Lo Yu-Chen, Liu Yuxuan, Kammersgaard Marte, Koladiya Abhishek, Keyes Timothy J, Davis Kara L
Department of Pediatrics, Division of Hematology, Oncology, Stem Cell Transplant and Regenerative Medicine, Stanford University, Stanford, CA, USA.
Medical Scientist Training Program, Stanford University School of Medicine, Stanford, CA, USA.
Semin Immunopathol. 2023 Jan;45(1):61-69. doi: 10.1007/s00281-022-00981-1. Epub 2023 Jan 10.
Childhood cancer is the second leading cause of death in children aged 1 to 14. Although survival rates have vastly improved over the past 40 years, cancer resistance and relapse remain a significant challenge. Advances in single-cell technologies enable dissection of tumors to unprecedented resolution. This facilitates unraveling the heterogeneity of childhood cancers to identify cell subtypes that are prone to treatment resistance. The rapid accumulation of single-cell data from different modalities necessitates the development of novel computational approaches for processing, visualizing, and analyzing single-cell data. Here, we review single-cell approaches utilized or under development in the context of childhood cancers. We review computational methods for analyzing single-cell data and discuss best practices for their application. Finally, we review the impact of several studies of childhood tumors analyzed with these approaches and future directions to implement single-cell studies into translational cancer research in pediatric oncology.
儿童癌症是1至14岁儿童死亡的第二大主要原因。尽管在过去40年里生存率有了大幅提高，但癌症耐药性和复发仍然是一个重大挑战。单细胞技术的进步使肿瘤剖析达到了前所未有的分辨率。这有助于揭示儿童癌症的异质性，以识别易于产生治疗耐药性的细胞亚型。来自不同模式的单细胞数据的快速积累，使得开发用于处理、可视化和分析单细胞数据的新型计算方法成为必要。在这里，我们回顾了在儿童癌症背景下已使用或正在开发的单细胞方法。我们回顾了分析单细胞数据的计算方法，并讨论了其应用的最佳实践。最后，我们回顾了几项用这些方法分析儿童肿瘤的研究的影响，以及将单细胞研究应用于儿科肿瘤转化癌症研究的未来方向。
