TMED2 Induces Cisplatin Resistance in Breast Cancer via Targeting the KEAP1-Nrf2 Pathway.

OBJECTIVE: Cisplatin is the first-line treatment for breast cancer, but it faces challenges of drug resistance. This study investigated new molecular mechanisms underlying cisplatin resistance in breast cancer. METHODS: We analyzed sequencing data from the TCGA database to identify potential associations between transmembrane emp24 protein transport domain containing 2 (TMED2) and breast cancer. Western blotting, real-time PCR, CCK-8, and TUNEL assays were used to measure the effects and molecular mechanism of TMED2 on cisplatin resistance in MCF-7 and MDA-MB-231 cell lines. RESULTS: TMED2 was overexpressed in breast cancer and associated with poor prognosis. TMED2 increased cisplatin resistance in breast cancer cells in vitro via promoting ubiquitination of Kelch-like ECH-associated protein 1 (KEAP1), relieving inhibition of KEAP1 on nuclear factor erythroid 2-related factor 2 (Nrf2), and increasing expression of downstream drug resistance related genes, such as heme oxygenase 1 (HO-1) and NAD (P) H quinone oxidoreductase 1 (NQO1). CONCLUSION: We identified a new molecular mechanism by which TMED2 affects cisplatin resistance in breast cancer. Our results provide theoretical guidance for future clinical applications.

Predictive Value of Gray-Matter-White-Matter Ratio on Brain Computed Tomography for Delayed Encephalopathy after Acute Carbon Monoxide Poisoning: A Retrospective Cohort Study.

BACKGROUND: This study is aimed at determining the predictive value of the gray-matter-white-matter ratio (GWR) on brain computed tomography for delayed encephalopathy after acute carbon monoxide (CO) poisoning (DEACMP). METHODS: This retrospective cohort study reviewed 352 patients with acute CO poisoning and who underwent the brain computed tomography test. These patients were admitted to Cangzhou Central Hospital from May 2010 to May 2020. The patients were divided into the DEACMP (n = 16) and non-DEACMP (n = 336) groups. Pearson's correlation coefficients were computed for correlation analysis. The predictive value of GWR for DEACMP was evaluated by using logistic regression analysis and receiver operator characteristic curves. RESULTS: The morbidity of DEACMP was 4.5% (16/352). The GWR-basal ganglia, GWR-cerebrum, and GWR-average in the DEACMP group were lower than those in the non-DEACMP group. Correlation analysis indicated that GWR-basal ganglia (r = 0.276; P < 0.001), GWR-cerebrum (r = 0.163; P = 0.002), and GWR-average (r = 0.200; P < 0.001) were correlated with DEACMP. Multivariate logistic regression analysis revealed that reduced GWR-basal ganglia, GWR-cerebrum, and GWR-average were independent risk factors (P < 0.001; P = 0.008; P = 0.001; respectively). Compared with GWR-cerebrum and GWR-average, GWR-basal ganglia had a higher area under the curve of 0.881 (95% confidence interval: 0.783-0.983) with sensitivity and specificity of 93.8% and 68.7%, respectively. The cut-off value of GWR-basal ganglia was 1.055. CONCLUSION: GWR, especially GWR-basal ganglia, is an early useful predictor for DEACMP.