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炎症和载脂蛋白可能是皮肤黑色素瘤患者免疫治疗和靶向治疗分层的潜在生物标志物。

Inflammation and Apolipoproteins Are Potential Biomarkers for Stratification of Cutaneous Melanoma Patients for Immunotherapy and Targeted Therapy.

机构信息

Science for Life Laboratory, KTH Royal Institute of Technology, Stockholm, Sweden.

Department of Oncology-Pathology, Karolinska Institutet, Stockholm, Sweden.

出版信息

Cancer Res. 2021 May 1;81(9):2545-2555. doi: 10.1158/0008-5472.CAN-20-2000. Epub 2021 Feb 11.

DOI:10.1158/0008-5472.CAN-20-2000
PMID:33574091
Abstract

Malignant cutaneous melanoma is one of the most common cancers in young adults. During the last decade, targeted and immunotherapies have significantly increased the overall survival of patients with malignant cutaneous melanoma. Nevertheless, disease progression is common, and a lack of predictive biomarkers of patient response to therapy hinders individualized treatment strategies. To address this issue, we performed a longitudinal study using an unbiased proteomics approach to identify and quantify proteins in plasma both before and during treatment from 109 patients treated with either targeted or immunotherapy. Linear modeling and machine learning approaches identified 43 potential prognostic and predictive biomarkers. A reverse correlation between apolipoproteins and proteins related to inflammation was observed. In the immunotherapy group, patients with low pretreatment expression of apolipoproteins and high expression of inflammation markers had shorter progression-free survival. Similarly, increased expression of during treatment elicited a significant impact on response to immunotherapy. Overall, we identified potential common and treatment-specific biomarkers in malignant cutaneous melanoma, paving the way for clinical use of these biomarkers following validation on a larger cohort. SIGNIFICANCE: This study identifies a potential biomarker panel that could improve the selection of therapy for patients with cutaneous melanoma.

摘要

皮肤恶性黑色素瘤是青年人中最常见的癌症之一。在过去十年中,靶向治疗和免疫疗法显著提高了皮肤恶性黑色素瘤患者的总体生存率。然而,疾病进展是常见的,缺乏预测患者对治疗反应的生物标志物阻碍了个体化治疗策略的制定。为了解决这个问题,我们进行了一项纵向研究,使用无偏蛋白质组学方法来鉴定和定量 109 名接受靶向或免疫治疗的患者治疗前后血浆中的蛋白质。线性建模和机器学习方法鉴定出 43 个有潜在预后和预测价值的生物标志物。我们观察到载脂蛋白和与炎症相关的蛋白质之间存在反向相关性。在免疫治疗组中,预处理时载脂蛋白表达水平低、炎症标志物表达水平高的患者无进展生存期更短。同样,治疗期间 表达增加对免疫治疗的反应产生了显著影响。总的来说,我们在皮肤恶性黑色素瘤中鉴定出了潜在的通用和治疗特异性生物标志物,为这些生物标志物在更大队列上的验证后临床应用铺平了道路。意义:本研究确定了一个潜在的生物标志物面板,可改善对皮肤黑色素瘤患者的治疗选择。

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