转移性黑色素瘤的综合基因组分析:来自7个意大利癌症中心的网络查结果
Matteo Pallocca1, Ivan Molineris2,3, Enrico Berrino3,4
1Institute of Experimental Endocrinology and Oncology, National Research Council, Naples, Italy. matteo.pallocca@ifo.it.
Journal of translational medicine
|January 6, 2024
概括
晚期黑色素瘤的综合基因组分析揭示了BRAF之外的新的预测生物标志物. 在PDGFRB,NOTCH3和RET中的突变显示出改善免疫疗法和向治疗结果的希望.
科学领域:
- 在瘤学瘤学.
- 基因组学就是基因组学.
- 翻译医学是一种翻译医学.
背景情况:
- 先进的黑色素瘤治疗依赖于连续的向和免疫疗法,主要是免疫检查点封锁.
- 目前黑色素瘤的预测生物标志物仅限于BRAF突变和瘤突变负担 (TMB).
- 综合基因组分析 (CGP) 已被批准用于固体瘤,但缺乏在黑色素瘤中验证的预测生物标志物.
研究的目的:
- 评估CGP在接受向和免疫治疗的晚期黑色素瘤患者中的实用性.
- 确定可预测治疗反应和生存的新型基因组生物标志物.
- 评估基因组学驱动的临床试验网络的可行性.
主要方法:
- 一个多中心观察性临床试验,涉及来自意大利7个癌症中心的82个FFPE转移性黑色素瘤样本.
- 下一代测序 (NGS) 使用自定义的184基因安普利康面板进行DNA分析.
- 用机器学习模型 (COX/Lasso,随机森林) 来进行生物标志物发现的生物信息学分析.
主要成果:
- 基因组景观分析显示,单核酸变异和INDEL与现有队列相比较,验证了大规模测序.
- 由于技术偏差和样本大小,在副本数量变化 (CNV) 层面没有可比性.
- 在免疫检查点治疗患者中,PDGFRB,NOTCH3和RET的突变与改善的整体和无疾病生存率相关;NOTCH4变异是有害的.
结论:
- 基因组学驱动的试验提供了有价值的见解,并在先进的黑色素瘤研究中提出了挑战.
- 鉴定到的基因组变化可以作为免疫疗法和向治疗的潜在预测生物标志物.
- 这一队列为验证黑色素瘤治疗分层中的新型基因组生物标志物提供了宝贵的资源.
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