Identification of multiple genomic alterations and prediction of neoantigens from circulating tumor cells at the single-cell level

Xiaochen Gao, Xinyu Li, Weize Xu, Ming Jiao, Yu Guo, Jiajia Wang, Weihao Wang, Jiling Feng, Qianqian Guo, Chengchao Wu, Taiyu Zhang, Yuqin Yang () and Da Lin ()
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Xiaochen Gao: Shanghai Jiao Tong University School of Medicine
Xinyu Li: Shanghai Jiao Tong University School of Medicine
Weize Xu: Huazhong Agricultural University
Ming Jiao: Shanghai Jiao Tong University School of Medicine
Yu Guo: Shanghai Jiao Tong University School of Medicine
Jiajia Wang: Shanghai Jiao Tong University School of Medicine
Weihao Wang: Shanghai Jiao Tong University School of Medicine
Jiling Feng: Shanghai Jiao Tong University School of Medicine
Qianqian Guo: Shanghai Jiao Tong University School of Medicine
Chengchao Wu: Affiliated Hospital of Guangdong Medical University
Taiyu Zhang: Shanghai Jiao Tong University School of Medicine
Yuqin Yang: Shanghai Jiao Tong University School of Medicine
Da Lin: Shanghai Jiao Tong University School of Medicine

Nature Communications, 2025, vol. 16, issue 1, 1-15

Abstract: Abstract Circulating tumor cells (CTCs) are linked to cancer progression and poor prognosis, offering valuable genetic insights into tumors. Accurate detection of genomic alterations in CTCs is essential for improving cancer diagnosis and treatment. To address this, we develop Uniform Chromosome Conformation Capture (Uni-C), a method for profiling 3D chromatin architecture and genomic alterations at the single-cell level. Using Uni-C, we analyze CTCs from pancreatic cancer patient-derived xenograft (PDX) and spontaneous tumor mouse models. In the PDX model, integrating data from seven CTCs captures 88.7% of SNPs and INDELs, and 75.0% of structural variants present in tumor tissue. These findings indicate that variants detected in CTCs reflect tumor genomic features. Notably, we observe chromatin conformation differences between mitotic and interphase CTCs, suggesting potential markers of cell vitality. In the spontaneous tumor model, we identify driver gene mutations in CTCs and predict neoantigens, advancing early cancer detection and treatment strategies.

Date: 2025
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DOI: 10.1038/s41467-025-62215-w

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