Jones Daniel C, Elz Anna E, Hadadianpour Azadeh, Ryu Heeju, Glass David R, Newell Evan W
Vaccine and Infectious Disease Division, Fred Hutchinson Cancer Center, Seattle, WA, USA.
Immunotherapy Integrated Research Center, Fred Hutchinson Cancer, Seattle, WA, USA.
Nat Methods. 2025 May 22. doi: 10.1038/s41592-025-02697-0.
Single-cell spatial transcriptomics promises a highly detailed view of a cell's transcriptional state and microenvironment, yet inaccurate cell segmentation can render these data murky by misattributing large numbers of transcripts to nearby cells or conjuring nonexistent cells. We adopt methods from ab initio cell simulation, in a method called Proseg (probabilistic segmentation), to rapidly infer morphologically plausible cell boundaries. Benchmarking applied to datasets generated by three commercial platforms shows superior performance and computational efficiency of Proseg when compared to existing methods. We show that improved accuracy in cell segmentation aids greatly in detection of difficult-to-segment tumor-infiltrating immune cells such as neutrophils and T cells. Last, through improvements in our ability to delineate subsets of tumor-infiltrating T cells, we show that CXCL13-expressing CD8 T cells tend to be more closely associated with tumor cells than their CXCL13-negative counterparts in data generated from samples from patients with renal cell carcinoma.
单细胞空间转录组学有望提供细胞转录状态和微环境的高度详细视图，但不准确的细胞分割可能会将大量转录本错误地归因于附近细胞或虚构不存在的细胞，从而使这些数据变得模糊不清。我们采用从头开始的细胞模拟方法，即一种名为Proseg（概率分割）的方法，来快速推断形态上合理的细胞边界。应用于三个商业平台生成的数据集的基准测试表明，与现有方法相比，Proseg具有卓越的性能和计算效率。我们表明，细胞分割准确性的提高极大地有助于检测难以分割的肿瘤浸润免疫细胞，如中性粒细胞和T细胞。最后，通过提高我们描绘肿瘤浸润性T细胞亚群的能力，我们表明，在肾细胞癌患者样本生成的数据中，表达CXCL13的CD8 T细胞比不表达CXCL13的CD8 T细胞往往与肿瘤细胞联系更紧密。
