Objectives: . Our study aimed to explore the role of the potassium channel KCNK1 in head and neck squamous cell carcinoma, focusing on its impact on tumor growth, invasion, and metastasis. We also investigated the therapeutic potential of quinidine, a known KCNK1 inhibitor, in both in vitro cell lines and a zebrafish patient-derived xenograft (PDX) model. Methods: . We established primary cell cultures from head and neck cancer tissues and employed the FaDu cell line for in vitro studies, modulating KCNK1 expression through overexpression and knockdown techniques. We evaluated cell migration, invasion, and proliferation. Additionally, we developed a zebrafish PDX model to assess the impact of quinidine on tumor growth and metastasis in vivo. RNA sequencing and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses were conducted to elucidate the molecular mechanisms underlying the role of KCNK1 in cancer progression. Results: . Overexpression of KCNK1 in FaDu cells resulted in enhanced cell migration and invasion, whereas its knockdown diminished these processes. In the zebrafish PDX model, quinidine markedly inhibited tumor growth and metastasis, demonstrating a significant reduction in tumor volume and micrometastasis rates compared to the control groups. The molecular analyses indicated that KCNK1 plays a role in critical signaling pathways associated with tumor growth, such as the Ras and MAPK pathways. Conclusion . Our findings highlight the critical role of KCNK1 in promoting tumor growth and metastasis in head and neck cancer. The inhibitory effect of quinidine on tumor progression in the zebrafish PDX model highlights the therapeutic potential of targeting KCNK1. These results suggest that KCNK1 could serve as a valuable therapeutic target for head and neck cancer, warranting further investigation into treatments that target KCNK1.

Objectives: . Our study aimed to explore the role of the potassium channel KCNK1 in head and neck squamous cell carcinoma, focusing on its impact on tumor growth, invasion, and metastasis. We also investigated the therapeutic potential of quinidine, a known KCNK1 inhibitor, in both in vitro cell lines and a zebrafish patient-derived xenograft (PDX) model. Methods: . We established primary cell cultures from head and neck cancer tissues and employed the FaDu cell line for in vitro studies, modulating KCNK1 expression through overexpression and knockdown techniques. We evaluated cell migration, invasion, and proliferation. Additionally, we developed a zebrafish PDX model to assess the impact of quinidine on tumor growth and metastasis in vivo. RNA sequencing and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses were conducted to elucidate the molecular mechanisms underlying the role of KCNK1 in cancer progression. Results: . Overexpression of KCNK1 in FaDu cells resulted in enhanced cell migration and invasion, whereas its knockdown diminished these processes. In the zebrafish PDX model, quinidine markedly inhibited tumor growth and metastasis, demonstrating a significant reduction in tumor volume and micrometastasis rates compared to the control groups. The molecular analyses indicated that KCNK1 plays a role in critical signaling pathways associated with tumor growth, such as the Ras and MAPK pathways. Conclusion . Our findings highlight the critical role of KCNK1 in promoting tumor growth and metastasis in head and neck cancer. The inhibitory effect of quinidine on tumor progression in the zebrafish PDX model highlights the therapeutic potential of targeting KCNK1. These results suggest that KCNK1 could serve as a valuable therapeutic target for head and neck cancer, warranting further investigation into treatments that target KCNK1.

Objectives: . Our study aimed to explore the role of the potassium channel KCNK1 in head and neck squamous cell carcinoma, focusing on its impact on tumor growth, invasion, and metastasis. We also investigated the therapeutic potential of quinidine, a known KCNK1 inhibitor, in both in vitro cell lines and a zebrafish patient-derived xenograft (PDX) model. Methods: . We established primary cell cultures from head and neck cancer tissues and employed the FaDu cell line for in vitro studies, modulating KCNK1 expression through overexpression and knockdown techniques. We evaluated cell migration, invasion, and proliferation. Additionally, we developed a zebrafish PDX model to assess the impact of quinidine on tumor growth and metastasis in vivo. RNA sequencing and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses were conducted to elucidate the molecular mechanisms underlying the role of KCNK1 in cancer progression. Results: . Overexpression of KCNK1 in FaDu cells resulted in enhanced cell migration and invasion, whereas its knockdown diminished these processes. In the zebrafish PDX model, quinidine markedly inhibited tumor growth and metastasis, demonstrating a significant reduction in tumor volume and micrometastasis rates compared to the control groups. The molecular analyses indicated that KCNK1 plays a role in critical signaling pathways associated with tumor growth, such as the Ras and MAPK pathways. Conclusion . Our findings highlight the critical role of KCNK1 in promoting tumor growth and metastasis in head and neck cancer. The inhibitory effect of quinidine on tumor progression in the zebrafish PDX model highlights the therapeutic potential of targeting KCNK1. These results suggest that KCNK1 could serve as a valuable therapeutic target for head and neck cancer, warranting further investigation into treatments that target KCNK1.

