The current tumor-node-metastasis (TNM) system is limited in predicting the survival and guiding the treatment of hepatocellular carcinoma (HCC) patients since the TNM system only focuses on the anatomical factors, regardless of the intratumoral molecule heterogeneity. Besides, the landscape of intratumoral immune genes has emerged as a prognostic indicator. The mediator complex subunit 8 (MED8) is a major polymerase regulator and has been described as an oncogene in renal cell carcinoma, but its pathophysiological significance of HCC and its contribution to the prognosis of HCC remain unclear. Here, we aimed to discuss the expression profile and clinical correlation of MED8 in HCC and construct a predictive model based on MED8-related immunomodulators as a supplement to the TNM system. According to our analyses, MED8 was overexpressed in HCC tissues and increased expression of MED8 was an indicator of poor outcome in HCC. The knockdown of MED8 weakened the proliferation, colony forming, and migration of HepG2 and Huh7 cells. Subsequently, a predictive model was identified based on a panel of three MED8-related immunomodulators using The Cancer Genome Atlas (TCGA) database and further validated in International Cancer Genome Consortium (ICGC) database. The combination of the predictive model and the TNM system could improve the performance in predicting the survival of HCC patients. High-risk patients had poor overall survival in TCGA and ICGC databases, as well as in subgroup analysis with early clinicopathology classification. It was also found that high-risk patients had a higher probability of recurrence in TCGA cohort. Furthermore, low-risk score indicated a better response to immunotherapy and drug therapy. This predictive model can be served as a supplement to the TNM system and may have implications in prognosis stratification and therapeutic guidance for HCC.
Background: Old drugs for new indications in the novel coronavirus disease of 2019 (COVID-19) pandemic have raised concerns regarding cardiotoxicity, especially the development of drug-induced QT prolongation. The acute blocking of the cardiac hERG potassium channel is conventionally thought to be the primary mechanism of QT prolongation induced by COVID-19 drugs fluvoxamine (FLV) and lopinavir (LPV). The chronic impact of these medications on the hERG expression has yet to be determined.Methods: To investigate the effect of long-term incubation of FLV and LPV on the hERG channel, we used electrophysiological assays and molecular experiments, such as Western blot, RT-qPCR, and immunofluorescence, in HEK-293 cells stably expressing hERG and human-induced pluripotent stem cell–derived cardiomyocytes (hiPSC-CMs).Results: Compared to the acute effects, chronic incubation for FLV and LPV generated much lower half-maximal inhibitory concentration (IC50) values, along with a left-shifted activation curve and retarded channel activation. Inconsistent with the reduction in current, we unexpectedly found that the chronic effects of drugs promoted the maturation of hERG proteins, accompanied by the high expression of Hsp70 and low expression of Hsp90. Targeting Hsp70 using siRNA was able to reverse the effects of these drugs on hERG proteins. In addition, FLV and LPV resulted in a significant reduction of APD90 and triggered the early after-depolarizations (EADs), as well as inhibited the protein level of the L-type voltage–operated calcium channel (L-VOCC) in hiPSC-CMs.Conclusion: Chronic incubation with FLV and LPV produced more severe channel-blocking effects and contributed to altered channel gating and shortened action potential duration by inhibiting hERG and Cav1.2.
BackgroundObservational studies have suggested that irritability is associated with a higher risk of cardiovascular disease (CVD). However, the potential causal association is not clear. Therefore, we used Mendelian randomization (MR) analysis to assess the causal association of irritability with CVD risk.MethodsA two-sample MR analysis was performed to confirm the causal association of irritability with the risk of several common CVDs. The exposure data were derived from the UK biobank involving 90,282 cases and 232,386 controls, and outcome data were collected from the published genome-wide association studies (GWAS) and FinnGen database. Inverse-variance weighted (IVW), MR-Egger, and weighted median methods were performed to assess the causal association. Furthermore, the mediating effect of smoking, insomnia, and depressed affect was explored by using a two-step MR.ResultsThe MR analysis indicated that genetically predicted irritability increased the risk of CVD, including coronary artery disease (CAD) (Odds ratio, OR: 2.989; 95% confidence interval, CI: 1.521–5.874, p = 0.001), myocardial infarction (MI) (OR: 2.329, 95% CI: 1.145–4.737, p = 0.020), coronary angioplasty (OR: 5.989, 95% CI: 1.696–21.153, p = 0.005), atrial fibrillation (AF) (OR: 4.646, 95% CI: 1.268–17.026, p = 0.02), hypertensive heart disease (HHD) (OR: 8.203; 95% CI: 1.614–41.698, p = 0.011), non-ischemic cardiomyopathy (NIC) (OR: 5.186; 95% CI: 1.994–13.487, p = 0.001), heart failure (HF) (OR: 2.253; 95% CI: 1.327–3.828, p = 0.003), stroke (OR: 2.334; 95% CI: 1.270–4.292, p = 0.006), ischemic stroke (IS) (OR: 2.249; 95% CI: 1.156–4.374, p = 0.017), and ischemic stroke of large-artery atherosclerosis ISla (OR: 14.326; 95% CI: 2.750–74.540, p = 0.002). The analysis also indicated that smoking, insomnia, and depressed affect play an important role in the process of irritability leading to cardiovascular disease.ConclusionOur findings support the first genetic evidence of the causality of genetically predicted irritability with the risk of developing into CVDs. Our results deliver a viewpoint that more early active interventions to manage an individual's anger and related unhealthy lifestyle habits are needed to prevent the occurrence of adverse cardiovascular events.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.