使用PRISM可靠检测癌症中的宿主微生物特征
Bassel Ghaddar1, Martin J Blaser2, Subhajyoti De3
1Center for Systems and Computational Biology, Rutgers Cancer Institute, Rutgers University, 195 Albany Street, New Brunswick, NJ 08901, USA; Hospital of the University of Pennsylvania, Philadelphia, PA 19104, USA.
Cancer cell
|February 6, 2026
概括
这项研究介绍了PRISM,这是一种用于在人类基因组数据中准确检测微生物的计算工具,特别是来自低生物质样本的样本. PRISM提高了癌症微生物组分析的可靠性,并识别了与癌症和宿主途径相关的微生物特征.
科学领域:
- 计算生物学是一种计算生物学.
- 微生物组研究的研究.
- 癌症基因组学 癌症基因组学
背景情况:
- 癌症微生物组领域面临着从人类基因组数据中可靠检测微生物的挑战.
- 低生物质样本往往产生模两可的结果,导致争议.
- 准确识别微生物对于了解癌症的发展和治疗至关重要.
研究的目的:
- 开发一个高效的计算框架,PRISM,用于从低生物质测序数据中精确识别和消毒微生物.
- 在各种数据集上对PRISM的性能进行基准测试.
- 应用PRISM来分析各种癌症类型的癌症微生物群签名.
主要方法:
- 开发PRISM,一个高效的微生物识别和消毒计算框架.
- 在已知微生物种群的230个独立数据集上对PRISM进行基准测试.
- 使用癌症基因组图谱和临床蛋白质瘤分析联盟的数据,分析了25种癌症类型.
主要成果:
- 在微生物检测和消毒方面,PRISM表现出强大的性能.
- 在胃肠道,头和尿路瘤中发现了一致的微生物特征.
- 在胰腺癌中,微生物检测与改变宿主蛋白质糖化和吸烟暴露相关.
结论:
- PRISM显著提高了从人类基因组数据中微生物分析的可靠性.
- 该框架允许利用现有的基因组数据进行并发宿主微生物特征检测.
- 这些发现表明,宿主微生物相互作用在癌症中的潜在分子和临床意义.
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