Schmitt Marisa, Sinnberg Tobias, Niessner Heike, Forschner Andrea, Garbe Claus, Macek Boris, Nalpas Nicolas C
Quantitative Proteomics, University of Tübingen, 72074 Tübingen, Germany.
Division of Dermatooncology, University of Tübingen, 72074 Tübingen, Germany.
Cancers (Basel). 2021 Oct 28;13(21):5411. doi: 10.3390/cancers13215411.
Immune checkpoint inhibitors are used to restore or augment antitumor immune responses and show great promise in the treatment of melanoma and other types of cancers. However, only a small percentage of patients are fully responsive to immune checkpoint inhibition, mostly due to tumor heterogeneity and primary resistance to therapy. Both of these features are largely driven by the accumulation of patient-specific mutations, pointing to the need for personalized approaches in diagnostics and immunotherapy. Proteogenomics integrates patient-specific genomic and proteomic data to study cancer development, tumor heterogeneity and resistance mechanisms. Using this approach, we characterized the mutational landscape of four clinical melanoma patients. This enabled the quantification of hundreds of sample-specific amino acid variants, among them many that were previously not reported in melanoma. Changes in abundance at the protein and phosphorylation site levels revealed patient-specific over-represented pathways, notably linked to melanoma development (MAPK1 activation) or immunotherapy (NLRP1 inflammasome). Personalized data integration resulted in the prediction of protein drug targets, such as the drugs vandetanib and bosutinib, which were experimentally validated and led to a reduction in the viability of tumor cells. Our study emphasizes the potential of proteogenomic approaches to study personalized mutational landscapes, signaling networks and therapy options.
免疫检查点抑制剂用于恢复或增强抗肿瘤免疫反应,在黑色素瘤和其他类型癌症的治疗中显示出巨大潜力。然而,只有一小部分患者对免疫检查点抑制完全有反应,这主要是由于肿瘤异质性和对治疗的原发性耐药。这两个特征在很大程度上是由患者特异性突变的积累驱动的,这表明在诊断和免疫治疗中需要个性化方法。蛋白质基因组学整合患者特异性基因组和蛋白质组数据,以研究癌症发展、肿瘤异质性和耐药机制。通过这种方法,我们对四名临床黑色素瘤患者的突变图谱进行了表征。这使得能够对数百种样本特异性氨基酸变体进行定量,其中许多在黑色素瘤中以前未被报道。蛋白质和磷酸化位点水平上丰度的变化揭示了患者特异性过度表达的途径,特别是与黑色素瘤发展(MAPK1激活)或免疫治疗(NLRP1炎性小体)相关的途径。个性化数据整合导致了蛋白质药物靶点的预测,如凡德他尼和博舒替尼,这些靶点经过实验验证,并导致肿瘤细胞活力降低。我们的研究强调了蛋白质基因组学方法在研究个性化突变图谱、信号网络和治疗选择方面的潜力。