology 2003; 40:237-248
  4. ↑ Loukopoulos P, Mungall BA, Straw RC, Thornton JR , Robinson WF. Matrix metalloproteinase-2 and -9 involvement in canine tumors. Veterinary Pathology 2003; 40:382-394
  5. ↑ Waaler E. "On the occurrence of a factor in human serum activating the specific agglutintion of sheep blood corpuscles. 1939". APMIS 2007 (May) 115 (5): 422–38. 
  6. ↑ Rose HM, Ragan E, Pearce E, Lipman MO. "Differential agglutination of normal and sensitized sheep erythrocytes by sera of patients with rheumatoid arthritis". Proc Soc Exp Biol Med. 1948 May;68(1):1-6. 
  7. ↑ Bang H, Egerer K, Gauliard A, Lüthke K, Rudolph PE, Fredenhagen G; et al. (2007). "Mutation and citrullination modifies vimentin to a novel autoantigen for rheumatoid arthritis". Arthritis Rheum. 56 (8): 2503–11. 
  8. ↑ Szodoray P, Szabó Z, Kapitány A, Gyetvai A, Lakos G, Szántó S, Szücs G, Szekanecz Z. "Anti-citrullinated protein/peptide autoantibodies in association with genetic and environmental factors as indicators of disease outcome in rheumatoid arthritis". Autoimmun Rev. 2009 May 6. [Epub ahead of print]. 
  9. ↑ Mathsson L, Mullazehi M, Wick MC, Sjöberg O, van Vollenhoven R, Klareskog L, Rönnelid J. "Antibodies against citrullinated vimentin in rheumatoid arthritis: higher sensitivity and extended prognostic value concerning future radiographic progression as compared with antibodies against cyclic citrullinated peptides". Arthritis Rheum. 2008 Jan;58(1):36-45. 
  10. ↑ Nicaise Roland P, Grootenboer Mignot S, Bruns A, Hurtado M, Palazzo E, Hayem G, Dieudé P, Meyer O, Chollet Martin S. "Antibodies to mutated citrullinated vimentin for diagnosing rheumatoid arthritis in anti-CCP-negative patients and for monitoring infliximab therapy". Arthritis Res Ther. 2008;10(6):R142. 
  11. ↑ Häupl T, Stuhlmüller B, Grützkau A, Radbruch A, Burmester GR. "Does gene expression analysis inform us in rheumatoid arthritis?". Ann Rheum Dis. 2010 Jan;69 Suppl 1:i37-42. 
  12. ↑ Pharma Matters White Paper: Establishing the standards in biomarker research (2008). Thomson Reuters
  13. ↑ Craig-Schapiro R, Fagan AM, Holtzman DM. "Biomarkers of Alzheimer's disease". Neurobiol Dis. 2008 Oct 28. 
  14. ↑ Egerer K, Feist E, Burmester G. "The Serological Diagnosis of Rheumatoid Arthritis – Antibodies to citrullinated Antigens". Dtsch Arztebl Int 2009; 106(10): 159-63. 
  15. ↑ Loukopoulos P, Shibata T, Katoh H, Kokubu A, Sakamoto M, Yamazaki K, Kosuge T, Kanai Y, Hosoda F, Imoto I, Ohki M, Inazawa J , Hirohashi S. Genome-wide array-based comparative genomic hybridization analysis of pancreatic adenocarcinoma: Identification of genetic indicators that predict patient outcome. Cancer Science 2007; 98:392-400
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