The research update below was reported by our Chief Research Officer, Dr. John McDonald.

OCI Progress Report 2016-2017

Thanks for this opportunity to summarize our progress over the past year (2016-2017). Our research focuses on both improved diagnostics and therapeutics. In addition, our individual research projects fall into additional sub-categories: those that are close to clinical application and those that are more basic, i.e., exploring noel lines of investigation that I believe have significant future potential.

 

Diagnostics

            As many of you know, the centerpiece of our diagnostic efforts is our metabolomics/machine-learning based assay for early ovarian cancer diagnosis. Our initial findings reporting the 100% accuracy of our test over 96 patients was published in Nature Scientific Reports in 2015 (https://www.nature.com/articles/srep16351). This article remains one of the most highly accessed of all papers of a similar age in all scientific journals (99th percentile; https://www.nature.com/articles/srep16351/metrics). While we have had a number of initial “feelers” from a number of diagnostic companies, they all want to see validation in a much larger number of women before making any commercial commitments. My goal is to validate the test in 1000 patient samples. Thus far, I have identified about 500 samples from various sources throughout the US and CANADA that we can acquire. I am currently negotiating a collaborative arrangement with the national databank of Denmark (the largest tissue and documented depository in the world) to acquire additional samples. To support these efforts, we have submitted a large grant proposal to the NIH “Cancer Moon Shot” program which is still pending. This program was initiated in the final days of the Obama administration but its current funding is in some jeopardy. We are also applying to Tina’s Wish Foundation to acquire funds to support at least initiating our proposed extended analysis.

            On a more basic research level, we have initiated collaborative studies with a new research faculty member at GA Tech, Dr. Fatih Sariolgu (https://www.ece.gatech.edu/faculty-staff-directory/a-fatih-sarioglu), who is working on a novel device to detect circulating cancer cells in blood (http://www.nature.com/nmeth/journal/v12/n7/abs/nmeth.3404.html). I believe this methodology has the potential to complement our metabolic diagnostic test and additionally give us a way to non-invasively conduct genomic profiles of patient tumors that will compliment our personalized therapy program (see below).

 

Therapeutics

            A major achievement for us over the past year has been the development of a nanoparticle system that is able to target therapeutic RNAs specifically to tumors. The results of our initial studies, conducted in a mouse model of ovarian cancer, were published last year in Nature scientific Reports (https://www.nature.com/articles/srep36518) and have received significant notice in the press (e.g., see: http://www.genegnews.com/gen-news-highlights/rnai-chemo-tag-team-slams-ovarian-cancer/81253406). We are most interested in moving this technology into early stage human trials. Shortly after publication of our paper, we were invited by NIH National Characterization Laboratory to submit a proposal to them to conduct additional tests on our nanoparticles that are pre-requisite to FDA approval to conduct human trials. Conducting these tests is a very expensive enterprise (app. $1 MIL) and if our proposal is approved, the NCL will conduct these tests for free. We have just submitted the requested proposal to NCL but we are also pursuing other possible sources of funding (Georgia Research Alliance, etc.) to move this technology into human trials ASAP. We are also trying to schedule a meeting with FDA in order to get feedback from them directly on precisely what they require before we can move forward to testing our methodology in OC patients who have failed all existing therapies.

 

            We are also moving forward with our personalized therapy algorithms that employ machine learning methods to predict optimal drug therapies from the personalized molecular profiles of individual OC patients. We have submitted our initial paper, again to Nature, and we are awaiting a decision. We also have two additional papers currently under review in major journals. One is on the importance of chromosomal aberrations in cancer and another demonstrates that many significant changes occur on the protein level mediated by small regulatory RNAs that are not detectable in the currently employed DNA sequencing and RNA profiles used by molecular diagnostic companies like Foundation One, etc..  

 

            Finally, I am very excited about our recent finding that at least one so called “cancer driver mutation” (i.e., genetic changes that have been identified as causing cancers) is in fact, being carried by normal healthy individuals (we discovered this by analyzing DNA sequencing data from a recent world wide sequencing study conducted by NIH). This finding implies that there is some mechanism that “suppresses” the action of cancer causing mutations in healthy individuals and that this mechanism somehow breaks down in people who develop cancer. We are interested in studying the basis of this suppression mechanism because we think it could lead to a novel and possibly more effective way to treat cancers.

 

In summary, we had a good year on the research front. We are working to move our past discoveries into clinical practice and we have uncovered a number of novel lines of investigation that I think will reap benefits in the future. With your continued support, we hope to continue our progress over the next year.

 

                                                                        Yours,

                                                                        John F. McDonald

                                                                        Chief Scientific Officer

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