EFFROC Research Funding

Perception-Based Detection of an Ovarian Cancer Disease Fingerprint

Daniel Heller, PhD, Memorial Sloan Kettering Cancer Center

2023 Collaborative Research Development Grant

Although serum biomarker measurements are widely used for ovarian cancer diagnosis and several other diseases, they provide low sensitivity and specificity, particularly around screening. Dr. Heller’s team believes that differentiation of diseased biofluids from normal biofluids could be achieved by detection of a “disease fingerprint,” which may be possible through collection of large data sets of molecular binding interactions to a set of sensors. In order to accomplish this, the team is building sensor arrays comprising modified carbon nanotubes (called organic color centers, OCCs). In preliminary experiments, the team found that a library of their nanosensors, using machine learning algorithms, reliably identified late stage ovarian cancer significantly better than the established, FDA-approved methods. Dr. Heller’s team proposes to further develop and validate sensor platform to enable accurate screening of ovarian cancer.

Learn more about Dr. Heller’s research project.

Targeting Apoptotic Vulnerabilities in Ovarian Cancer

Kristopher Sarosiek, PhD, Harvard T.H. Chan School of Public Health

2023 Collaborative Research Development Grant

In order to effectively treat and ultimately cure aggressive ovarian cancers, therapies must strongly induce cancer cell death. Existing therapies like carboplatin and paclitaxel are highly effective by damaging key components within cancer cells and can cure some patients. However, most patients become resistant to these therapies. Recently, medicines have been developed to enhance the ability of standard chemotherapies to activate tumor cell death — potentially providing an opportunity to increase cure rates in many cancers, including ovarian. By combining standard therapies with cell death-promoting BH3 mimetics — medicines that inhibit pro-survival proteins that keep cancer cells alive — clinicians may be able to extend remissions or increase cure rates by delaying or preventing development of treatment resistance in tumor cells. Importantly, BH3 mimetics have already been approved by the FDA for use in some cancers, with positive results observed even in patients treated previously by multiple other therapies. The goal of Dr. Sarosiek’s team is to understand how to best use these new, highly-effective drugs to improve treatment outcomes for patients with ovarian cancers.

Learn more about Dr. Sarosiek’s research project.

Inferring Mutational Processes and Patient Stratification From Standard-of-Care Clinical Imaging

Sohrab Shah, PhD, Memorial Sloan Kettering Cancer Center

2022 Collaborative Research Development Grant

Patients with ovarian cancer can be categorized into different groups based on changes in their tumor genomes, and these subgroups hold differences in response to therapy and overall survival. Researchers have found that tumors defective in their ability to repair DNA are more susceptible to treatment and patients tend to fare better. In contrast, tumors with an intact DNA repair system, but more complex rearrangements of their genomes, are better able to withstand chemotherapy — and as a result these patients have worse outcome. This stratification is based on genome sequencing. Genome sequencing is not yet the standard of care at every health care institution, and it is still relatively costly. Dr. Shah’s team aims to use data created during routine clinical care, such as histopathological (H&E) slides of tumor tissue, computed tomography (CT) scans and clinical information, to improve the prediction of patient outcome.

Learn more about Dr. Shah’s research project.