医学
黑色素瘤
免疫疗法
精密医学
临床试验
免疫检查点
仿形(计算机编程)
癌症免疫疗法
生物信息学
易普利姆玛
癌症
免疫系统
肿瘤科
计算生物学
内科学
免疫学
癌症研究
病理
计算机科学
生物
操作系统
作者
Tuba N. Gide,Yizhe Mao,Richard A. Scolyer,Georgina V. Long,James S. Wilmott
标识
DOI:10.1158/1078-0432.ccr-24-1109
摘要
Abstract Immunotherapies targeting the programmed cell death 1 (PD-1) and cytotoxic T lymphocyte antigen 4 (CTLA-4) checkpoint receptors have revolutionised the treatment of metastatic melanoma. However, half of treated patients do not respond to or eventually progress on standard therapies and many experience adverse events as a result of drug toxicity. The identification of accurate biomarkers of clinical outcomes are required in order to move away from the one-size-fits-all treatment approach of standard clinical practice, and towards a more personalised approach to enable the administration of the optimal therapy for any given patient and further improve patient outcomes. Recent clinical trials have proven the potential of multi-omics analyses, including genomic, gene expression, and tumour immune profiling, of patients’ tumour biopsies, to predict a patient’s response to subsequently administered immunotherapies. However, reproducibility of such multi-omics analyses, tissue requirements, and clinical validation have limited the practical application of these approaches in routine clinical workflows. In this review, we discuss several pivotal tissue-based profiling techniques that can be utilised to identify potential genomic, transcriptomic and immune biomarkers predictive of clinical outcomes following treatment with immune checkpoint inhibitors in melanoma. Furthermore, we highlight the key opportunities and challenges associated with the use of each of these techniques. The development and implementation of multimodal predictive models which combine data derived from these various methods is the future for achieving precision medicine for patients with melanoma.
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