罗格斯大学Subhajyoti De小组的研究开发出了利用PRISM可靠检测癌症宿主-微生物特征。相关论文发表在2026年2月5日出版的《癌细胞》杂志上。

研究小组开发了PRISM，这是一个高效的计算框架，用于精确的微生物鉴定和从低生物量测序数据中去除污染。PRISM在230个具有已知真阳性和污染物分类群的独立数据集上进行基准测试时达到了最佳性能。然后，研究小组将PRISM用于分析来自癌症基因组图谱和临床蛋白质组学肿瘤分析联盟的25种癌症类型。研究小组在胃肠道、头颈部和泌尿生殖道肿瘤中发现了一致的微生物特征，而在其他地方发现了稀疏的信号。

在胰腺癌中，课题组研究人员将微生物检测与宿主蛋白糖基化途径的改变和更大的吸烟暴露联系起来。最后，研究组考虑了测序方法对正面和负面数据解释的影响。总体而言，PRISM提高了微生物谱分析的可靠性，并允许利用现有的人类基因组数据同时检测具有潜在分子和临床意义的宿主-微生物特征。

据介绍，最近在癌症微生物组领域的争议强调了从人类基因组数据中进行更可靠的微生物检测的必要性。

附：英文原文

Title: Reliable detection of Host-Microbe Signatures in cancer using PRISM

Author: Bassel Ghaddar, Martin J. Blaser, Subhajyoti De

Issue&Volume: 2026-02-05

Abstract: Recent controversy in the cancer microbiome field highlights the need for more reliable microbial detection from human genomic data. Here, we develop PRISM, an efficient computational framework for precise microorganism identification and decontamination from low-biomass sequencing data. PRISM achieves robust performance when benchmarked on 230 independent datasets with known true-positive and contaminant taxa. We then use PRISM to profile 25 cancer types from The Cancer Genome Atlas and Clinical Proteomic Tumor Analysis Consortium. We identify consistent microbial signatures in gastrointestinal tract, head-and-neck, and urogenital tract tumors, and sparse signal elsewhere. In pancreatic cancer, we associate microbial detection with altered host protein glycosylation pathways and greater smoking exposure. Lastly, we consider the impact of sequencing approaches on positive and negative data interpretation. Overall, PRISM improves the reliability of microbial profiling and allows leveraging of existing human genomic data for the concurrent detection of host-microbial signatures with potential molecular and clinical significance.

DOI: 10.1016/j.ccell.2026.01.007

Source: https://www.cell.com/cancer-cell/abstract/S1535-6108(26)00046-2