ABSTRACT
BACKGROUND: COVID-19 caused by SARS-CoV-2 has infected 219 million individuals at the time of writing of this paper. A large volume of research findings from observational studies about disease interactions with COVID-19 is being produced almost daily, making it difficult for physicians to keep track of the latest information on COVID-19's effect on patients with certain pre-existing conditions. OBJECTIVE: In this paper, we describe the creation of a clinical decision support tool, the SMART COVID Navigator, a web application to assist clinicians in treating patients with COVID-19. Our application allows clinicians to access a patient's electronic health records and identify disease interactions from a large set of observational research studies that affect the severity and fatality due to COVID-19. METHODS: The SMART COVID Navigator takes a 2-pronged approach to clinical decision support. The first part is a connection to electronic health record servers, allowing the application to access a patient's medical conditions. The second is accessing data sets with information from various observational studies to determine the latest research findings about COVID-19 outcomes for patients with certain medical conditions. By connecting these 2 data sources, users can see how a patient's medical history will affect their COVID-19 outcomes. RESULTS: The SMART COVID Navigator aggregates patient health information from multiple Fast Healthcare Interoperability Resources-enabled electronic health record systems. This allows physicians to see a comprehensive view of patient health records. The application accesses 2 data sets of over 1100 research studies to provide information on the fatality and severity of COVID-19 for several pre-existing conditions. We also analyzed the results of the collected studies to determine which medical conditions result in an increased chance of severity and fatality of COVID-19 progression. We found that certain conditions result in a higher likelihood of severity and fatality probabilities. We also analyze various cancer tissues and find that the probabilities for fatality vary greatly depending on the tissue being examined. CONCLUSIONS: The SMART COVID Navigator allows physicians to predict the fatality and severity of COVID-19 progression given a particular patient's medical conditions. This can allow physicians to determine how aggressively to treat patients infected with COVID-19 and to prioritize different patients for treatment considering their prior medical conditions.
Subject(s)
COVID-19 , Decision Support Systems, Clinical , Electronic Health Records , Humans , SARS-CoV-2 , SoftwareABSTRACT
Approximately 40% of rectal cancers harbor activating K-RAS mutations, and these mutations are associated with poor clinical response to chemoradiotherapy. We aimed to identify small molecule inhibitors (SMIs) that synergize with ionizing radiation (IR) ("radiosensitizers") that could be incorporated into current treatment strategies for locally advanced rectal cancers (LARCs) expressing mutant K-RAS. We first optimized a high-throughput assay for measuring individual and combined effects of SMIs and IR that produces similar results to the gold standard colony formation assay. Using this screening platform and K-RAS mutant rectal cancer cell lines, we tested SMIs targeting diverse signaling pathways for radiosensitizing activity and then evaluated our top hits in follow-up experiments. The two most potent radiosensitizers were the Chk1/2 inhibitor AZD7762 and the PI3K/mTOR inhibitor BEZ235. The chemotherapeutic agent 5-fluorouracil (5-FU), which is used to treat LARC, synergized with AZD7762 and enhanced radiosensitization by AZD7762. This study is the first to compare different SMIs in combination with IR for the treatment of K-RAS mutant rectal cancer, and our findings suggest that Chk1/2 inhibitors should be evaluated in new clinical trials for LARC.
Subject(s)
Chemoradiotherapy/methods , Enzyme Inhibitors/pharmacology , Mutation , Proto-Oncogene Proteins , Radiation-Sensitizing Agents/pharmacology , Rectal Neoplasms , ras Proteins , Cell Line, Tumor , Enzyme Inhibitors/chemistry , Humans , Proto-Oncogene Proteins/antagonists & inhibitors , Proto-Oncogene Proteins/genetics , Proto-Oncogene Proteins/metabolism , Proto-Oncogene Proteins p21(ras) , Radiation-Sensitizing Agents/chemistry , Rectal Neoplasms/genetics , Rectal Neoplasms/metabolism , Rectal Neoplasms/pathology , Rectal Neoplasms/therapy , ras Proteins/antagonists & inhibitors , ras Proteins/genetics , ras Proteins/metabolismABSTRACT
Epidermal growth factor receptors (ErbB1-4) are oncogenic receptor tyrosine kinases (RTKs) that regulate diverse cellular processes. In this study, we combine measurement and mathematical modeling to quantify phospho-turnover at ErbB receptors in human cells and to determine the consequences for signaling and drug binding. We find that phosphotyrosine residues on ErbB1 have half-lives of a few seconds and therefore turn over 100-1000 times in the course of a typical immediate-early response to ligand. Rapid phospho-turnover is also observed for EGF-activated ErbB2 and ErbB3, unrelated RTKs, and multiple intracellular adaptor proteins and signaling kinases. Thus, the complexes formed on the cytoplasmic tail of active receptors and the downstream signaling kinases they control are highly dynamic and antagonized by potent phosphatases. We develop a kinetic scheme for binding of anti-ErbB1 drugs to receptors and show that rapid phospho-turnover significantly impacts their mechanisms of action.
