Understanding Biomarkers

Personalized Treatment for Ovarian Cancer

The promise of personalized medicine lies in matching the right drug with the right patient. As we learn more about the genetic variations of different diseases and how drugs work to combat them, the reality of personalized medicine comes more clearly into view. It has been argued that cancer is the most complex disease we face and that understanding its genetic underpinnings can help us defeat it with targeted therapeutics. In fact, doctors are currently using biomarkers to make treatment choices for patients with breast, colon and lung cancer. A biomarker is a molecular or genetic characteristic of a tumor that has implications for treatment decisions. For example, breast cancers that express high levels of a biomarker called Her2 are likely to respond to a drug called Herceptin and in colon cancer, a mutation in the kras gene is predictive of lack of response to the drug Cetuximab. Currently, personalized treatment approaches based on biomarkers are not commonly used for ovarian cancer patients.

Clearity wants to change that reality. The Clearity Foundation’s mission is to transform ovarian cancer treatment by providing access to a molecular profiling service that measures biomarkers and provides information that enables the matching of drugs to individual disease. Hillary Theakston, executive director of the Clearity Foundation, explained that, “Clearity has developed something new and unique using existing diagnostic technologies and published scientific literature.” Clearity has created a knowledge base for using biomarkers in ovarian cancer. Theakston described Clearity’s new research and findings on ovarian cancer biomarkers, “The technology has been there; the literature exists, but before Laura Shawver founded Clearity, no one was using it to help ovarian cancer patients.” Clearity has surveyed the medical literature to identify biomarkers that can be used by ovarian cancer patients and physicians to help inform treatment choices.

Biomarkers in Ovarian Cancer

Seventy-five to eighty percent of advanced stage ovarian cancers recur after the patient’s initial treatment with carboplatin/taxane. Their tumors can be even less responsive to this treatment the second time around; fortunately, many different treatment options are available to patients who recur. Unfortunately, there is no standard-of-care to help select from the many available treatment options, leaving patients with trial-and-error selection. Few doctors and patients are aware that there are molecular markers or biomarkers to help rationally select the best treatment options for patients who recur.

Through a microscope, ovarian tumors may look similar, but on the molecular level, each tumor has it’s own set of molecular weapons and frailties. These molecular strengths and weaknesses can be tested to provide a molecular profile or “tumor blueprint”. The “tumor blueprint” for each patient will determine which cancer drugs are most likely to be effective. To educate patients and physicians on this individualized approach, the Clearity Foundation initiated a comprehensive study of the evidence supporting the use of molecular profiling tools to make better treatment decisions for recurrent and refractory ovarian cancer.

Dr. Deb Zajchowski, the scientific director for the Clearity Foundation, led the study to identify and evaluate the evidence in the medical literature for how certain features in the “tumor blueprint” may predict response to specific chemotherapy drugs. This study was funded in part by a grant from California Ovarian Cancer Awareness Program (COCAP). All medical literature is catalogued in a gargantuan, publicly available database called Pubmed. Pubmed is maintained by the National Library of Medicine and contains nearly 12 million scientific and medical articles. Dr. Zajchowski and other researchers at Clearity searched Pubmed using key words that would find all articles related to biomarkers and their correlations with chemotherapeutic drugs. Using key word searches, she and her team identified around 5000 research articles. After reviewing the articles for relevancy, 585 research articles were selected as providing information on the relationship of various biomarkers with response to a given chemotherapeutic (literature references can be accessed for each biomarker by clicking through the Drugs and Biomarkers table). The team then read the abstracts, or results summaries, of every selected article to be able to classify the data. Finally, the results were tallied.

Twenty-six biomarkers were found to correlate with either cancer sensitivity or resistance to chemotherapeutics in 7 drug classes (click here for a complete list on the Drugs and Biomarkers table). Dr Zajchowski used several criteria to establish that a biomarker correlates with tumor response including: that the results came from clinical research studies, that at least two research articles found a specific correlation, and that most studies agreed on the correlation. This evidence supports the use of molecular profiling in making treatment decisions. The collected and consolidated evidence can be found on several pages of Clearity’s website, in the Drugs and Biomarkers pages of the physician section, which is directed towards increasing awareness of doctors and patients of the opportunity to rationally select treatments for recurrent and refractory ovarian cancer.

Using Biomarkers to Make Treatment Choices

The scientific team at Clearity looked in the literature for evidence that the drugs commonly used in ovarian cancer treatment had biomarkers that would indicate whether or not the drug was a good match for an individual patient. For example, when the team searched for biomarkers associated the chemotherapy Gemcitabine, they found 39 research articles from studies in pancreatic, lung and ovarian cancer. From these articles, five biomarkers were identified that correlate with Gemcitabine response and therefore suggest that a patient’s tumor is likely to be sensitive (3 markers) or resistant (2 markers) to this drug. The sensitivity markers were ENT1, DCK and HuR. If a patient has high levels of any of these markers, she is more likely to respond to Gemcitabine. Nine out of ten research articles provide evidence for ENT1 as a sensitivity marker, three of five for DCK, and two of two for HuR.

The resistance markers identified in the literature were RRM1 and RRM2. The literature results suggest that if a patient has high levels of either of these markers, her tumor is more likely to be resistant to Gemcitabine. Ten of fifteen articles that looked at RRM1 and tumor response to Gemcitabine found this marker to be predictive of resistance or lack of response. Five of seven research articles found RRM2 to be predictive of lack of response. Information about the biology of Gemcitabine and its five predictive biomarkers can be found by clicking on Drugs and Biomarkers table.

Looking at biomarkers for all of the drugs being considered for treatment, patients and their clinical teams, can identify the best individual therapeutic options. Her tumor biomarkers can help eliminate drugs her tumor is less likely to respond to and choose among drugs that are more likely to be effective. An illustration of how biomarkers are associated with drug sensitivity or resistance can be accessed by clicking here.