Comparison of EMT mediated tyrosine kinase inhibitor resistance in NSCLC.

In the United States, lung cancer is the second most common cancer in men and women. In 2017, 222,500 new cases and 155,870 deaths from lung cancer are estimated to have occurred. A tyrosine kinase receptor, epidermal growth factor receptor (EGFR), is over expressed or mutated in non-small cell lung cancer (NSCLC) resulting in increased cell proliferation and survival. Tyrosine kinase inhibitors (TKIs) are currently being used as therapy for NSCLC patients, however, they have limited efficacy in NSCLC patients due to acquisition of resistance. This study investigates the role of epithelial-mesenchymal transition (EMT) in the development of resistance against TKIs in NSCLC. Currently, the role of p120-catenin, Kaiso factor and PRMT-1 in reversal of EMT in T790M mutated and TKI-resistant NSCLC cells is a new line of study. In this investigation we found upregulation of cytoplasmic p120-catenin, which was co-localized with Kaiso factor. In the nucleus, binding of p120-catenin to Kaiso factor initiates transcription by activating EMT-transcription factors such as Snail, Slug, Twist, and ZEB1. PRMT-1 was also found to be upregulated, which induces methylation of Twist and repression of E-cadherin activity, thus promoting EMT. We confirmed that TKI-resistant cells have mesenchymal cell type characteristics based on their cell morphology and gene or protein expression of EMT related proteins. EMT proteins, Vimentin and N-cadherin, displayed increased expression, whereas E-cadherin expression was downregulated. Finally, we found that the knockdown of p120-catenin and PRMT-1 by siRNA or use of a PRMT-1 inhibitor Furamidine increased Erlotinib sensitivity and could reverse EMT to overcome TKI resistance.

Accuracy of Consumer Monitors for Estimating Energy Expenditure and Activity Type.

INTRODUCTION: Increasing use of consumer-based physical activity (PA) monitors necessitates that they are validated against criterion measures. Thus, the purpose of this study was to examine the accuracy of three consumer-based PA monitors for estimating energy expenditure (EE) and PA type during simulated free-living activities. METHODS: Twenty-eight participants (mean ± SD: age, 25.5 ± 3.7 yr; body mass index, 24.9 ± 2.6 kg·m) completed 11 activities ranging from sedentary behaviors to vigorous intensities. Simultaneous measurements were made with an Oxycon portable calorimeter (criterion), a Basis Peak and Garmin Vivofit on the nondominant wrist, and three Withings Pulse devices (right hip, shirt collar, dominant wrist). Repeated-measures ANOVA were used to examine differences between measured and predicted EE. Intraclass correlation coefficients were calculated to determine reliability of EE predictions between Withings placements. Paired samples t tests were used to determine mean differences between observed minutes and Basis Peak predictions during walking, running, and cycling. RESULTS: On average, the Basis Peak was within 8% of measured EE for the entire PA routine (P > 0.05); however, there were large individual errors (95% prediction interval, -290.4 to +233.1 kcal). All other devices were significantly different from measured EE for the entire PA routine (P < 0.05). For activity types, Basis Peak correctly identified ≥92% of actual minutes spent walking and running (P > 0.05), and 40.4% and 0% of overground and stationary cycling minutes, respectively (P < 0.001). CONCLUSIONS: The Basis Peak was the only device that did not significantly differ from measured EE; however, it also had the largest individual errors. Additionally, the Basis Peak accurately predicted minutes spent walking and running, but not cycling.