The Next Innovation? How Biologics May Act as Biomarkers in Determining Risk for Cancer
Imagine if there were a simple blood test for cancer. What if that test could determine the severity of the disease and predict patient outcomes? These musings have challenged researchers in the field of cancer immunomics for decades. Since the 1970’s, scientists have studied cancer biomarkers, hoping to design diagnostic or prognostic tests based on serum levels of the proteins secreted during the disease process. There are fundamental problems with the existing tests that limit their clinical applicability, but biologic antibodies may provide a solution. If scientists can design biologic antibodies to act as biomarkers for cancer, the development of diagnostic and prognostic blood tests may finally be within reach.
Antigens and Autoantibodies: Promising but Unreliable Biomarkers
Biomarkers are proteins that are secreted in response to a disease, so when scientists detect them in a patient’s blood, they can use the information for diagnosis or to predict the patient’s outcome. Many cancers are associated with the release of certain antigenic proteins, which researchers originally hoped could serve as reliable biomarkers. However, not all antigens are tumor-specific. For instance, prostate-specific antigen (PSA) was initially identified as a promising biomarker for malignant prostate tumors, but it soon became clear that serum levels of PSA also rise in response to inflammation, trauma and benign proliferation. As a result, the prostate cancer diagnostic test that measures PSA levels has a false positive rate as high as eighty percent.1
Tests for antigens also show limited sensitivity, so they can’t be used for cancer prognosis. Even when a test for PSA does correctly identify a patient with prostate cancer, the test doesn’t provide reliable information about the extent of the disease or the patient’s chances for survival.2 Without this information, it’s a challenge for doctors to come up with a treatment strategy. This means that they must continue to rely on more invasive prognostic tests.
Because direct detection of antigens proved to be an unreliable way to detect cancer, some scientists hoped that the autoantibodies that the body produces in response to cancer-related antigens could serve as reliable biomarkers for cancer. Again, they ran into problems. For most forms of cancer, there is no single antibody that signals the presence of the disease. In order to reliably diagnose the disease or predict outcomes, scientists need to analyze the complex combination of autoantibodies in a patient’s blood.3 To complicate matters even more, a cancer-related autoantibody is not always produced, even when the disease is present. For instance, there are at least eight autoantibodies associated with colorectal cancer, but each antibody is present in less than forty percent of patients.4 Plus, there are so many different types of cancer to begin with that the task of designing comprehensive diagnostic and prognostic tests for all of them is enormous.
Could Biologic Antibodies Be the Solution?
Researchers may be able to overcome the limitations of cancer diagnostic and prognostic tests that rely on the detection of antigens and autoantibodies by designing biologic antibodies to act as biomarkers. In order to reduce the risk of false positive test results, scientists could design biologic antibodies that selectively target tumor-specific antigens. Instead of directly testing for non-tumor-specific antigens like PSA, a doctor could treat a patient with a tumor-specific biologic antibody that can be detected in the serum when it binds to its target. A simple, inexpensive blood test would then be able to determine whether the antibody (and therefore its antigen target) is present in the serum. Modern biologics software has the potential to enable scientists to design such antibodies for the first time. Because the software provides tools that allow scientists to analyze higher volumes of data and design better experiments, they may be able to design novel biologics that are more specific and selective than natural biomarkers. These biologic biomarkers would be more reliable for diagnosing cancer and predicting outcomes.
Still, researchers attempting to design biologic biomarkers are faced with the complexity of cancer itself. There are many different types of cancer, and in many cases, different mutations can lead to the same type. In the past, antibody discovery for cancer-associated antigens was hindered by this complexity5, but the latest technology may provide the solution. As scientists are able to process more antibody sequence data more efficiently, it becomes easier to identify potential candidates. High-level design tools can also be used to design biologic antibodies that can detect multiple forms of cancer, rather than just one. That is, of course, the ultimate goal—finding a biomarker for any and all types of cancer—and today’s scientists just might be able to use technology to make this dream a reality.
The BIOVIA Biologics solution provides the discovery tools that your life sciences firm needs in order to design better quality biotherapeutics. The software can improve research efficiency and speed time to market so that your novel biologics can reach the patients who need them as quickly as possible. Contact us today to learn more about the technology that will empower your lab to lead the way in revolutionizing cancer diagnostic and prognostic testing.
- “Autoantibody markers in the detection of cancer,” June 2006, http://www.sciencedirect.com/science/article/pii/S0925443906000548 ↩
- “Cancer immunomics: Using autoantibody signatures in the early detection of prostate cancer,” May-June 2006, http://www.sciencedirect.com/science/article/pii/S1078143905002826 ↩
- “Cancer immunomics: from serological proteome analysis to multiple affinity protein profiling,” June 2007, http://www.ncbi.nlm.nih.gov/pubmed/17804550 ↩
- “Targeting serum antibody for cancer diagnosis: a focus on colorectal cancer,” January 17, 2007, http://www.tandfonline.com/doi/abs/10.1517/14728220.127.116.11 ↩
- “Autoantibody recognition mechanisms of p53 epitopes,” June 2016, http://www.sciencedirect.com/science/article/pii/S0925443906000548 ↩