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A cancer biomarker refers to a substance or process that is indicative of the presence of cancer in the body. A biomarker may be a molecule secreted by a tumor or a specific response of the body to the presence of cancer. Genetic, epigenetic, proteomic, glycomic, and imaging biomarkers can be used for cancer diagnosis, prognosis, and epidemiology. Ideally, such biomarkers can be assayed in non-invasively collected biofluids like blood or serum.

While numerous challenges exist in translating biomarker research into the clinical space; a number of gene and protein based biomarkers have already been approved for use in patient care; including, AFP (Liver Cancer), BCR-ABL (Chronic Myeloid Leukemia), BRCA1 / BRCA2 (Breast/Ovarian Cancer), BRAF V600E (Melanoma/Colorectal Cancer), CA-125 (Ovarian Cancer), CA19.9 (Pancreatic Cancer), CEA (Colorectal Cancer), EGFR (Non-small Cell Lung Cancer), HER-2 (Breast Cancer), KIT (Gastrointestinal Stromal Tumor), PSA (Prostate Specific Antigen), S100 (Melanoma), and many others.



Definitions of Cancer Biomarkers
Different organizations and publications vary in their definition of biomarker. In many areas of medicine, biomarkers are limited to proteins identifiable or measurable in the blood or urine. However, the term is often used colloquially to cover any molecular, biochemical, physiological, or anatomical property that can be quantified and measured.

The National Cancer Institute (NCI), in particular, defines biomarker as a: “A biological molecule found in blood, other body fluids, or tissues that is a sign of a normal or abnormal process, or of a condition or disease. A biomarker may be used to see how well the body responds to a treatment for a disease or condition. Also called molecular marker and signature molecule."

In cancer research and medicine, biomarkers are used in three primary ways:
 * 1) To help diagnose conditions, as in the case of identifying early stage cancers (Diagnostic)
 * 2) To forecast how aggressive a condition is, as in the case of determining a patient's ability to fare in the absence of treatment (Prognostic)
 * 3) To predict how well a patient will respond to treatment (Predictive)

Risk Assessment
Cancer biomarkers, particular those associated with genetic mutations or epigenetic alterations, often offer a quantitative way to determine when individuals are predisposed to particular types of cancers. Notable examples of potentially predictive cancer biomarkers include mutations on genes KRAS, p53, EGFR, erbB2 for colorectal, esophageal, liver, and pancreatic cancer; mutations of genes BRCA1 and BRCA2 for breast and ovarian cancer; abnormal methylation of tumor suppressor genes p16, CDKN2B, and p14ARF for brain cancer; hypermethylation of MYOD1, CDH1, and CDH13 for cervical cancer; and hypermethylation of p16, p14, and RB1, for oral cancer.

Diagnostic
Cancer biomarkers can also be useful in establishing a specific diagnosis. This is particularly the case when there is a need to determine whether tumors are of primary or metastatic origin. To make this distinction, researchers will screen the chromosomal alterations found on cells located in the primary tumor site against those found in the secondary site. If the alterations match, the secondary tumor can be identified as metastatic; whereas if the alterations differ, the secondary tumor can be identified as a distinct primary tumor.

Prognostic

 * These cancer biomarkers help to assess the risk of developing a particular cancer and determine prognosis. Because certain cancers progress more rapidly than others, these biomarkers help the doctors to decide how aggressive the cancer treatment should be. An example of this type of cancer biomarker is tissue inhibitor of metalloprotease-1 (TIMP1), and gives a better prognosis to the myeloma patients with lower levels of this protein.

Predictive

 * Predict the response to cancer drug(s) or treatment(s) in the patient. An example of this is human epidermal growth factor receptor 2 (HER-2) overexpression due to an aberrant increase in the HER-2 gene. Breast cancer patients with this abnormal increase of HER-2 respond to trastuzumab (Herceptin®), a monoclonal antibody cancer drug. However, breast cancer patients not exhibiting the additional copies of the HER-2 gene are not recommended to go on this drug.

Pharmacodynamics and Pharmacokinetics

 * Cancer biomarkers under this category help determine the most effective dosage of drug or therapy is needed for that specific person. These biomarkers are just another tool aiding the field of personalized medicine. An example is the thiopurine methyl-transferase (TPMT) gene. Patients with mutations in the gene encoding TPMT are unable to metabolize large amounts of a leukemia drug, mercaptopurine, and this results in a possibly fatal drop in white blood cell count. Because of the TPMT biomarker, cancer patients with a mutation can take a lower, and safer, dose of the cancer drug.

