Department of Dermatology, University of California, Davis, Sacramento, CA 95816, USA.
NanoString Technologies, a Bruker Company, Seattle, WA 98109, USA.
Sci Adv. 2024 Jul 12;10(28):eadm8206. doi: 10.1126/sciadv.adm8206.
Melanoma clinical outcomes emerge from incompletely understood genetic mechanisms operating within the tumor and its microenvironment. Here, we used single-cell RNA-based spatial molecular imaging (RNA-SMI) in patient-derived archival tumors to reveal clinically relevant markers of malignancy progression and prognosis. We examined spatial gene expression of 203,472 cells inside benign and malignant melanocytic neoplasms, including melanocytic nevi and primary invasive and metastatic melanomas. Algorithmic cell clustering paired with intratumoral comparative two-dimensional analyses visualized synergistic, spatial gene signatures linking cellular proliferation, metabolism, and malignancy, validated by protein expression. Metastatic niches included up-regulation of and , which independently predicted poor clinical outcome in 473 patients with melanoma via Cox regression analysis. More generally, our work demonstrates a framework for applying single-cell RNA-SMI technology toward identifying gene regulatory landscapes pertinent to cancer progression and patient survival.
黑色素瘤的临床结果源于肿瘤及其微环境中尚未完全理解的遗传机制。在这里，我们使用基于单细胞 RNA 的空间分子成像（RNA-SMI）在患者来源的存档肿瘤中进行研究，以揭示与恶性进展和预后相关的临床相关标志物。我们检查了良性和恶性黑素细胞肿瘤（包括黑素细胞痣和原发性侵袭性和转移性黑色素瘤）中 203472 个细胞的空间基因表达。通过算法细胞聚类和肿瘤内二维比较分析，可视化了与细胞增殖、代谢和恶性相关的协同空间基因特征，通过蛋白质表达进行了验证。转移龛中包括上调的 和 ，通过 Cox 回归分析，这两个基因在 473 名黑色素瘤患者中独立预测了不良的临床结局。更普遍地说，我们的工作展示了一种应用单细胞 RNA-SMI 技术识别与癌症进展和患者生存相关的基因调控景观的框架。
