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空间分辨转录组学可解析 III 期皮肤恶性黑色素瘤的遗传异质性。

Spatially Resolved Transcriptomics Enables Dissection of Genetic Heterogeneity in Stage III Cutaneous Malignant Melanoma.

机构信息

Department of Gene Technology, KTH Royal Institute of Technology, SciLifeLab, Stockholm, Sweden.

Department of Oncology-Pathology, Karolinska Institutet, SE-17176 Stockholm, Sweden.

出版信息

Cancer Res. 2018 Oct 15;78(20):5970-5979. doi: 10.1158/0008-5472.CAN-18-0747. Epub 2018 Aug 28.

Abstract

Cutaneous malignant melanoma (melanoma) is characterized by a high mutational load, extensive intertumoral and intratumoral genetic heterogeneity, and complex tumor microenvironment (TME) interactions. Further insights into the mechanisms underlying melanoma are crucial for understanding tumor progression and responses to treatment. Here we adapted the technology of spatial transcriptomics (ST) to melanoma lymph node biopsies and successfully sequenced the transcriptomes of over 2,200 tissue domains. Deconvolution combined with traditional approaches for dimensional reduction of transcriptome-wide data enabled us to both visualize the transcriptional landscape within the tissue and identify gene expression profiles linked to specific histologic entities. Our unsupervised analysis revealed a complex spatial intratumoral composition of melanoma metastases that was not evident through morphologic annotation. Each biopsy showed distinct gene expression profiles and included examples of the coexistence of multiple melanoma signatures within a single tumor region as well as shared profiles for lymphoid tissue characterized according to their spatial location and gene expression profiles. The lymphoid area in close proximity to the tumor region displayed a specific expression pattern, which may reflect the TME, a key component to fully understanding tumor progression. In conclusion, using the ST technology to generate gene expression profiles reveals a detailed landscape of melanoma metastases. This should inspire researchers to integrate spatial information into analyses aiming to identify the factors underlying tumor progression and therapy outcome. Applying ST technology to gene expression profiling in melanoma lymph node metastases reveals a complex transcriptional landscape in a spatial context, which is essential for understanding the multiple components of tumor progression and therapy outcome. .

摘要

皮肤恶性黑色素瘤(黑色素瘤)的特征是突变负荷高、广泛的肿瘤间和肿瘤内遗传异质性以及复杂的肿瘤微环境(TME)相互作用。进一步深入了解黑色素瘤的发生机制对于理解肿瘤进展和对治疗的反应至关重要。在这里,我们将空间转录组学(ST)技术应用于黑色素瘤淋巴结活检,并成功地对超过 2200 个组织区域的转录组进行了测序。去卷积结合转录组数据的传统降维方法,使我们能够可视化组织内的转录景观,并确定与特定组织学实体相关的基因表达谱。我们的无监督分析揭示了黑色素瘤转移的复杂空间肿瘤内组成,这通过形态学注释是不明显的。每个活检都显示出独特的基因表达谱,并包括在单个肿瘤区域内共存多个黑色素瘤特征的例子,以及根据其空间位置和基因表达谱特征的共同特征的淋巴组织。与肿瘤区域紧密相邻的淋巴区域显示出特定的表达模式,这可能反映了 TME,这是全面理解肿瘤进展的关键组成部分。总之,使用 ST 技术生成基因表达谱揭示了黑色素瘤转移的详细景观。这应该激发研究人员将空间信息整合到旨在识别肿瘤进展和治疗结果背后因素的分析中。将 ST 技术应用于黑色素瘤淋巴结转移的基因表达谱分析揭示了一种复杂的转录景观,这对于理解肿瘤进展和治疗结果的多个组成部分至关重要。

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