Single-Cell Profiling of Cutaneous T-Cell Lymphoma Reveals Underlying Heterogeneity Associated with Disease Progression
Single-Cell Profiling of Cutaneous T-Cell Lymphoma Reveals Underlying Heterogeneity Associated with Disease Progression
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DOI：
10.1158/1078-0432.ccr-18-3309
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发表时间：
2019-05-15
影响因子：
11.5
通讯作者：
Jabbari, Ali
中科院分区：
文献类型：
--
作者：
Borcherding, Nicholas;Voigt, Andrew P.;Jabbari, Ali
目的：皮肤T细胞淋巴瘤（CTCL），包括一系列涉及皮肤的T细胞淋巴增生性疾病，在过去的40年中发病率集体增加。Sezary综合征是一种侵袭性CTCL，其特征在于血液和皮肤中存在大量恶性细胞。Sezary综合征的预后反映了缺乏可靠有效的治疗，部分原因是对疾病发病机制的不完全理解。实验设计：使用单细胞RNA测序和Monocle软件包中的机器学习反向图嵌入方法，我们定义了一个具有不同转录组状态的模型。用于区分独特的转录状态的基因表达被进一步用于开发早期与晚期CTCL diseases.Results：我们的分析显示FOXP3（+）恶性T细胞参与克隆进化，从FOXP3（+）T细胞转变为GATA 3（+）或IKZF 2（+）（HELIOS）肿瘤细胞。克隆性肿瘤中的转录组学差异可用于预测疾病阶段，我们能够表征预测疾病阶段的基因特征，准确率接近80%。FOXP3被认为是最重要的因素，以预测早期疾病的CTCL，沿着与其他19个基因用于预测CTCL stage.Conclusions：这项工作提供了深入了解塞扎里综合征的异质性，提供更好的理解内的克隆性肿瘤的转录组学的差异。这种转录异质性可以预测肿瘤的分期，从而为治疗提供指导。
Purpose: Cutaneous T-cell lymphomas (CTCL), encompassing a spectrum of T-cell lymphoproliferative disorders involving the skin, have collectively increased in incidence over the last 40 years. Sezary syndrome is an aggressive form of CTCL characterized by significant presence of malignant cells in both the blood and skin. The guarded prognosis for Sezary syndrome reflects a lack of reliably effective therapy, due, in part, to an incomplete understanding of disease pathogenesis.Experimental Design: Using single-cell sequencing of RNA and the machine-learning reverse graph embedding approach in the Monocle package, we defined a model featuring distinct transcriptomic states within Sezary syndrome. Gene expression used to differentiate the unique transcriptional states were further used to develop a boosted tree classification for early versus late CTCL disease.Results: Our analysis showed the involvement of FOXP3(+) malignant T cells during clonal evolution, transitioning from FOXP3(+) T cells to GATA3(+) or IKZF2(+) (HELIOS) tumor cells. Transcriptomic diversities in a clonal tumor can be used to predict disease stage, and we were able to characterize a gene signature that predicts disease stage with close to 80% accuracy. FOXP3 was found to be the most important factor to predict early disease in CTCL, along with another 19 genes used to predict CTCL stage.Conclusions: This work offers insight into the heterogeneity of Sezary syndrome, providing better understanding of the transcriptomic diversities within a clonal tumor. This transcriptional heterogeneity can predict tumor stage and thereby offer guidance for therapy.