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利用 Tumoroscope 进行肿瘤异质性的综合空间和基因组分析

Integrative spatial and genomic analysis of tumor heterogeneity with Tumoroscope.

机构信息

Faculty of Mathematics, Informatics and Mechanics, University of Warsaw, Warsaw, Poland.

Sorbonne Universite, CNRS, IBPS, Laboratoire de Biologie Computationnelle et Quantitative, Paris, France.

出版信息

Nat Commun. 2024 Oct 29;15(1):9343. doi: 10.1038/s41467-024-53374-3.

Abstract

Spatial and genomic heterogeneity of tumors are crucial factors influencing cancer progression, treatment, and survival. However, a technology for direct mapping the clones in the tumor tissue based on somatic point mutations is lacking. Here, we propose Tumoroscope, the first probabilistic model that accurately infers cancer clones and their localization in close to single-cell resolution by integrating pathological images, whole exome sequencing, and spatial transcriptomics data. In contrast to previous methods, Tumoroscope explicitly addresses the problem of deconvoluting the proportions of clones in spatial transcriptomics spots. Applied to a reference prostate cancer dataset and a newly generated breast cancer dataset, Tumoroscope reveals spatial patterns of clone colocalization and mutual exclusion in sub-areas of the tumor tissue. We further infer clone-specific gene expression levels and the most highly expressed genes for each clone. In summary, Tumoroscope enables an integrated study of the spatial, genomic, and phenotypic organization of tumors.

摘要

肿瘤的空间和基因组异质性是影响癌症进展、治疗和生存的关键因素。然而,目前缺乏一种基于体细胞点突变直接绘制肿瘤组织中克隆的技术。在这里,我们提出了 Tumoroscope,这是第一个概率模型,通过整合病理图像、全外显子测序和空间转录组学数据,能够以近乎单细胞分辨率准确推断癌症克隆及其定位。与之前的方法相比,Tumoroscope 明确解决了在空间转录组学点中去卷积克隆比例的问题。将 Tumoroscope 应用于参考前列腺癌数据集和新生成的乳腺癌数据集,揭示了肿瘤组织亚区中克隆共定位和相互排斥的空间模式。我们进一步推断了每个克隆的克隆特异性基因表达水平和表达量最高的基因。总之,Tumoroscope 能够实现对肿瘤的空间、基因组和表型组织的综合研究。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/574d/11522407/904039267c3b/41467_2024_53374_Fig1_HTML.jpg

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