背景:确定转移性肾细胞癌(mRCC)的生物标志物是实际免疫治疗时代尚未满足的需求。有关染色体3p基因的可用数据(即,VHL,PBRM1,SETD2)突变作为治疗反应的潜在预测因子是相互矛盾的。我们描述了这些突变对接受免疫检查点抑制剂(ICI)-双重或ICI/酪氨酸激酶抑制剂(TKI)组合治疗的mRCC患者临床结局的影响。
方法:我们对一线ICI/ICI或ICI/TKI治疗的mRCC患者进行了单中心回顾性分析。使用了多基因小组,允许扩增841个扩增子(54.93kb,人类参考序列hg19/GRCh37)在以下基因的编码序列中:ATM,BAP1,KDM5C,MET,MTOR,NF2,PBRM1,PIK3CA,PTEN,SETD2、SMARCB1、TP53、TSC1、TSC2、VHL。
结果:纳入18例接受ICI/ICI和ICI/TKI治疗的患者,其肿瘤组织足以进行分子分析。组织学为100%透明细胞。IMDC风险为50%中等,33.4%好,差16.6%。一线治疗为89%ICI/TKI,11%ICI/ICI。83.3%的患者(n=15)携带基因组改变(GA)。最常见的GA包括44%的VHL(n=8;7个致病性-PAT和1个未知意义的变异-VUS),44%的PBRM1(n=8;5PAT和3VUS)和33%的SETD2(n=6;4PAT和2VUS)。由于小样本的限制,不允许进行适当的统计分析,SETD2突变患者的中位无进展(mPFS)和总生存期(mOS)低于非SETD2突变患者。VHL或PBRM1GA显示更高的mPFS和mOS,特别是在PBRM1+VHL突变的pts中。
结论:我们的数据显示SETD2GA对RCC基于ICI的治疗可能具有阴性预测作用。合并VHL和PBRM1GA可作为ICI/TKI疗效的预测因子。我们的假设生成分析强调了对这些基因作为RCC中有希望的生物标志物进行综合评估的必要性。需要更多的研究。
BACKGROUND: Identifying biomarkers for metastatic renal cell carcinoma (mRCC) is an unmet need in actual immunotherapy era. Available data regarding chromosome 3p genes (i.e., VHL,
PBRM1, SETD2) mutations as potential predictors for therapy response is conflicting. We describe the impact of these mutations on clinical outcomes in mRCC patients treated with immune checkpoint inhibitor (ICI)-doublet or ICI/tyrosine kinase inhibitor (TKI) combinations.
METHODS: We performed a single-center retrospective analysis on mRCC patients treated with first line ICI/ICI or ICI/TKI. A multi-gene panel was used, allowing the amplification of 841 amplicons (54.93 kb, human reference sequence hg19/GRCh37) in the coding sequences of the following genes: ATM, BAP1, KDM5C, MET, MTOR, NF2,
PBRM1, PIK3CA, PTEN, SETD2, SMARCB1, TP53, TSC1, TSC2, VHL.
RESULTS: 18 patients undergoing ICI/ICI and ICI/TKI who had tumor tissue adequate for molecular analysis were included. Histology was 100% clear cell. IMDC risk was 50% intermediate, 33.4% good, 16.6% poor. First line therapy was 89% ICI/TKI, 11% ICI/ICI. 83.3% pts (n = 15) carried genomic alterations (GA). Most common GA included VHL in 44% (n = 8; 7 pathogenic - PAT and 1 variant of unknown significance - VUS),
PBRM1 in 44% (n = 8; 5 PAT and 3 VUS) and SETD2 in 33% (n = 6; 4 PAT and 2 VUS). With the limit of a small sample that did not allow proper statistical analyses, SETD2-mutated patients had lower median progression free (mPFS) and overall survival (mOS) than non-SETD2 mutated patients. Higher mPFS and mOS were shown with VHL or
PBRM1 GA, especially in
PBRM1 +VHL mutated pts.
CONCLUSIONS: Our data shows a possible negative predictive role of SETD2 GA for ICI-based therapy in RCC. Concomitant VHL and
PBRM1 GA could act as a predictor for ICI/TKI efficacy. Our hypothesis-generating analysis highlights the need of an integrated evaluation of these genes as promising biomarkers in RCC. Further larger studies are required.