Dr. Peter Rogan is presenting our laboratory’s recent F1000Research publication (9: 943) on a proposed molecular mechanism for pathogenesis of severe RNA-viral pulmonary infections at the 2020 RiboClub Forum:
#sarscov2 #covid19research #genomics #molecularmechanism #RNA #virology #covidー19
We are giving a platform presentation at the upcoming American Society of Human Genetics virtual meeting #ASHG2020
Session: Personalized Medicine Approaches in Healthcare.
Paper: Pathway-extended gene expression signatures integrate novel biomarkers that improve predictions of responses to kinase inhibitors
P. K. Rogan(1,2), A. J. Bagchee-Clark(1), E. J. Mucaki(1). 1. Department of Biochemistry, University of Western Ontario and 2. CytoGnomix Inc., London ON Canada
Abstract: Individualized chemotherapy selection in cancer potentially maximizes drug efficacy while minimizing drug toxicity. Despite the knowledge of many pharmacogenetic biomarkers, inter-individual variability in response to chemotherapeutic response has limited the success of the approach. We derive multi-gene expression signatures that predict individual patient responses to tyrosine kinase inhibitors (TKIs): erlotinib, gefitinib, sorafenib, sunitinib, lapatinib and imatinib. Gene models for TKIs implicated from the published literature tend to predict either sensitivity or resistance to TKIs well (but not both). This
issue was addressed with a systems biology-based strategy that expanded with candidate gene products related to these genes in these models through biochemical pathways and interactions. Using patient transcriptome data, these Pathway-Extended (PE) models predicted responses for individual patients that matched observed outcomes at accuracies of 65% (imatinib), 71% (lapatinib and gefitinib), 78% (sunitinib), 83% (erlotinib) and 89% (sorafenib). After training and evaluating many extended signatures, those with the strongest predictive performance were composed primarily of pathway-related genes that according to post-hoc analysis were clearly implicated in cancer phenotypes. Machine learning-based PE expression signatures display strong efficacy in predicting both sensitivity and specificity in patients through incorporation
of novel cancer biomarkers.
#genomics #medicine #chemotherapy #cancertreatment #kinaseinhibitors
Peter Rogan was interviewed by Gill Eapin for his daily podcast, Scientific Sense, focused on Science & Economics about our research projects about COVID19. Listen at the link below.
#medicine #sarscov2 #covidー19 #medicalsciences #epidemiology #health #geostatistics #hotspots #publichealth #genomics #molecularmechanism
We have described and provide evidence for an explanation for how rapid onset, severe RNA viral infections, such as SARS-CoV-2 or Influenza, may develop:
Rogan PK, Mucaki EJ and Shirley BC. A proposed molecular mechanism for pathogenesis of severe RNA-viral pulmonary infections. F1000Research 2020, 9:943 (https://doi.org/10.12688/f1000research.25390.1)
