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一个整合M2巨细胞和细胞外矩阵组件的诺米图表在肺肉类瘤预后中优于TNM分类:一项两中心回顾性研究

Chao Ma¹, Yaoying Li², Chengyou Zheng¹

¹State Key Laboratory of Oncology in South China, Guangdong Provincial Clinical Research Center for Cancer, Sun Yat-sen University Cancer Center, Guangzhou 510060, China; Department of Pathology, Sun Yat-Sen University Cancer Center, Guangzhou 510060, China.

Pathology, research and practice

|August 9, 2025

概括

高的M2TAM和低的网状/原纤维表明肺肉类瘤 (PSC) 的预后不佳. 一种新型的诺莫格拉姆模型有效地预测了生存率,超过了个性化PSC治疗的传统分期.

科学领域:

在瘤学瘤学.
瘤微环境研究研究
病理学病理学病理学

背景情况:

瘤微环境的组成严重影响瘤的进展.
肺部类癌 (PSC) 是一种侵袭性的恶性瘤.
了解体成分和免疫细胞的空间分布对于预后至关重要.

研究的目的:

研究PSC.中M2瘤相关巨细胞 (TAMs),网状纤维 (RFs) 和原纤维 (CFs) 的分布.
评估PSC中这些成分的临床病理学意义.
开发一种患者生存的预测模型.

主要方法:

分析127个PSC患者的组织样本,使用免疫组织化学和戈莫里染色.
使用HALO软件对M2 TAM,RF和CF分布进行定量分析.
统计分析包括卡普兰-梅尔,多变量分析和名ogram构造.

主要成果:

低M2 TAM密度和高RF/CF密度与较长的整体存活率 (OS) 相相关.
综合因素 (MR和MC) 定义了具有显著差异的OS的低风险和高风险组.
M2 TAMs,RFs,CFs,MC和MR被确定为OS的独立预后因素.
诺米图模型在预测OS时表现出高准确度 (C指数为0.74和0.73) .

结论:

高M2TAM密度和低RF/CF密度与PSC的预后不佳有关.
这些因素作为PSC的独立预后指标.
一个开发的Nomogram模型在预测中长期生存方面优于pTNM分期,有助于个性化治疗策略.

关键词:

原纤维是一种原纤维.巨细胞是一个巨细胞.这个名字叫做Nomogram.肺部肉类瘤癌是肺部的肉类瘤.网状纤维是一种网状纤维.

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