Suppr超能文献

原发性黑色素瘤 T 细胞的分子分析可识别有转移复发风险的患者。

Molecular analysis of primary melanoma T cells identifies patients at risk for metastatic recurrence.

机构信息

Department of Dermatology and Harvard Medical School, Brigham and Women's Hospital, Boston, MA, USA.

Department of Dermatology, University of Luebeck, Luebeck, Germany.

出版信息

Nat Cancer. 2020 Feb;1(2):197-209. doi: 10.1038/s43018-019-0019-5. Epub 2020 Jan 20.

Abstract

Primary melanomas >1 mm thickness are potentially curable by resection, but can recur metastatically. We assessed the prognostic value of T cell fraction (TCFr) and repertoire T cell clonality, measured by high-throughput-sequencing of the T cell receptor beta chain (TRB) in T2-T4 primary melanomas (n=199). TCFr accurately predicted progression-free survival (PFS) and was independent of thickness, ulceration, mitotic rate, or age. TCFr was second only to tumor thickness in its predictive value, using a gradient boosted model. For accurate PFS prediction, adding TCFr to tumor thickness was superior to adding any other histopathological variable. Furthermore, a TCFr >20% was protective regardless of tumor ulceration status, mitotic rate or presence of nodal disease. TCFr is a quantitative molecular assessment that predicts metastatic recurrence in primary melanoma patients whose disease has been resected surgically. This study suggests that a successful T cell-mediated antitumor response can be present in primary melanomas.

摘要

原发黑色素瘤厚度>1 毫米可以通过手术切除治愈,但可能会转移复发。我们评估了 T 细胞分数(TCFr)和 T 细胞受体β链(TRB)高通量测序测量的 T 细胞克隆性在 T2-T4 期原发性黑色素瘤(n=199)中的预后价值。TCFr 可准确预测无进展生存期(PFS),与厚度、溃疡、有丝分裂率或年龄无关。使用梯度提升模型,TCFr 在预测价值方面仅次于肿瘤厚度。为了准确预测 PFS,将 TCFr 添加到肿瘤厚度中优于添加任何其他组织病理学变量。此外,TCFr >20% 无论肿瘤溃疡状态、有丝分裂率或是否存在淋巴结疾病均具有保护作用。TCFr 是一种定量分子评估,可以预测已接受手术切除的原发性黑色素瘤患者的转移复发。本研究表明,在原发性黑色素瘤中可能存在成功的 T 细胞介导的抗肿瘤反应。

相似文献

引用本文的文献

本文引用的文献

6
Melanoma Immunotherapy: Next-Generation Biomarkers.黑色素瘤免疫疗法:新一代生物标志物
Front Oncol. 2018 May 29;8:178. doi: 10.3389/fonc.2018.00178. eCollection 2018.

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验