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Melanoma progression and prognostic models drawn from single-cell, spatial maps of benign and malignant tumors
Science Advances ( IF 11.7 ) Pub Date : 2024-07-12 , DOI: 10.1126/sciadv.adm8206 Nick R. Love 1 , Claire Williams 2 , Emily E. Killingbeck 2 , Alexander Merleev 1 , Mohammad Saffari Doost 1 , Lan Yu 1 , John D. McPherson 3 , Hidetoshi Mori 4 , Alexander D. Borowsky 4 , Emanual Maverakis 1 , Maija Kiuru 1, 4
Science Advances ( IF 11.7 ) Pub Date : 2024-07-12 , DOI: 10.1126/sciadv.adm8206 Nick R. Love 1 , Claire Williams 2 , Emily E. Killingbeck 2 , Alexander Merleev 1 , Mohammad Saffari Doost 1 , Lan Yu 1 , John D. McPherson 3 , Hidetoshi Mori 4 , Alexander D. Borowsky 4 , Emanual Maverakis 1 , Maija Kiuru 1, 4
Affiliation
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 CDK2 and FABP5 , 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.
中文翻译:
从良性和恶性肿瘤的单细胞空间图绘制的黑色素瘤进展和预后模型
黑色素瘤的临床结果源于肿瘤及其微环境中运作的不完全了解的遗传机制。在这里,我们在源自患者的档案肿瘤中使用基于单细胞 RNA 的空间分子成像 (RNA-SMI),以揭示恶性肿瘤进展和预后的临床相关标志物。我们检查了良性和恶性黑素细胞肿瘤(包括黑素细胞痣以及原发性侵袭性和转移性黑素瘤)内 203,472 个细胞的空间基因表达。算法细胞聚类与肿瘤内比较二维分析相结合,可视化了与细胞增殖、代谢和恶性肿瘤相关的协同空间基因特征,并通过蛋白质表达进行了验证。转移性生态位包括上调CDK2和FABP5 ,通过 Cox 回归分析独立预测了 473 名黑色素瘤患者的不良临床结果。更一般地说,我们的工作展示了一个应用单细胞 RNA-SMI 技术来识别与癌症进展和患者生存相关的基因调控景观的框架。
更新日期:2024-07-12
中文翻译:
![](https://scdn.x-mol.com/jcss/images/paperTranslation.png)
从良性和恶性肿瘤的单细胞空间图绘制的黑色素瘤进展和预后模型
黑色素瘤的临床结果源于肿瘤及其微环境中运作的不完全了解的遗传机制。在这里,我们在源自患者的档案肿瘤中使用基于单细胞 RNA 的空间分子成像 (RNA-SMI),以揭示恶性肿瘤进展和预后的临床相关标志物。我们检查了良性和恶性黑素细胞肿瘤(包括黑素细胞痣以及原发性侵袭性和转移性黑素瘤)内 203,472 个细胞的空间基因表达。算法细胞聚类与肿瘤内比较二维分析相结合,可视化了与细胞增殖、代谢和恶性肿瘤相关的协同空间基因特征,并通过蛋白质表达进行了验证。转移性生态位包括上调CDK2和FABP5 ,通过 Cox 回归分析独立预测了 473 名黑色素瘤患者的不良临床结果。更一般地说,我们的工作展示了一个应用单细胞 RNA-SMI 技术来识别与癌症进展和患者生存相关的基因调控景观的框架。