Background: and Purpose Symptomatic intracranial hemorrhage (sICH) following endovascular thrombectomy (EVT) is a severe complication associated with adverse functional outcomes and increased mortality rates. Currently, a reliable predictive model for sICH risk after EVT is lacking. Methods: This study used data from patients aged ≥20 years who underwent EVT for anterior circulation stroke from the nationwide Taiwan Registry of Endovascular Thrombectomy for Acute Ischemic Stroke (TREAT-AIS). A predictive model including factors associated with an increased risk of sICH after EVT was developed to differentiate between patients with and without sICH. This model was compared existing predictive models using nationwide registry data to evaluate its relative performance. Results: Of the 2,507 identified patients, 158 developed sICH after EVT. Factors such as diastolic blood pressure, Alberta Stroke Program Early CT Score, platelet count, glucose level, collateral score, and successful reperfusion were associated with the risk of sICH after EVT. The TREAT-AIS score demonstrated acceptable predictive accuracy (area under the curve [AUC]=0.694), with higher scores being associated with an increased risk of sICH (odds ratio=2.01 per score increase, 95% confidence interval=1.64–2.45, P<0.001). The discriminatory capacity of the score was similar in patients with symptom onset beyond 6 hours (AUC=0.705). Compared to existing models, the TREAT-AIS score consistently exhibited superior predictive accuracy, although this difference was marginal. Conclusions The TREAT-AIS score outperformed existing models, and demonstrated an acceptable discriminatory capacity for distinguishing patients according to sICH risk levels. However, the differences between models were only marginal. Further research incorporating periprocedural and postprocedural factors is required to improve the predictive accuracy.

Background: and Purpose Symptomatic intracranial hemorrhage (sICH) following endovascular thrombectomy (EVT) is a severe complication associated with adverse functional outcomes and increased mortality rates. Currently, a reliable predictive model for sICH risk after EVT is lacking. Methods: This study used data from patients aged ≥20 years who underwent EVT for anterior circulation stroke from the nationwide Taiwan Registry of Endovascular Thrombectomy for Acute Ischemic Stroke (TREAT-AIS). A predictive model including factors associated with an increased risk of sICH after EVT was developed to differentiate between patients with and without sICH. This model was compared existing predictive models using nationwide registry data to evaluate its relative performance. Results: Of the 2,507 identified patients, 158 developed sICH after EVT. Factors such as diastolic blood pressure, Alberta Stroke Program Early CT Score, platelet count, glucose level, collateral score, and successful reperfusion were associated with the risk of sICH after EVT. The TREAT-AIS score demonstrated acceptable predictive accuracy (area under the curve [AUC]=0.694), with higher scores being associated with an increased risk of sICH (odds ratio=2.01 per score increase, 95% confidence interval=1.64–2.45, P<0.001). The discriminatory capacity of the score was similar in patients with symptom onset beyond 6 hours (AUC=0.705). Compared to existing models, the TREAT-AIS score consistently exhibited superior predictive accuracy, although this difference was marginal. Conclusions The TREAT-AIS score outperformed existing models, and demonstrated an acceptable discriminatory capacity for distinguishing patients according to sICH risk levels. However, the differences between models were only marginal. Further research incorporating periprocedural and postprocedural factors is required to improve the predictive accuracy.

Background: and Purpose Symptomatic intracranial hemorrhage (sICH) following endovascular thrombectomy (EVT) is a severe complication associated with adverse functional outcomes and increased mortality rates. Currently, a reliable predictive model for sICH risk after EVT is lacking. Methods: This study used data from patients aged ≥20 years who underwent EVT for anterior circulation stroke from the nationwide Taiwan Registry of Endovascular Thrombectomy for Acute Ischemic Stroke (TREAT-AIS). A predictive model including factors associated with an increased risk of sICH after EVT was developed to differentiate between patients with and without sICH. This model was compared existing predictive models using nationwide registry data to evaluate its relative performance. Results: Of the 2,507 identified patients, 158 developed sICH after EVT. Factors such as diastolic blood pressure, Alberta Stroke Program Early CT Score, platelet count, glucose level, collateral score, and successful reperfusion were associated with the risk of sICH after EVT. The TREAT-AIS score demonstrated acceptable predictive accuracy (area under the curve [AUC]=0.694), with higher scores being associated with an increased risk of sICH (odds ratio=2.01 per score increase, 95% confidence interval=1.64–2.45, P<0.001). The discriminatory capacity of the score was similar in patients with symptom onset beyond 6 hours (AUC=0.705). Compared to existing models, the TREAT-AIS score consistently exhibited superior predictive accuracy, although this difference was marginal. Conclusions The TREAT-AIS score outperformed existing models, and demonstrated an acceptable discriminatory capacity for distinguishing patients according to sICH risk levels. However, the differences between models were only marginal. Further research incorporating periprocedural and postprocedural factors is required to improve the predictive accuracy.