2021 Research Update

Overview

Despite the delays to our research program due to COVID-19, 2021 was a very good year for the OCI research program. Based upon publications over the past 10 years, ExpertScape (https://expertscape.com) classified Dr. McDonald “… in the top 1% of scholars writing about ovarian neoplasms.” The following is a summary of advancements in the various areas of research supported by OCI.

Diagnostic Test

We are continuing the development of our metabolic-based early-diagnostic blood test for ovarian cancer across 800 patient samples. Our current overall accuracy remains greater than 95% for the detection of early-stage serous papillary ovarian cancer (OC). Our most recent studies indicate that there are sub-types of this most abundant form of OC. One path we are currently exploring is the development of diagnostic profiles for each of these sub-groups separately, which we believe will generate even higher predictive accuracies. The future clinical scenario might be to first use the metabolic profiles of blood samples to classify patients into the appropriate sub-group and then run the diagnostic test designed to be most accurate for each individual sub-group.

We recently met with Lynn Durham, President and CEO of the Georgia CORE (Center for Oncology Research & Education- see: https://www.georgiacancerinfo.org/about-georgia-core.aspx) about setting up a network of physicians across the state of Georgia to prospectively evaluate the utility of our diagnostic test. Lynn was enthusiastic about such a collaboration and she is consulting with her Board to draft an implementation plan that could begin as soon as this coming spring.

Nanoparticle Drug Delivery System

We are submitting our pre-IND application to the FDA early next month (Feb) for Phase I human trials. This initial application describes our technology, our favorable toxicity and efficacy results from experimental animals, and our proposed procedures for trials in humans. FDA will respond by telling us in detail what if any, additional trials they may require before granting final approval. Based upon consultations with experts in the field (funded by the Georgia Research Alliance) of new drug approval procedures, we have been advised that the FDA will likely require us to demonstrate that scaled-up production of the particles is carried out in an approved manufacturing facility under strict GMP (“good manufacturing procedures”) conditions. In addition, we have been further advised that the FDA will likely require toxicity studies to be carried out in non-human primates prior to testing in humans. Both of these anticipated requirements will need to be outsourced and we are in the process of negotiating contracts with the appropriate companies to conduct these studies.

Personalized Cancer Medicine

We recently published the latest iteration of our drug prediction algorithms (https://escires.com/articles/JOR-4-111.pdf). These updated computational methods combine the best of previously developed machine-learning approaches and were shown to provide high accuracy in identifying optimal drug therapies for ovarian cancer patients. Our findings were the subject of several articles in the national and international press (e.g.https://healthitanalytics.com/news/machine-learning-predicts-cancer-treatment-response; https://healthitanalytics.com/features/top-opportunities-for-artificial-intelligence-to-improve-cancer-care).

Other Significant Research Breakthroughs

In December, we published the results of our pioneering research on changes in gene-gene interactions associated with the onset and progression of cancer (iScience, 2021; 24 (12): 103522). Our findings were again the topic of several articles published in the popular press (e.g., https://www.drugtargetreview.com/news/100256/researchers-investigate-gene-network-to-identify-cancer-driver-genes/).

Two other major papers were published over the last several months based on collaborative studies with other researchers at Georgia Tech. The first paper published in the high-profile journal Cancer Research (Housley et al. Cancer Exacerbates Chemotherapy-Induced Sensory Neuropathy. Cancer Res. https://doi.org/10.1158/0008-5472.CAN-19-2331) reports the first demonstration of a direct connection between cancer and the neurological system. The results have implications on how the negative side effects on the neural system may be mitigated.

Another paper published in Nature Scientific Reports (https://doi.org/10.1038/s41598-021-96862-y) describes a methodology for the isolation of metastasizing cancer cells from the ascites fluid of ovarian cancer patients. This methodology opens the possibility of isolating metastasizing cells for molecular analyses that will generate data applicable to our personalized medicine algorithms (see above) allowing for the prediction of optimal chemotherapies for individual patients.

A third paper is soon to be published in Cancer Research (Lee et al. Effects of inherited molecular differences on cancer survival on cancer survival disparities: a pan-cancer analysis (in press) explores the contribution of inherited differences in gene profiles on cancer survival.

Finally, Dr. McDonald was invited to contribute a review paper on our machine-learning approach to personalized cancer therapy (McDonald, J. The ability to accurately predict optimal drug therapies for cancer patients is rapidly approaching), which will be published in February in the journal Health Europa.