Single-cell RNA-seq of melanoma ecosystems reveals sources of T cells exclusion linked to immunotherapy clinical outcomes

Immune checkpoint inhibitors (ICI) produce durable responses in some melanoma patients, but many patients derive no clinical benefit, and the molecular underpinnings of such resistance remain elusive. Here, we leveraged single-cell RNA-seq (scRNA-seq) from 31 melanoma tumors and novel computational methods to interrogate malignant cell states that promote immune evasion. We identified a resistance program expressed by malignant cells that is associated with T cell exclusion and immune evasion. The program is present prior to immunotherapy, characterizes cold niches, and predicts clinical responses to anti-PD-1 therapy in an independent cohort of 112 melanoma patients. CDK4/6-inhibition represses this program in individual malignant cells, induces senescence, and reduces melanoma tumor outgrowth in a mouse model when given in combination with immunotherapy. Our study provides a high-resolution landscape of ICI resistant cell states, identifies clinically predictive signatures, and forms a basis for the development of novel therapeutic strategies that could overcome immunotherapy resistance.

免疫检查点抑制剂（Immune Checkpoint Inhibitors, ICI）可使部分黑色素瘤患者获得持久临床应答，但多数患者无法获得临床获益，此类耐药的分子机制仍尚不明确。本研究利用31例黑色素瘤肿瘤的单细胞RNA测序（single-cell RNA-seq, scRNA-seq）数据与新型计算方法，探究了促进免疫逃逸的恶性细胞状态。我们鉴定出一类由恶性细胞表达的耐药程序，该程序与T细胞排斥及免疫逃逸密切相关。该程序早在免疫治疗前即已存在，是免疫冷龛的标志性特征，并可在112例黑色素瘤患者组成的独立队列中预测抗PD-1治疗的临床应答情况。CDK4/6靶向抑制可在单个恶性细胞中抑制该程序的表达、诱导细胞衰老，且在小鼠模型中联合免疫治疗可减缓黑色素瘤的肿瘤生长。本研究绘制了ICI耐药细胞状态的高分辨率图谱，鉴定出具有临床预测价值的特征集，为开发可克服免疫治疗耐药的新型治疗策略奠定了基础。

搜集汇总

背景与挑战

背景概述

该数据集包含31个黑色素瘤肿瘤的单细胞RNA测序数据，研究恶性细胞状态如何促进免疫逃逸，并识别了一个与T细胞排斥和免疫逃逸相关的抵抗程序。该程序能够预测抗PD-1治疗的临床反应，且CDK4/6抑制可以抑制这一程序。