Biomarkers 101: Reporting From The AACR Scientist Survivor Program
AACR Scientist Survivor Program
Recently I returned from the 2017 American Association for Cancer Research (AACR) Annual Meeting which was held in Washington, DC. The AACR is the oldest and largest professional association related to cancer research in the world, and its mission is to prevent and cure cancer through research, education, communication, and collaboration. I attended this year’s meeting as part of the Scientist-Survivor Program (SSP), which provides an opportunity for patient advocates to learn about cancer research and to network with scientists, doctors, health professionals, and other advocates. I’ve attended two previous AACR meetings as a patient advocate. This year my role was Advocate Mentor.
Patient advocates who attend the meeting are required to prepare and present a poster explaining their advocacy work during the meeting’s Scientific Poster session. Patient advocates are also divided into working groups that consist of 4-5 advocates, a scientific advisor, and a mentor advocate. Advocates collaborate with their pre-assigned working group to answer a scientific question that was assigned to them. They gather information to answer their question by attending the meeting and interacting with researchers. The group presents what they learned during the SSP’s closing dinner. My role as an advocate mentor was to guide my group through the meeting’s agenda and to make sure they worked together on the question that our group was exploring.
This year my group’s question focused on biomarkers. I learned a lot about biomarkers during this process and thought that this would be a great place to share some of what I learned. First we had to define biomarkers. Well that’s a loaded question. The World Health Organization defines a biomarker as “any substance, structure, or process that can be measured in the body or its products and influence or predict the incidence of outcome or disease.” Biomarkers can range from basic markers such as blood pressure, pulse, and temperature, to cancer biomarkers such as HER2 that require special genetic testing. In this blog I will focus on cancer biomarkers.
Types Of Cancer Biomarkers
Many times an oncologist will order tests from a lab to detect biomarkers. These tests are called molecular diagnostics. Biomarkers provide information about an individual patient’s cancer. Biomarkers are grouped based on how they are used. Cancer biomarkers can be diagnostic, predictive or prognostic. Biomarkers are becoming major players in the era of Precision Medicine since they can help a treating physician make a personalized prognosis and treatment plan.
- Diagnostic biomarkers are used to confirm a diagnosis. Developing and validating diagnostic biomarkers for different types of cancer will help lead to early detection. When cancer is diagnosed at an earlier stage it is usually easier to treat.
- Prostate cancer diagnosis and management have been guided by the amount of prostate specific antigen (PSA) in the serum. This biomarker has come into question because of its limitation. PSA’s specificity and sensitivity ranges from 20 to 40% and 70 to 90% respectively. One of the major reasons for such poor specificity is the fact non-cancerous conditions can also cause an elevated PSA. Many advances are being made in developing new prostate cancer biomarkers that are more specific and sensitive.
- In myeloma the presence of an elevated m-spike may be considered a diagnostic biomarker. Some diagnostic biomarkers can be used alone while other diagnostic biomarkers need to be used in combination with other testing. An elevated m-spike alone will not confirm a diagnosis of myeloma since other health conditions may cause an elevated m-spike. A bone marrow biopsy that reveals malignant myeloma cells in the marrow is a biomarker that will confirm the diagnosis of myeloma.
- Prognostic biomarkers help indicate how cancer may progress in an individual who is already diagnosed.
- The GEP- 70 (Gene Expression Profile- 70 genes) is a diagnostic test used in myeloma to determine risk-stratification. The 70-gene Prognostic Risk Score quantifies the expression of 70 genes commonly altered in Myeloma. GEP-70 assesses risk of disease relapse and survival outcomes by analyzing the genes that are expressed in an individual.
- The Myeloma FISH (Fluorescence in Situ Hybridization) testing panel can also be used as a prognostic biomarker. FISH testing provides a mutational analysis.
- M-Smart (from Mayo Clinic) uses results from FISH testing to group patients into standard, intermediate, or high risk based on chromosomal abnormalities.
- A predictive biomarker helps determine which patients are most likely to benefit from a specific treatment. These predictive biomarkers for precision oncology are used mainly in leukemia, colon, breast and lung cancer, and recently in melanoma.
- We have all seen Bristol Myers Squibb’s commercial for Opdivo (nivolumab). Opdivo is an anti-PD-1 drug used in advanced Non-Small Cell Lung Cancer (NSCLC) patients. Several studies have shown that patients with NSCLCs that express PD-L1 have a greater probability of receiving clinical benefit from Opdivo.
- In breast cancer, HER2 overexpression predicts for response to Herceptin (trastuzumab). Other drugs that target HER2 include Perjeta (pertuzumab) and Kadcycla (trastuzumab emtansine). Per the National Cancer Institute, “Checking to see if a cancer is HER2 positive may help plan treatment, which may include drugs that kill HER2 positive cancer cells. Cancers that may be HER2 positive include breast, bladder, pancreatic, ovarian, and stomach cancers.”
- EGFR expression in colorectal cancer usually indicates treatment with Erbitux (cetuximab).
- In myeloma, predictive biomarkers are being developed. Gene expression profiling places myeloma patients into one of seven different molecular subgroups which behave different clinically. One of the subgroups identified by gene expression profiling is the MS molecular subgroup. This group is more sensitive to proteasome inhibitors than immunomodulatory agents. Therefore patients in the MS subgroup could consider treatment with Velcade, Carfilzomib or Ninlaro.
Personalized oncology is on the horizon. Molecular diagnostics is a key tool leading to the personalization of oncology treatment. The one-size-fits-all approach to cancer treatment is being replaced by targeted therapies aimed at specific biomarkers. Understanding the relationship between measurable biological processes, aka biomarkers, and clinical outcomes is vital to expanding our arsenal of treatments for all diseases. Scientific analysis of big data is helping to identify new biomarkers. Once biomarkers are identified they need to be validated and companion diagnostics need to be approved. But that is a story for another day.
*From left to right, advocates Caleb Egwuenu, Candace Henley, Denise Barlow, Penny Blaisdell, and Meisha Brown.
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