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肿瘤诱导血小板转录组学的去卷积揭示了激活的血小板和炎症细胞的转录特征。

Deconvolution of the tumor-educated platelet transcriptome reveals activated platelet and inflammatory cell transcript signatures.

机构信息

Department of Radiation Oncology, NYU Grossman School of Medicine, New York, New York, USA.

Department of Radiation Oncology, Keck School of Medicine of University of Southern California, Los Angeles, California, USA.

出版信息

JCI Insight. 2024 Aug 27;9(19):e178719. doi: 10.1172/jci.insight.178719.

Abstract

Tumor-educated platelets (TEPs) are a potential method of liquid biopsy for the diagnosis and monitoring of cancer. However, the mechanism underlying tumor education of platelets is not known, and transcripts associated with TEPs are often not tumor-associated transcripts. We demonstrated that direct tumor transfer of transcripts to circulating platelets is an unlikely source of the TEP signal. We used CDSeq, a latent Dirichlet allocation algorithm, to deconvolute the TEP signal in blood samples from patients with glioblastoma. We demonstrated that a substantial proportion of transcripts in the platelet transcriptome are derived from nonplatelet cells, and the use of this algorithm allows the removal of contaminant transcripts. Furthermore, we used the results of this algorithm to demonstrate that TEPs represent a subset of more activated platelets, which also contain transcripts normally associated with nonplatelet inflammatory cells, suggesting that these inflammatory cells, possibly in the tumor microenvironment, transfer transcripts to platelets that are then found in circulation. Our analysis suggests a useful and efficient method of processing TEP transcriptomic data to enable the isolation of a unique TEP signal associated with specific tumors.

摘要

肿瘤教育血小板(TEP)是一种用于癌症诊断和监测的潜在液体活检方法。然而,血小板肿瘤教育的机制尚不清楚,与 TEP 相关的转录本通常不是肿瘤相关的转录本。我们证明,直接向循环血小板转移转录本不太可能是 TEP 信号的来源。我们使用 CDSeq(一种潜在狄利克雷分配算法)来分解胶质母细胞瘤患者血液样本中的 TEP 信号。我们证明血小板转录组中的很大一部分转录本来自非血小板细胞,并且该算法的使用可以去除污染的转录本。此外,我们使用该算法的结果证明,TEP 代表更活跃的血小板亚群,其中还包含通常与非血小板炎性细胞相关的转录本,这表明这些炎性细胞(可能在肿瘤微环境中)将转录本转移到随后在循环中发现的血小板。我们的分析表明,这是一种有用且高效的处理 TEP 转录组数据的方法,可用于分离与特定肿瘤相关的独特 TEP 信号。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7525/11466191/cbf6980e42c7/jciinsight-9-178719-g050.jpg

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