CELL INTELLIGENCE · 肿瘤细胞治疗研究
肿瘤细胞治疗研究
英文原题:Novel immune scoring dynamic nomograms based on B7-H3, B7-H4, and HHLA2: Potential prediction in survival and immunotherapeutic efficacy for gallbladder cancer.
Novel immune scoring dynamic nomograms based on B7-H3, B7-H4, and HHLA2: Potential prediction in survival and immunotherapeutic efficacy for gallbladder cancer.
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关注 B7-H3、B7-H4 和 HHLA2 的免疫评分系统可能有效对 GBC 的预后进行分层。基于新型免疫评分系统的预后列线图可能潜在地预测 GBC 的生存和免疫治疗疗效。需要进一步的有效验证。
胆囊癌(GBC)是一种致命的恶性肿瘤,治疗策略有限。我们旨在开发聚焦于 B7-H3、B7-H4 和 HHLA2 的新型免疫评分系统。我们进一步研究了这些系统在预测 GBC 生存和免疫治疗疗效方面的潜在临床作用。
这是一项单中心回顾性队列研究,探讨了B7-H3、B7-H4和HHLA2的表达特征。通过logistic回归分析开发了用于预后评估的免疫评分列线图。采用Harrell一致性指数(C-index)和决策曲线分析(DCA)评估其性能,并通过校准曲线进行验证。
B7-H3、B7-H4和HHLA2在GBC组织中表现出相对较高的共表达模式发生率。它们与更差的临床病理分期、免疫微环境抑制以及术后生存的不良预后相关。基于B7-H3、B7-H4和HHLA2建立的B7分层是独立的预后预测因子(两组中p<0.05)。此外,基于B7分层和CD8 + TILs密度也成功构建了免疫分层(均p<0.001)。基于B7分层/或免疫分层结合TNM/或Nevin分期系统开发了预测模型。通过DCA和临床影响图,这些新型模型在预测GBC患者生存和免疫治疗疗效方面具有出色的区分能力。最后,针对最有前景的临床预测模型(B7-TNM模型和Immune-TNM模型)开发了动态列线图以方便预测。
Gallbladder cancer (GBC) is a mortal malignancy with limited therapeutic strategies. We aimed to develop novel immune scoring systems focusing on B7-H3, B7-H4, and HHLA2. We further investigated their potential clinical effects in predicting survival and immunotherapeutic efficacy for GBC.
This was a retrospective cohort study in a single center that explored the expression characteristics of B7-H3, B7-H4, and HHLA2. The immune scoring nomograms for prognostic were developed via logistic regression analyses. Their performance was evaluated using the Harrell concordance index (C-index) and decision curves analysis (DCA), and validated with calibration curves.
B7-H3, B7-H4, and HHLA2 manifested with a relatively high rate of co-expression patterns in GBC tissues. They were associated with worse clinicopathological stage, suppression of immune microenvironment, and unfavorable prognosis in postoperative survival. B7 stratification established based on B7-H3, B7-H4, and HHLA2 was an independent prognostic predictor (p<0.05 in both groups). Moreover, immune stratification was also successfully constructed based on B7 stratification and the density of CD8 + TILs (all p<0.001). The prediction models were developed based on B7-/or immune stratification combined with the TNM/or Nevin staging system. These novel models have excellent discrimination ability in predicting survival and immunotherapeutic efficacy for GBC patients by DCA and clinical impact plots. Finally, dynamic nomograms were developed for the most promising clinical prediction models (B7-TNM model and Immune-TNM model) to facilitate prediction.
Immune scoring systems focusing on B7-H3, B7-H4, and HHLA2 may effectively stratify the prognosis of GBC. Prognostic nomograms based on novel immune scoring systems may potentially predict survival and immunotherapeutic efficacy in GBC. Further valid verification is necessary.
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