In biomedical contexts, a biomarker, or biological marker, is a measurable indicator of some biological state or condition. Biomarkers are often measured and evaluated using blood, urine, or soft tissues to examine normal biological processes, pathogenic processes, or pharmacologic responses to a therapeutic intervention. Biomarkers are used in many scientific fields.
Medicine
Biomarkers used in the medical field, are a part of a relatively new clinical toolset categorized by their clinical applications. The four main classes are molecular, physiologic, histologic and radiographic biomarkers. All four types of biomarkers have a clinical role in narrowing or guiding treatment decisions and follow a sub-categorization of being either predictive, prognostic, or diagnostic.
Predictive
Predictive molecular, cellular, or imaging biomarkers that pass validation can serve as a method of predicting clinical outcomes. Predictive biomarkers are used to help optimize ideal treatments, and often indicate the likelihood of benefiting from a specific therapy. For example, molecular biomarkers situated at the interface of pathology-specific molecular process architecture and drug mechanism of action promise capturing aspects allowing assessment of an individual treatment response. This offers a dual approach to both seeing trends in retrospective studies and using biomarkers to predict outcomes. For example, in metastatic colorectal cancer predictive biomarkers can serve as a way of evaluating and improving patient survival rates and in the individual case by case scenario, they can serve as a way of sparing patients from needless toxicity that arises from cancer treatment plans.
Common examples of predictive biomarkers are genes such as ER, PR and HER2/neu in breast cancer, BCR-ABL fusion protein in chronic myeloid leukaemia, c-KIT mutations in GIST tumours and EGFR1 mutations in NSCLC.
Diagnostic
Diagnostic biomarkers that meet a burden of proof can serve a role in narrowing down diagnosis. This can lead to diagnosis that are significantly more specific to individual patients. A biomarker can be a traceable 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.
One example of a commonly used biomarker in medicine is prostate-specific antigen (PSA). This marker can be measured as a proxy of prostate size with rapid changes potentially indicating cancer. The most extreme case would be to detect mutant proteins as cancer specific biomarkers through selected reaction monitoring (SRM), since mutant proteins can only come from an existing tumor, thus providing ultimately the best specificity for medical purposes.
Another example is KRAS, an oncogene that encodes a GTPase involved in several signal transduction pathways. Biomarkers for precision oncology are typically utilized in the molecular diagnostics of chronic myeloid leukemia, colon, breast, and lung cancer, and in melanoma.
Digital
Digital biomarkers are a novel emerging field of biomarkers, mostly collected by smart biosensors. So far, digital biomarkers have been focusing on monitoring vital parameters such as accelerometer data and heartrate but also speech. Novel non-invasive, molecular digital biomarkers are increasingly available recorded by e.g. on-skin sweat analysis (internet-enabled Sudorology), which can be seen as next-generation digital biomarkers. Digital biomarkers can be easily shared with the responsible physician, and novel diagnostics approaches can be developed using artificial intelligence.
Digital biomarkers are currently being used in conjugation with artificial intelligence (A.I.) in order to recognize symptoms for mild cognitive impairment (MCI). One major current use of digital biomarkers involves keeping track of regular brain activity. Specific neural indicators can be measured by devices to evaluate patients for any neuro abnormalities. The data collected can determine the patients disease probability or condition. While patients carryout everyday tasks (IADL), computers are using machine learning to observe and detect any deviation from normal behavior. These markers are used as signs or indicators of cognitive decline.