Zhang Huarong, Wu Junling, Ji Daihan, Liu Yijuan, Lu Shuting, Lin Zeman, Chen Ting, Ao Lu
Key Laboratory of Ministry of Education for Gastrointestinal Cancer, The School of Basic Medical Sciences, Fujian Medical University, Fuzhou, China.
Fujian Key Laboratory of Medical Bioinformatics, Department of Bioinformatics, School of Medical Technology and Engineering, Fujian Medical University, Fuzhou, China.
Front Microbiol. 2022 Nov 3;13:1005201. doi: 10.3389/fmicb.2022.1005201. eCollection 2022.
The gut microbial dysbiosis is a risk of colorectal cancer (CRC) and some bacteria have been reported as potential markers for CRC diagnosis. However, heterogeneity among studies with different populations and technologies lead to inconsistent results. Here, we investigated six metagenomic profiles of stool samples from healthy controls (HC), colorectal adenoma (CA) and CRC, and six and four genera were consistently altered between CRC and HC or CA across populations, respectively. In FengQ cohort, which composed with 61 HC, 47 CA, and 46 CRC samples, a random forest (RF) model composed of the six genera, denoted as signature-HC, distinguished CRC from HC with an area under the curve (AUC) of 0.84. Similarly, another RF model composed of the four universal genera, denoted as signature-CA, discriminated CRC from CA with an AUC of 0.73. These signatures were further validated in five metagenomic sequencing cohorts and six independent 16S rRNA gene sequencing cohorts. Interestingly, three genera overlapped in the two models (, and ) were with very low abundance in HC and CA, but sharply increased in CRC. A concise RF model on the three genera distinguished CRC from HC or CA with AUC of 0.87 and 0.67, respectively. Functional gene family analysis revealed that Kyoto Encyclopedia of Genes and Genomes Orthogroups categories which were significantly correlated with markers in signature-HC and signature-CA were mapped into pathways related to lipopolysaccharide and sulfur metabolism, which might be vital risk factors of CRC development. Conclusively, our study identified universal bacterial markers across populations and technologies as potential aids in non-invasive diagnosis of CRC.
肠道微生物群失调是结直肠癌（CRC）的一个风险因素，一些细菌已被报道为CRC诊断的潜在标志物。然而，不同人群和技术的研究之间的异质性导致结果不一致。在此，我们研究了来自健康对照（HC）、结直肠腺瘤（CA）和CRC的粪便样本的六个宏基因组图谱，并且在不同人群中，分别有六个和四个属在CRC与HC或CA之间持续发生改变。在由61例HC、47例CA和46例CRC样本组成的FengQ队列中，由这六个属组成的随机森林（RF）模型（记为signature-HC）区分CRC与HC的曲线下面积（AUC）为0.84。同样，另一个由四个普遍存在的属组成的RF模型（记为signature-CA）区分CRC与CA的AUC为0.73。这些标志物在五个宏基因组测序队列和六个独立的16S rRNA基因测序队列中得到了进一步验证。有趣的是，在两个模型中重叠的三个属（、和）在HC和CA中的丰度非常低，但在CRC中急剧增加。基于这三个属的一个简洁RF模型区分CRC与HC或CA的AUC分别为0.87和0.67。功能基因家族分析表明，与signature-HC和signature-CA中的标志物显著相关的京都基因与基因组百科全书直系同源组类别被映射到与脂多糖和硫代谢相关的途径中，这可能是CRC发生的重要风险因素。总之，我们的研究确定了跨人群和技术的普遍细菌标志物，作为CRC非侵入性诊断的潜在辅助手段。
