Determining cell type abundance and expression from bulk tissues with digital cytometry.,Nature Biotechnology

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Determining cell type abundance and expression from bulk tissues with digital cytometry.
Nature Biotechnology ( IF 33.1 ) Pub Date : 2019-05-06 , DOI: 10.1038/s41587-019-0114-2
Aaron M Newman _{1,

2} , Chloé B Steen _{3,

4} , Chih Long Liu _{1,

3} , Andrew J Gentles _{2,

3,

5,

6} , Aadel A Chaudhuri _{7,

8} , Florian Scherer _{3,

9} , Michael S Khodadoust ₃ , Mohammad S Esfahani _{3,

5,

8} , Bogdan A Luca ₆ , David Steiner ₃ , Maximilian Diehn _{1,

6,

8} , Ash A Alizadeh _{1,

3,

5,

8,

9}

Affiliation

Single-cell RNA-sequencing has emerged as a powerful technique for characterizing cellular heterogeneity, but it is currently impractical on large sample cohorts and cannot be applied to fixed specimens collected as part of routine clinical care. We previously developed an approach for digital cytometry, called CIBERSORT, that enables estimation of cell type abundances from bulk tissue transcriptomes. We now introduce CIBERSORTx, a machine learning method that extends this framework to infer cell-type-specific gene expression profiles without physical cell isolation. By minimizing platform-specific variation, CIBERSORTx also allows the use of single-cell RNA-sequencing data for large-scale tissue dissection. We evaluated the utility of CIBERSORTx in multiple tumor types, including melanoma, where single-cell reference profiles were used to dissect bulk clinical specimens, revealing cell-type-specific phenotypic states linked to distinct driver mutations and response to immune checkpoint blockade. We anticipate that digital cytometry will augment single-cell profiling efforts, enabling cost-effective, high-throughput tissue characterization without the need for antibodies, disaggregation or viable cells.

中文翻译：

用数字细胞仪确定大块组织中的细胞类型丰度和表达。

单细胞 RNA 测序已成为表征细胞异质性的强大技术，但目前在大样本队列中不切实际，并且不能应用于作为常规临床护理的一部分收集的固定标本。我们之前开发了一种称为 CIBERSORT 的数字细胞计数方法，该方法能够估计来自大量组织转录组的细胞类型丰度。我们现在介绍 CIBERSORTx，这是一种机器学习方法，可扩展该框架以推断细胞类型特异性基因表达谱，而无需物理细胞分离。通过最小化平台特定的变化，CIBERSORTx 还允许使用单细胞 RNA 测序数据进行大规模组织解剖。我们评估了 CIBERSORTx 在多种肿瘤类型中的效用，包括黑色素瘤、其中单细胞参考谱用于解剖大量临床标本，揭示与不同驱动突变和对免疫检查点阻断反应相关的细胞类型特异性表型状态。我们预计数字细胞仪将增强单细胞分析工作，实现具有成本效益的高通量组织表征，而无需抗体、解聚或活细胞。

更新日期：2019-05-16

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