University of British Columbia
ORCID: 0000-0001-8310-7855Publishes on Virus-based gene therapy research, SARS-CoV-2 and COVID-19 Research, COVID-19 Clinical Research Studies. 26 papers and 720 citations.
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Human papillomavirus (HPV) causes an increasing number of head and neck squamous cell carcinomas (HNSCCs). Altered metabolism contributes to patient prognosis, but the impact of HPV status on HNSCC metabolism remains relatively uncharacterized. We hypothesize that metabolism-related gene expression differences unique to HPV-positive HNSCC influences patient survival. The Cancer Genome Atlas RNA-seq data from primary HNSCC patient samples were categorized as 73 HPV-positive, 442 HPV-negative, and 43 normal-adjacent control tissues. We analyzed 229 metabolic genes and identified numerous differentially expressed genes between HPV-positive and negative HNSCC patients. HPV-positive carcinomas exhibited lower expression levels of genes involved in glycolysis and higher levels of genes involved in the tricarboxylic acid cycle, oxidative phosphorylation, and β-oxidation than the HPV-negative carcinomas. Importantly, reduced expression of the metabolism-related genes SDHC, COX7A1, COX16, COX17, ELOVL6, GOT2, and SLC16A2 were correlated with improved patient survival only in the HPV-positive group. This work suggests that specific transcriptional alterations in metabolic genes may serve as predictive biomarkers of patient outcome and identifies potential targets for novel therapeutic intervention in HPV-positive head and neck cancers.
Viruses are obligate intracellular parasites that alter many cellular processes to create an environment optimal for viral replication. Reprogramming of cellular metabolism is an important, yet underappreciated feature of many viral infections, as this ensures that the energy and substrates required for viral replication are available in abundance. Human adenovirus (HAdV), which is the focus of this review, is a small DNA tumor virus that reprograms cellular metabolism in a variety of ways. It is well known that HAdV infection increases glucose uptake and fermentation to lactate in a manner resembling the Warburg effect observed in many cancer cells. However, HAdV infection induces many other metabolic changes. In this review, we integrate the findings from a variety of proteomic and transcriptomic studies to understand the subtleties of metabolite and metabolic pathway control during HAdV infection. We review how the E4ORF1 protein of HAdV enacts some of these changes and summarize evidence for reprogramming of cellular metabolism by the viral E1A protein. Therapies targeting altered metabolism are emerging as cancer treatments, and similar targeting of aberrant components of virally reprogrammed metabolism could have clinical antiviral applications.
BACKGROUND: Ulcerative colitis (UC) patients failing medical management require colectomy. This study compares risk estimates for predictors of postoperative complication derived from administrative data against that of chart review and evaluates the accuracy of administrative coding for this population. METHODS: Hospital administrative databases were used to identify adults with UC undergoing colectomy from 1996-2007. Medical charts were reviewed and regression analyses comparing chart versus administrative data were performed to assess the effect of age, emergent operation, and Charlson comorbidities on the occurrence of postoperative complications. Sensitivity, specificity, and positive/negative predictive values of administrative coding for identifying the study population, Charlson comorbidities, and postoperative complications were assessed. RESULTS: Compared to chart review, administrative data estimated a higher magnitude of effect for emergent admission (OR 2.52 [95% CI: 1.80-3.52] versus 1.49 [1.06-2.09]) and Charlson comorbidities (OR 2.91 [1.86-4.56] versus 1.50 [1.05-2.15]) as predictors of postoperative complications. Administrative data correctly identified UC and colectomy in 85.9% of cases. The administrative database was 37% sensitive in identifying patients with ≥ 1Charlson comorbidity. Restricting analysis to active comorbidities increased the sensitivity to 63%. The sensitivity of identifying patients with at least one postoperative complication was 68%; restricting analysis to more severe complications improved the sensitivity to 84%. CONCLUSIONS: Administrative data identified the same risk factors for postoperative complications as chart review, but overestimated the magnitude of risk. This discrepancy may be explained by coding inaccuracies that selectively identifying the most serious complications and comorbidities.
Live viral neutralizing antibody titers are an accepted measure of immunity; however, testing procedures are labor-intensive. COVID-19 antibody and angiotensin converting enzyme-2 (ACE-2) levels have been used as surrogates to live viral neutralizing antibody titers; however, validity among vaccinated individuals is unclear. Using samples from 120 two-dose mRNA vaccinees without previous COVID-19, we found that live viral neutralization was correlated with COVID-19 antibody and ACE2 binding levels. When grouping samples by the time interval between vaccination and sample blood collection, samples collected over 158 days after the first vaccine and over 71 days from the second vaccine demonstrated stronger correlation between live viral neutralization titers and both antibody and ACE2 levels, in comparison to those collected earlier.