Virginia Bio Presents 2015 Virginia State Science and Engineering Fair Awards for Biotechnology
Wednesday, April 15, 2015
Virginia Bio, in conjunction with the Virginia Bio Foundation, presented the Mark Licata Award for Biotechnology awards at the 2015 Virginia State Science and Engineering Fair on Saturday, March 28, 2015, at Virginia Military Institute in Lexington. The volunteer judges studied the abstracts prior to their arrival at the Fair and then voted on the top projects to interview one-on-one at the event. The first place winners also went on to win the Governor’s Award and Grand Prize at the fair.
In 2014 Virginia Bio and the Virginia Bioscience Foundation were honored to rename the Virginia Bio Award for Biotechnology to the Mark Licata Award for Biotechnology after the sudden passing of Mark.
"Mark Licata derived tremendous enjoyment from sparking the passion of scientific understanding in others,” said Ron Gunn, Chief Operating Officer of kaléo and long-time friend of Mark and his family. "His tireless desire to solve complex engineering challenges led to as many as 130 biomedical patents and the development and approval of multiple life-enhancing and life-saving medical products including a recently FDA approved antidote for opioid overdose.”
“Mark was always one of the first to sign up as a volunteer judge for Virginia Bio at the Virginia State Science Fair,” said Mark Herzog, former executive director of Virginia Bio and now a member of the team at kaléo. “Naming this award for Mark is a wonderful tribute. Not only to his contributions to science, but it also really captures his love of teaching and mentoring those around him.”
After talking with each of the student entrants, the judges made their final selections.
"It was hard to choose among so many outstanding projects," said Jeffrey Gallagher, Virginia Bio CEO. “The judges were extremely impressed by the caliber of the work.”
The awards presented included:
First Place: Matthew and Michael Retchin
Project Title: Identification and Characterization of HCC-Suppressing MicroRNA-1202 using DeepMine, a Novel Deep Learning Algorithm
Abstract: Hepatocellular carcinoma (HCC) has virtually no treatment options in late stages, and has the shortest survival time of any cancer. MicroRNA-1202 (miR-1202) is downregulated in HCC-recurring and chronic HCV-infected sera, suggesting a potential tumor suppressing role in HCC. A novel deep learning algorithm called DeepMine using a deep belief network was developed for miRNA target prediction. DeepMine predicted putative targets of miR-1202; of predicted targets, staphylococcal nuclease domain containing protein 1 (SND1) was identified as highly overexpressed in HCC. SND1 levels were evaluated in miR-1202 transfected HCC cell lines, and proliferation and apoptosis were analyzed. DeepMine identified SND1 as a possible downstream target of miR-1202, and predicted the 3'UTR as a potential binding site. MiR-1202 transfected cells showed significant SND1 knockdown. Stable clones also showed reduced cell viability and increased apoptotic pathway activity. Additionally, DeepMine outperformed currently available miRNA target prediction algorithms in standard metrics. Conclusion: A novel, antagonistic pathway relating miR-1202 with SND1 gene expression in HCC was characterized. MiR-1202 was identified as a potential biomarker of HCC and a target for anti-cancer therapies. In addition, DeepMine was established as the most accurate human miRNA target prediction software. DeepMine is freely available at http://deepmine.org/.
Second Place: David Lu
Project Title: Computer-Aided Drug Discovery of Sortase A Inhibitors to Combat MRSA Infections
Abstract: Methicillin resistant S. aureus (MRSA) is one of the most deadly strains of S. aureus due to its resistance to many different antibiotics, leading to 11,285 deaths in America every year. One promising approach for treating MRSA infections is to strip the bacteria of their surface proteins, which frequently function as virulence factors and facilitate bacterial adhesion during infection. S. aureus mutants lacking the srtA gene fail to anchor and display some surface proteins and are impaired in their ability to cause infections in several animal models of the disease. The purpose of this experiment was to identify potent small-molecule inhibitors for Sortase A. Virtual screening is a computational technique used in drug discovery to dock libraries of small molecules into the active site of the drug target in order to identify compounds which are most likely to inhibit an enzyme's activity. Through a FRET-based enzyme activity assay, a compound identified utilizing virtual screening displayed potent Sortase A inhibitory activity in vitro. Compound J had an IC50 at 1mM against Sortase A activity. Through kinetic studies, it was determined that Compound J irreversibly and covalently binds to Sortase A's active site. This compound forms the basis for further drug development which could potentially lead to a new therapy against multidrug-resistant bacteria infections.
Third Place: Eryney Marrogi
Project Title: An Epigenetic Approach to Osteosarcoma
Abstract: Osteosarcoma is a rare and aggressive form of bone cancer in children, presenting as an extremely painful mass in long bones around the knee joint with potential metastasis to lungs and brain. Localized disease carries a 5-year survival of 75%, declining to 25% in advanced stages. Previous studies have indicated that the c-Fos gene plays a role in osteosarcoma; specifically, the viral homologue, v-Fos, can induce tumor formation when injected into rodents in vivo and can transform osteogenic cells in tissues undergoing bone formatio. The c-Fos gene is a major component of the AP-1 transcription factor complex binding to AP-l sites in the regulatory regions of specific target genes. Further, data has shown that a knockout mutation of the c-Fos gene in the human U-2 OS osteoscaroma cell line significant apoptosis. This study extends these results to clinical human tissue samples. Immunohistochemistry staining with anti-c-Fos antibody on an 85 tumor osteosarcoma tissue microarray show an over-expression of c-Fos protein in all tumors of chondroblastic differentiation. Other tumor subtypes show no or minimal (+1) expression, suggesting that c-Fos overexpression may be ideal for diagnosis and targeted therapy of the chondroblastic osteosarcoma. A molecule, T-5224, used in prior studies as an arthritis treatment, acts as an inhibitor for c-Fos, and could be a potential treatment for osteosarcoma by blocking AP-1 binding sites.
Project Title: A Diagnostic Blood Test for Parkinson’s Identification of miRNA Biomarkers of Neuronal Exosomes.
Virginia Bio offers congratulations to all of the students for their outstanding projects and thanks the following award judges:
Jeff Gallagher, Virginia Bio
Tom Hoerner, Merck
Debbie Winetzky, BIO-CAT