Department of Melanoma, Cancer Immunotherapy and Development Therapeutics, Istituto Nazionale Tumori-IRCCS Fondazione "G. Pascale", 80131 Napoli, Italy.
Mental and Physical Health and Preventive Medicine, Medical Statistics Unit, University of Campania "Luigi Vanvitelli", 81100 Naples, Italy.
Int J Mol Sci. 2024 Aug 28;25(17):9345. doi: 10.3390/ijms25179345.
Resistance biomarkers are needed to identify patients with advanced melanoma obtaining a response to ICI treatment and developing resistance later. We searched a combination of molecular signatures of response to ICIs in patients with metastatic melanoma. In a retrospective study on patients with metastatic melanoma treated with an anti-PD-1 agent carried out at Istituto Nazionale Tumori-IRCCS-Fondazione "G. Pascale", Naples, Italy. We integrated a whole proteome profiling of metastatic tissue with targeted transcriptomics. To assess the prognosis of patients according to groups of low and high risk, we used PFS and OS as outcomes. To identify the proteins and mRNAs gene signatures associated with the patient's response groups, the discriminant analysis for sparse data performed via partial least squares procedure was performed. Tissue samples from 22 patients were analyzed. A combined protein and gene signature associated with poorer response to ICI immunotherapy in terms of PFS and OS was identified. The PFS and OS Kaplan-Meier curves were significantly better for patients with high expression of the protein signature compared to patients with low expression of the protein signature and who were high-risk (Protein: HR = 0.023, 95% CI: 0.003-0.213; < 0.0001. Gene: HR = 0.053, 95% CI: 0.011-0.260; < 0.0001). The Kaplan-Meier curves showed that patients with low-risk gene signatures had better PFS (HR = 0 0.221, 95% CI: 0.071-0.68; = 0.007) and OS (HR = 0.186, 95% CI: 0.05-0.695; = 0.005). The proteomic and transcriptomic combined analysis was significantly associated with the outcomes of the anti-PD-1 treatment with a better predictive value compared to a single signature. All the patients with low expression of protein and gene signatures had progression within 6 months of treatment (median PFS = 3 months, 95% CI: 2-3), with a significant difference vs. the low-risk group (median PFS = not reached; < 0.0001), and significantly poorer survival (OS = 9 months, 95% CI: 5-9) compared to patients with high expression of protein and gene signatures (median OS = not reached; < 0.0001). We propose a combined proteomic and transcriptomic signature, including genes involved in pro-tumorigenic pathways, thereby identifying patients with reduced probability of response to immunotherapy with ICIs for metastatic melanoma.
需要寻找耐药生物标志物,以识别出接受免疫检查点抑制剂(ICI)治疗后出现应答、但随后发生耐药的晚期黑色素瘤患者。我们检索了转移性黑色素瘤患者对 ICI 治疗应答的分子特征组合。在意大利那不勒斯国家肿瘤研究所-IRCCS-Fondazione “G. Pascale”进行的一项针对接受抗 PD-1 药物治疗的转移性黑色素瘤患者的回顾性研究中,我们整合了转移性组织的全蛋白质组谱与靶向转录组学。为了根据低风险和高风险组评估患者的预后,我们将无进展生存期(PFS)和总生存期(OS)作为结局。为了识别与患者应答组相关的蛋白质和 mRNA 基因特征,我们通过偏最小二乘程序进行了稀疏数据的判别分析。分析了 22 名患者的组织样本。我们发现,在 PFS 和 OS 方面,与对 ICI 免疫治疗应答较差的患者相比,与高表达蛋白特征的患者相比,患者的 PFS 和 OS 无进展生存期(Kaplan-Meier 曲线)明显更差,而与低表达蛋白特征的患者相比,他们属于高风险(蛋白:HR = 0.023,95%CI:0.003-0.213; < 0.0001。基因:HR = 0.053,95%CI:0.011-0.260; < 0.0001)。Kaplan-Meier 曲线显示,低风险基因特征的患者具有更好的 PFS(HR = 0.0221,95%CI:0.071-0.68; = 0.007)和 OS(HR = 0.186,95%CI:0.05-0.695; = 0.005)。与单个特征相比,蛋白质组学和转录组学的联合分析与抗 PD-1 治疗的结局显著相关,具有更好的预测价值。所有蛋白和基因特征低表达的患者在治疗 6 个月内均出现进展(中位 PFS = 3 个月,95%CI:2-3),与低风险组有显著差异(中位 PFS =未达到; < 0.0001),与蛋白和基因特征高表达的患者相比,生存率显著更差(OS = 9 个月,95%CI:5-9)(OS = 未达到; < 0.0001)。我们提出了一种联合蛋白质组学和转录组学特征,包括参与促肿瘤发生途径的基因,从而确定转移性黑色素瘤患者对免疫检查点抑制剂(ICI)免疫治疗应答的可能性降低。