PO.CL01.01 · 临床研究
定量c-MET免疫组化揭示乳头状肾细胞癌的预后亚组
Quantitative c-MET immunohistochemistry reveals prognostic subgroups in papillary renal cell carcinoma
作者与单位 Authors & Affiliations
摘要 Abstract
中文摘要
背景:MET是乳头状肾细胞癌(PRCC)的关键驱动基因,但c-MET免疫组化(IHC)表达的预后意义仍不明确。既往研究受限于包含混杂肾肿瘤实体的异质性队列,以及人工IHC评估固有的主观变异性。由于c-MET靶向抗体药物偶联物(如Telisotuzumab vedotin)在多种癌症中显示出治疗前景,我们旨在对严格定义的PRCC队列定量评估c-MET表达,并利用图像分析平台阐明其预后价值。
方法:共对505例手术切除的PRCC病例(1989-2023年,峨山医疗中心)在使用19标志物IHC panel排除非PRCC实体后,按照2022年WHO系统重新分类。在最终的415例PRCC病例中进行c-MET IHC(SP44,Ventana),并同时采用人工评分(H评分)和HALO图像分析进行评分。表达水平按中位值二分为高和低。统计分析包括Spearman相关分析,以及针对5年无复发生存(RFS)和疾病特异性生存(DSS)的生存分析。
结果:基于HALO的c-MET定量与人工评分显示出强相关性(R = 0.88,P < 0.001),支持了自动评估的有效性。HALO评分显示1型PRCC的c-MET表达显著高于2型PRCC(中位数64.03 vs. 33.26,P < 0.001)。2型PRCC的RFS和DSS均较1型更差(两者P < 0.001)。在亚组分析中,c-MET低表达的2型PRCC其DSS显著差于c-MET低表达(P = 0.022)或高表达(P = 0.029)的1型PRCC,然而c-MET低表达的2型PRCC与1型PRCC相比未显示统计学显著性。对于RFS,无论c-MET水平如何,2型PRCC的预后均一致地差于1型PRCC。然而,在单因素或多因素Cox模型中,c-MET表达并非独立预后因素。
结论:本研究的优势在于其庞大、经严格重新分类的PRCC队列以及人工与自动评分方法的结合使用。重要的是,自动HALO评分提供了c-MET表达的客观、可重复的测量,同时与人工评估保持极佳的一致性,支持其在标准化生物标志物评估中的应用价值。尽管现行WHO分类不再推荐PRCC亚型分型,但我们发现c-MET低表达与2型形态学及更差的DSS强烈相关,反映了各型特异性表型之间根本不同的潜在分子通路。此外,由于c-MET高表达的2型PRCC显示出与1型相似的生存模式,c-MET表达的定量评估可能改善PRCC的风险分层,并进一步指导新兴MET靶向治疗的患者选择。
查看英文原文 English abstract
Background: MET is a key driver gene in papillary renal cell carcinoma (PRCC), yet the prognostic significance of c-MET immunohistochemical (IHC) expression remains unclear. Previous studies have been limited by heterogeneous cohorts containing mixed renal tumor entities and by subjective variability inherent to manual IHC assessment. As c-MET targeted antibody-drug conjugates (e.g., Telisotuzumab vedotin) show therapeutic promise in several cancers, we aimed to quantitatively evaluate c-MET expression in a strictly defined PRCC cohort and to clarify its prognostic value using an image analysis platform.
Methods: A total of 505 surgically resected PRCC cases (1989-2023, Asan Medical Center) were reclassified according to the 2022 WHO system after excluding non-PRCC entities using a 19-marker IHC panel. c-MET IHC (SP44, Ventana) was performed in the final 415 PRCC cases and scored both manually (H-score) and by HALO image analysis. Expression levels were dichotomized into high and low by the median value. Statistical analyses included Spearman correlation, and survival analyses for 5-year recurrence-free (RFS) and disease-specific survival (DSS).
Results: HALO-based c-MET quantification showed a strong correlation with manual scoring (R = 0.88, P < 0.001), supporting the validity of automated evaluation. HALO scoring demonstrated significantly higher c-MET expression in type 1 compared to type 2 PRCC (median 64.03 vs. 33.26, P < 0.001). Type 2 PRCC exhibited worse RFS and DSS than type 1 (both P < 0.001). In subgroup analyses, type 2 PRCC with low c-MET expression had significantly poorer DSS than type 1 PRCC with either low (P = 0.022) or high (P = 0.029) expression, however type 2 PRCC with low c-MET expression did not show statistical significance compared to type 1 PRCC. For RFS, type 2 PRCC showed consistently worse outcomes than type 1 PRCC regardless of c-MET level. However, c-MET expression was not an independent prognostic factor in univariate or multivariate Cox models.
Conclusions: This study's strength lies in its large, rigorously reclassified PRCC cohort and the combined use of manual and automated scoring methods. Importantly, automated HALO scoring provided an objective, reproducible measure of c-MET expression while maintaining excellent concordance with manual evaluation, supporting its utility in standardizing biomarker assessment. Although PRCC subtyping is no longer recommended in the current WHO classification, we found that low c-MET expression strongly correlated with type 2 morphology and poorer DSS, reflecting the fundamentally different underlying molecular pathways between type-specific phenotypes. Also, since type 2 PRCC with high c-MET expression showed survival patterns similar to type 1, quantitative assessment of c-MET expression may refine risk stratification in PRCC and furhter guide patient selection for emerging MET-targeted therapies.
利益披露 Disclosure
Y. Lee, None..
J. Park, None..
S. Yoon, None..
Y. Cho, None..
I. Park, None..
B. Ahn, None.