Poletto Stefano, Paruzzo Luca, Nepote Alessandro, Caravelli Daniela, Sangiolo Dario, Carnevale-Schianca Fabrizio
Department of Oncology, University of Turin, AOU S. Luigi Gonzaga, 10043 Orbassano, Italy.
Department of Oncology, University of Turin, 10124 Turin, Italy.
Cancers (Basel). 2023 Dec 24;16(1):101. doi: 10.3390/cancers16010101.
The introduction of immunotherapy revolutionized the treatment landscape in metastatic melanoma. Despite the impressive results associated with immune checkpoint inhibitors (ICIs), only a portion of patients obtain a response to this treatment. In this scenario, the research of predictive factors is fundamental to identify patients who may have a response and to exclude patients with a low possibility to respond. These factors can be host-associated, immune system activation-related, and tumor-related. Patient-related factors can vary from data obtained by medical history (performance status, age, sex, body mass index, concomitant medications, and comorbidities) to analysis of the gut microbiome from fecal samples. Tumor-related factors can reflect tumor burden (metastatic sites, lactate dehydrogenase, C-reactive protein, and circulating tumor DNA) or can derive from the analysis of tumor samples (driver mutations, tumor-infiltrating lymphocytes, and myeloid cells). Biomarkers evaluating the immune system activation, such as IFN-gamma gene expression profile and analysis of circulating immune cell subsets, have emerged in recent years as significantly correlated with response to ICIs. In this manuscript, we critically reviewed the most updated literature data on the landscape of predictive factors in metastatic melanoma treated with ICIs. We focus on the principal limits and potentiality of different methods, shedding light on the more promising biomarkers.
免疫疗法的引入彻底改变了转移性黑色素瘤的治疗格局。尽管免疫检查点抑制剂（ICI）取得了令人瞩目的成果，但只有一部分患者对这种治疗有反应。在这种情况下，研究预测因素对于识别可能有反应的患者以及排除反应可能性低的患者至关重要。这些因素可分为宿主相关因素、免疫系统激活相关因素和肿瘤相关因素。患者相关因素范围广泛，从病史数据（体能状态、年龄、性别、体重指数、合并用药和合并症）到粪便样本的肠道微生物组分析。肿瘤相关因素可以反映肿瘤负荷（转移部位、乳酸脱氢酶、C反应蛋白和循环肿瘤DNA），也可以来自肿瘤样本分析（驱动基因突变、肿瘤浸润淋巴细胞和髓样细胞）。近年来，评估免疫系统激活的生物标志物，如γ-干扰素基因表达谱和循环免疫细胞亚群分析，已被发现与ICI反应显著相关。在本手稿中，我们批判性地回顾了关于ICI治疗转移性黑色素瘤预测因素领域的最新文献数据。我们关注不同方法的主要局限性和潜力，阐明更有前景的生物标志物。
