Uses of biomarkers in cancer medicine 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.
Diagnosis 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 can 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. For example, people with tumors have high levels of circulating tumor DNA (ctDNA) due to tumor cells that have gone through apoptosis. This tumor marker can be detected in the blood, saliva, or urine.
Prognosis and treatment predictions Another use of biomarkers in cancer medicine is for disease
prognosis, which take place after an individual has been diagnosed with cancer. Here biomarkers can be useful in determining the aggressiveness of an identified cancer as well as its likelihood of responding to a given treatment. In part, this is because tumors exhibiting particular biomarkers may be responsive to treatments tied to that biomarker's expression or presence. Examples of such prognostic biomarkers include elevated levels of
metallopeptidase inhibitor 1 (TIMP1), a marker associated with more aggressive forms of
multiple myeloma, elevated
estrogen receptor (ER) and/or
progesterone receptor (PR) expression, markers associated with better overall survival in patients with breast cancer;
HER2/neu gene amplification, a marker indicating a breast cancer will likely respond to
trastuzumab treatment; a mutation in exon 11 of the
proto-oncogene c-KIT, a marker indicating a
gastrointestinal stromal tumor (GIST) will likely respond to
imatinib treatment; and mutations in the
tyrosine kinase domain of
EGFR1, a marker indicating a patient's
non-small-cell lung carcinoma (NSCLC) will likely respond to
gefitinib or
erlotinib treatment.
Pharmacodynamics and pharmacokinetics Cancer biomarkers can also be used to determine the most effective treatment regime for a particular person's cancer. Because of differences in each person's genetic makeup, some people metabolize or change the chemical structure of drugs differently. In some cases, decreased metabolism of certain drugs can create dangerous conditions in which high levels of the drug accumulate in the body. As such, drug dosing decisions in particular cancer treatments can benefit from screening for such biomarkers. An example is the gene encoding the enzyme
thiopurine methyl-transferase (TPMPT). Individuals with mutations in the TPMT gene are unable to metabolize large amounts of the
leukemia drug,
mercaptopurine, which potentially causes a fatal drop in
white blood count for such patients. Patients with TPMT mutations are thus recommended to be given a lower dose of mercaptopurine for safety considerations.
Monitoring treatment response Cancer biomarkers have also shown utility in monitoring how well a treatment is working over time. Much research is going into this particular area, since successful biomarkers have the potential of providing significant cost reduction in patient care, as the current image-based tests such as CT and MRI for monitoring tumor status are highly costly. One notable biomarker garnering significant attention is the
protein biomarker
S100-beta in monitoring the response of
melanoma. In such melanomas,
melanocytes, the cells that make pigment in our skin, produce the protein S100-beta in high concentrations dependent on the number of cancer cells. Response to treatment is thus associated with reduced levels of S100-beta in the blood of such individuals. Similarly, additional laboratory research has shown that tumor cells undergoing
apoptosis can release cellular components such as
cytochrome c,
nucleosomes, cleaved
cytokeratin-18, and
E-cadherin. Studies have found that these macromolecules and others can be found in circulation during cancer therapy, providing a potential source of clinical metrics for monitoring treatment.
Uses of biomarkers in cancer research Developing drug targets In addition to their use in cancer medicine, biomarkers are often used throughout the cancer drug discovery process. For instance, in the 1960s, researchers discovered the majority of patients with
chronic myelogenous leukemia possessed a particular genetic abnormality on
chromosomes 9 and 22 dubbed the
Philadelphia chromosome. When these two chromosomes combine they create a cancer-causing gene known as
BCR-ABL. In such patients, this gene acts as the principle initial point in all of the physiological manifestations of the leukemia. For many years, the BCR-ABL was simply used as a biomarker to stratify a certain subtype of leukemia. However, drug developers were eventually able to develop
imatinib, a powerful drug that effectively inhibited this protein and significantly decreased production of cells containing the Philadelphia chromosome.
Surrogate endpoints Another promising area of biomarker application is in the area of
surrogate endpoints. In this application, biomarkers act as stand-ins for the effects of a drug on cancer progression and survival. Ideally, the use of validated biomarkers would prevent patients from having to undergo tumor
biopsies and lengthy
clinical trials to determine if a new drug worked. In the current standard of care, the metric for determining a drug's effectiveness is to check if it has decreased cancer progression in humans and ultimately whether it prolongs survival. However, successful biomarker surrogates could save substantial time, effort, and money if failing drugs could be eliminated from the development pipeline before being brought to clinical trials. Some ideal characteristics of surrogate endpoint biomarkers include: • Biomarker should be involved in process that causes the cancer • Changes in biomarker should correlate with changes in the disease • Levels of biomarkers should be high enough that they can be measured easily and reliably • Levels or presence of biomarker should readily distinguish between normal, cancerous, and precancerous tissue • Effective treatment of the cancer should change the level of the biomarker • Level of the biomarker should not change spontaneously or in response to other factors not related to the successful treatment of the cancer Two areas in particular that are receiving attention as surrogate markers include
circulating tumor cells (CTCs) and circulating
miRNAs. Both these markers are associated with the number of
tumor cells present in the blood, and as such, are hoped to provide a surrogate for tumor progression and
metastasis. However, significant barriers to their adoption include the difficulty of enriching, identifying, and measuring CTC and miRNA levels in blood. New technologies and research are likely necessary for their translation into clinical care. ==Types of cancer biomarkers==