Recurrence

 * Recurrence biomarkers are used to predict if cancer is likely to come back after treatment. An example is the Oncotype DX® breast cancer assay. This assay looks at several genes within a breast tumor sample and quantitatively indicates the probability that the patient’s cancer will return.

Prognostic

 * These cancer biomarkers help to assess the risk of developing a particular cancer and determine prognosis. Because certain cancers progress more rapidly than others, these biomarkers help the doctors to decide how aggressive the cancer treatment should be. An example of this type of cancer biomarker is tissue inhibitor of metalloprotease-1 (TIMP1), and gives a better prognosis to the myeloma patients with lower levels of this protein.

Diagnostic

 * Diagnose the particular type of cancer when pathologists are unable to identify the specific type of cancer from just looking at the cells.

Predictive

 * Predict the response to cancer drug(s) or treatment(s) in the patient. An example of this is human epidermal growth factor receptor 2 (HER-2) overexpression due to an aberrant increase in the HER-2 gene. Breast cancer patients with this abnormal increase of HER-2 respond to trastuzumab (Herceptin®), a monoclonal antibody cancer drug. However, breast cancer patients not exhibiting the additional copies of the HER-2 gene are not recommended to go on this drug.

Pharmacodynamics and Pharmacokinetics

 * Cancer biomarkers under this category help determine the most effective dosage of drug or therapy is needed for that specific person. These biomarkers are just another tool aiding the field of personalized medicine. An example is the thiopurine methyl-transferase (TPMT) gene. Patients with mutations in the gene encoding TPMT are unable to metabolize large amounts of a leukemia drug, mercaptopurine, and this results in a possibly fatal drop in white blood cell count. Because of the TPMT biomarker, cancer patients with a mutation can take a lower, and safer, dose of the cancer drug.

Recurrence

 * Recurrence biomarkers are used to predict if cancer is likely to come back after treatment. An example is the Oncotype DX® breast cancer assay. This assay looks at several genes within a breast tumor sample and quantitatively indicates the probability that the patient’s cancer will return.

Sensitivity and validity issues
Nothing is ever perfect, and cancer biomarkers also abide by this guideline. The sensitivity for a cancer biomarker is often debated because its reliability varies with the sensitivity of the biomarker. For example, if detection of lung cancer biomarker X could signify that ALL people with detectable levels of X would get lung cancer, but people without X would not develop lung cancer, then biomarker X would be the optimal lung cancer predictor. But in reality, there are going to be some false positives (which tell healthy people they will get lung cancer) and false negatives (which tell at-risk people they will not develop cancer). However, the markers with high sensitivity and accuracy would be key in early cancer prevention or detection. Moreover, the optimal cancer biomarker is one that can be easily accessed from the body (i.e. blood, urine, tissue from biopsy).

Molecular cancer biomarkers
Other Examples of Biomarkers:
 * Tumor Suppressors Lost in Cancer
 * Examples: BRCA1, BRCA2
 * RNA
 * Examples: mRNA, microRNA
 * Proteins found in body fluids or tissue.
 * Examples: Prostate-specific antigen, and CA-125

Imaging techniques

 * Examples: MRI, Mammography
 * Imaging disease biomarkers by magnetic resonance imaging (MRI)

MRI has the advantages of having very high spatial resolution and is very adept at morphological imaging and functional imaging. MRI does have several disadvantages though. First, MRI has a sensitivity of around 10−3 mol/L to 10−5 mol/L which, compared to other types of imaging, can be very limiting. This problem stems from the fact that the difference between atoms in the high energy state and the low energy state is very small. For example, at 1.5 tesla, a typical field strength for clinical MRI, the difference between high and low energy states is approximately 9 molecules per 2 million. Improvements to increase MR sensitivity include increasing magnetic field strength, and hyperpolarization via optical pumping or dynamic nuclear polarization. There are also a variety of signal amplification schemes based on chemical exchange that increase sensitivity.

To achieve molecular imaging of disease biomarkers using MRI, targeted MRI contrast agents with high specificity and high relaxivity (sensitivity) are required. To date, many studies have been devoted to developing targeted-MRI contrast agents to achieve molecular imaging by MRI. Commonly, peptides, antibodies, or small ligands, and small protein domains, such as HER-2 affibodies, have been applied to achieve targeting. To enhance the sensitivity of the contrast agents, these targeting moieties are usually linked to high payload MRI contrast agents or MRI contrast agents with high relaxivities.