Tissue-based Profiling Techniques to Achieve Precision Medicine in Cancer: Opportunities and Challenges in Melanoma.

IF 10 1区 医学 Q1 ONCOLOGY
Tuba N Gide, Yizhe Mao, Richard A Scolyer, Georgina V Long, James S Wilmott
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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.

基于组织的分析技术实现癌症精准医疗:黑色素瘤的机遇与挑战。
针对程序性细胞死亡1(PD-1)和细胞毒性T淋巴细胞抗原4(CTLA-4)检查点受体的免疫疗法彻底改变了转移性黑色素瘤的治疗方法。然而,半数接受治疗的患者对标准疗法没有反应或最终病情恶化,许多患者还因药物毒性而出现不良反应。为了摒弃标准临床实践中 "一刀切 "的治疗方法,转而采用更加个性化的方法,以便为任何特定患者提供最佳疗法,并进一步改善患者的预后,需要对临床结果进行准确的生物标志物鉴定。最近的临床试验证明,对患者肿瘤活检组织进行多组学分析,包括基因组、基因表达和肿瘤免疫分析,可以预测患者对后续免疫疗法的反应。然而,此类多组学分析的可重复性、组织要求和临床验证限制了这些方法在常规临床工作流程中的实际应用。在本综述中,我们将讨论几种基于组织的关键分析技术,这些技术可用于鉴定黑色素瘤免疫检查点抑制剂治疗后预测临床结果的潜在基因组、转录组和免疫生物标记物。此外,我们还强调了与使用这些技术相关的主要机遇和挑战。开发和实施多模态预测模型,将从这些不同方法中获得的数据结合起来,是为黑色素瘤患者实现精准医疗的未来。
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来源期刊
Clinical Cancer Research
Clinical Cancer Research 医学-肿瘤学
CiteScore
20.10
自引率
1.70%
发文量
1207
审稿时长
2.1 months
期刊介绍: Clinical Cancer Research is a journal focusing on groundbreaking research in cancer, specifically in the areas where the laboratory and the clinic intersect. Our primary interest lies in clinical trials that investigate novel treatments, accompanied by research on pharmacology, molecular alterations, and biomarkers that can predict response or resistance to these treatments. Furthermore, we prioritize laboratory and animal studies that explore new drugs and targeted agents with the potential to advance to clinical trials. We also encourage research on targetable mechanisms of cancer development, progression, and metastasis.
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