期刊文献+
共找到2篇文章
< 1 >
每页显示 20 50 100
Prognostic significance of grade of malignancy based on histopathological differentiation and Ki-67 in pancreatic ductal adenocarcinoma 被引量:3
1
作者 Yuexiang Liang Guannan Sheng +7 位作者 Yu Guo Yiping Zou Hanhan Guo Zhifei Li Shaofei Chang quan man Song Gao Jihui Hao 《Cancer Biology & Medicine》 SCIE CAS CSCD 2024年第5期416-432,共17页
Objective:Tumor cell malignancy is indicated by histopathological differentiation and cell proliferation.Ki-67,an indicator of cellular proliferation,has been used for tumor grading and classification in breast cancer... Objective:Tumor cell malignancy is indicated by histopathological differentiation and cell proliferation.Ki-67,an indicator of cellular proliferation,has been used for tumor grading and classification in breast cancer and neuroendocrine tumors.However,its prognostic significance in pancreatic ductal adenocarcinoma(PDAC)remains uncertain.Methods:Patients who underwent radical pancreatectomy for PDAC were retrospectively enrolled,and relevant prognostic factors were examined.Grade of malignancy(GOM),a novel index based on histopathological differentiation and Ki-67,is proposed,and its clinical significance was evaluated.Results:The optimal threshold for Ki-67 was determined to be 30%.Patients with a Ki-67 expression level>30%rather than≤30%had significantly shorter 5-year overall survival(OS)and recurrence-free survival(RFS).In multivariate analysis,both histopathological differentiation and Ki-67 were identified as independent prognostic factors for OS and RFS.The GOM was used to independently stratify OS and RFS into 3 tiers,regardless of TNM stage and other established prognostic factors.The tumor-nodemetastasis-GOM stage was used to stratify survival into 5 distinct tiers,and surpassed the predictive performance of TNM stage for OS and RFS.Conclusions:Ki-67 is a valuable prognostic indicator for PDAC.Inclusion of the GOM in the TNM staging system may potentially enhance prognostic accuracy for PDAC. 展开更多
关键词 Pancreatic ductal adenocarcinoma PROGNOSIS KI-67 DIFFERENTIATION TNM stage
在线阅读 下载PDF
Artificial intelligence-based comprehensive analysis of immune-stemness-tumor budding profile to predict survival of patients with pancreatic adenocarcinoma 被引量:5
2
作者 Tianxing Zhou quan man +9 位作者 Xueyang Li Yongjie Xie Xupeng Hou Hailong Wang Jingrui Yan Xueqing Wei Weiwei Bai Ziyun Liu Jing Liu Jihui Hao 《Cancer Biology & Medicine》 SCIE CAS CSCD 2023年第3期196-217,共22页
Objective:Pancreatic ductal adenocarcinoma(PDAC)is an aggressive malignancy.CD8^(+)T cells,cancer stem cells(CSCs),and tumor budding(TB)have been significantly correlated with the outcome of patients with PDAC,but the... Objective:Pancreatic ductal adenocarcinoma(PDAC)is an aggressive malignancy.CD8^(+)T cells,cancer stem cells(CSCs),and tumor budding(TB)have been significantly correlated with the outcome of patients with PDAC,but the correlations have been independently reported.In addition,no integrated immune-CSC-TB profile for predicting survival in patients with PDAC has been established.Methods:Multiplexed immunofluorescence and artificial intelligence(AI)-based comprehensive analyses were used for quantification and spatial distribution analysis of CD8^(+)T cells,CD133^(+)CSCs,and TB.In vivo humanized patient-derived xenograft(PDX)models were established.Nomogram analysis,calibration curve,time-dependent receiver operating characteristic curve,and decision curve analyses were performed using R software.Results:The established‘anti-/pro-tumor’models showed that the CD8^(+)T cell/TB,CD8^(+)T cell/CD133^(+)CSC,TB-adjacent CD8^(+)T cell,and CD133^(+)CSC-adjacent CD8^(+)T cell indices were positively associated with survival of patients with PDAC.These findings were validated using PDX-transplanted humanized mouse models.An integrated nomogram-based immune-CSC-TB profile that included the CD8^(+)T cell/TB and CD8^(+)T cell/CD133^(+)CSC indices was established and shown to be superior to the tumor-nodemetastasis stage model in predicting survival of patients with PDAC.Conclusions:‘Anti-/pro-tumor’models and the spatial relationship among CD8^(+)T cells,CSCs,and TB within the tumor microenvironment were investigated.Novel strategies to predict the prognosis of patients with PDAC were established using AI-based comprehensive analysis and machine learning workflow.The nomogram-based immune-CSC-TB profile can provide accurate prognosis prediction for patients with PDAC. 展开更多
关键词 Artificial intelligence CD8 CSCs tumor budding PDAC NOMOGRAM
在线阅读 下载PDF
上一页 1 下一页 到第
使用帮助 返回顶部