BACKGROUND Gastric cancer is a leading cause of cancer-related deaths worldwide.Prognostic assessments are typically based on the tumor-node-metastasis(TNM)staging system,which does not account for the molecular heter...BACKGROUND Gastric cancer is a leading cause of cancer-related deaths worldwide.Prognostic assessments are typically based on the tumor-node-metastasis(TNM)staging system,which does not account for the molecular heterogeneity of this disease.LATS2,a tumor suppressor gene involved in the Hippo signaling pathway,has been identified as a potential prognostic biomarker in gastric cancer.AIM To construct and validate a nomogram model that includes LATS2 expression to predict the survival prognosis of advanced gastric cancer patients following ra-dical surgery,and compare its predictive performance with traditional TNM staging.METHODS A retrospective analysis of 245 advanced gastric cancer patients from the Fourth Hospital of Hebei Medical University was conducted.The patients were divided into a training group(171 patients)and a validation group(74 patients)to deve-lop and test our prognostic model.The performance of the model was determined using C-indices,receiver operating characteristic curves,calibration plots,and decision curves.RESULTS The model demonstrated a high predictive accuracy with C-indices of 0.829 in the training set and 0.862 in the validation set.Area under the curve values for three-year and five-year survival prediction were significantly robust,suggesting an excellent discrimination ability.Calibration plots confirmed the high concordance between the predictions and actual survival outcomes.CONCLUSION We developed a nomogram model incorporating LATS2 expression,which significantly outperformed conven-tional TNM staging in predicting the prognosis of advanced gastric cancer patients postsurgery.This model may serve as a valuable tool for individualized patient management,allowing for more accurate stratification and im-proved clinical outcomes.Further validation in larger patient cohorts will be necessary to establish its generaliza-bility and clinical utility.展开更多
In recent years, human cancer genome projects provide unprecedented opportunities for the discovery of cancer genes and signaling pathways that contribute to tumor development. While numerous gene mutations can be ide...In recent years, human cancer genome projects provide unprecedented opportunities for the discovery of cancer genes and signaling pathways that contribute to tumor development. While numerous gene mutations can be identified from each cancer genome, what these muta- tions mean for cancer is a challenging question to address, especially for those from less understood putative new cancer genes. As a powerful approach, in silico bioinformatics analysis could efficiently sort out mutations that are predicted to damage gene function. Such an analysis of human large tumor suppressor genes, LATS1 and LATS2, has been carried out and the results support a role of hLATS1/12 as negative growth regulators and tumor suppressors.展开更多
Apoptosis signal-regulating kinase 1 (ASK1)is an important mediator of the cell stress response pathways.Because of its central role in regulating cell death,the activity of ASK1 is tightly regulated by protein-protei...Apoptosis signal-regulating kinase 1 (ASK1)is an important mediator of the cell stress response pathways.Because of its central role in regulating cell death,the activity of ASK1 is tightly regulated by protein-protein interactions and post-translational modifications.Deregulation of ASK1 activity has been linked to human diseases,such as neurological disorders and cancer.Here we describe the identification and characterization of large tumor suppressor 2 (LATS2)as a novel binding partner for ASK1.LATS2 is a core kinase in the Hippo signaling pathway and is commonly downregulated in cancer.We found that LATS2 interacts with ASK1 and increases ASK1-mediated signaUng to promote apoptosis and activate the iNK mitogen-activated protein kinase (MAPK).This change in MAPK signaling is dependent on the catalytic activity of ASK1 but does not require LATS2 kinase activity. This work identifies a novel role for LATS2 as a positive regulator of the ASK1-MKK-JNK signaling pathway and establishes a kinase-independent function of LATS2 that may be part of the intricate regulatory system for cellular response to diverse stress signals.展开更多
文摘BACKGROUND Gastric cancer is a leading cause of cancer-related deaths worldwide.Prognostic assessments are typically based on the tumor-node-metastasis(TNM)staging system,which does not account for the molecular heterogeneity of this disease.LATS2,a tumor suppressor gene involved in the Hippo signaling pathway,has been identified as a potential prognostic biomarker in gastric cancer.AIM To construct and validate a nomogram model that includes LATS2 expression to predict the survival prognosis of advanced gastric cancer patients following ra-dical surgery,and compare its predictive performance with traditional TNM staging.METHODS A retrospective analysis of 245 advanced gastric cancer patients from the Fourth Hospital of Hebei Medical University was conducted.The patients were divided into a training group(171 patients)and a validation group(74 patients)to deve-lop and test our prognostic model.The performance of the model was determined using C-indices,receiver operating characteristic curves,calibration plots,and decision curves.RESULTS The model demonstrated a high predictive accuracy with C-indices of 0.829 in the training set and 0.862 in the validation set.Area under the curve values for three-year and five-year survival prediction were significantly robust,suggesting an excellent discrimination ability.Calibration plots confirmed the high concordance between the predictions and actual survival outcomes.CONCLUSION We developed a nomogram model incorporating LATS2 expression,which significantly outperformed conven-tional TNM staging in predicting the prognosis of advanced gastric cancer patients postsurgery.This model may serve as a valuable tool for individualized patient management,allowing for more accurate stratification and im-proved clinical outcomes.Further validation in larger patient cohorts will be necessary to establish its generaliza-bility and clinical utility.
文摘In recent years, human cancer genome projects provide unprecedented opportunities for the discovery of cancer genes and signaling pathways that contribute to tumor development. While numerous gene mutations can be identified from each cancer genome, what these muta- tions mean for cancer is a challenging question to address, especially for those from less understood putative new cancer genes. As a powerful approach, in silico bioinformatics analysis could efficiently sort out mutations that are predicted to damage gene function. Such an analysis of human large tumor suppressor genes, LATS1 and LATS2, has been carried out and the results support a role of hLATS1/12 as negative growth regulators and tumor suppressors.
文摘Apoptosis signal-regulating kinase 1 (ASK1)is an important mediator of the cell stress response pathways.Because of its central role in regulating cell death,the activity of ASK1 is tightly regulated by protein-protein interactions and post-translational modifications.Deregulation of ASK1 activity has been linked to human diseases,such as neurological disorders and cancer.Here we describe the identification and characterization of large tumor suppressor 2 (LATS2)as a novel binding partner for ASK1.LATS2 is a core kinase in the Hippo signaling pathway and is commonly downregulated in cancer.We found that LATS2 interacts with ASK1 and increases ASK1-mediated signaUng to promote apoptosis and activate the iNK mitogen-activated protein kinase (MAPK).This change in MAPK signaling is dependent on the catalytic activity of ASK1 but does not require LATS2 kinase activity. This work identifies a novel role for LATS2 as a positive regulator of the ASK1-MKK-JNK signaling pathway and establishes a kinase-independent function of LATS2 that may be part of the intricate regulatory system for cellular response to diverse stress signals.
