Faculty of Biomedical Sciences, Institute of Oncology Research, USI, Bellinzona, TI, 6500, Switzerland.
Computational Oncology Unit, Department of Oncology, Istituto di Richerche Farmacologiche 'Mario Negri' IRCCS, 20156, Milano, Italy.
Nat Commun. 2021 Dec 2;12(1):7033. doi: 10.1038/s41467-021-26840-5.
Comprehensive genomic studies have delineated key driver mutations linked to disease progression for most cancers. However, corresponding transcriptional changes remain largely elusive because of the bias associated with cross-study analysis. Here, we overcome these hurdles and generate a comprehensive prostate cancer transcriptome atlas that describes the roadmap to tumor progression in a qualitative and quantitative manner. Most cancers follow a uniform trajectory characterized by upregulation of polycomb-repressive-complex-2, G2-M checkpoints, and M2 macrophage polarization. Using patient-derived xenograft models, we functionally validate our observations and add single-cell resolution. Thereby, we show that tumor progression occurs through transcriptional adaption rather than a selection of pre-existing cancer cell clusters. Moreover, we determine at the single-cell level how inhibition of EZH2 - the top upregulated gene along the trajectory - reverts tumor progression and macrophage polarization. Finally, a user-friendly web-resource is provided enabling the investigation of dynamic transcriptional perturbations linked to disease progression.
全面的基因组研究已经描绘出与大多数癌症疾病进展相关的关键驱动突变。然而，由于跨研究分析的偏差，相应的转录变化在很大程度上仍然难以捉摸。在这里，我们克服了这些障碍，生成了一个全面的前列腺癌转录组图谱，以定性和定量的方式描述了肿瘤进展的路线图。大多数癌症都遵循一个统一的轨迹，其特征是多梳抑制复合物 2、G2-M 检查点和 M2 巨噬细胞极化的上调。使用患者来源的异种移植模型，我们对我们的观察结果进行了功能验证，并增加了单细胞分辨率。由此，我们表明肿瘤进展是通过转录适应发生的，而不是选择预先存在的癌细胞簇。此外，我们在单细胞水平上确定了 EZH2 抑制（沿着轨迹上调最多的基因）如何逆转肿瘤进展和巨噬细胞极化。最后，提供了一个用户友好的网络资源，用于研究与疾病进展相关的动态转录扰动。
