Li Jun, Zhu Yanyun, Chang Qing, Gong Yuan, Wan Jun, Xu Shiping
Department of Gastroenterology, Second Medical Center, Chinese People's Liberation Army General Hospital, Beijing, China.
Department of Oncology, First Medical Center, Chinese People's Liberation Army General Hospital, Beijing, China.
Pol J Microbiol. 2025 Mar 26;74(1):71-81. doi: 10.33073/pjm-2025-006. eCollection 2025 Mar 1.
Alteration of the gut microbiota (GM) is associated with various diseases, including colorectal cancer (CRC). With the development of next-generation sequencing techniques, metagenomic sequencing, along with metabolic function and antibiotic-resistant gene analyses, has been used to investigate differences in GM between CRC patients and healthy controls. Fecal samples were obtained from seven CRC patients and six healthy subjects, and the sequencing data were analyzed for similarity, a-diversity, principal component analysis (PCA), and linear discriminant analyses (LDA). Regarding Actinobacteria, 3 orders, 5 families, 9 genera, and 19 species were identified with no differences between the CRC and control groups, while the levels of and were higher, and the level of was lower in the CRC group compared to the healthy controls ( = 0.053). Otherwise, 2 genera ( and ) and 7 species of bacteria (, unclassified ) were found to be significantly differently distributed between CRC patients and healthy controls. PCA-LDA successfully classified these 2 groups with satisfactory accuracy (84.52% for metabolic function and 77.38% for resistant genes). These findings underscore the potential of GM as a diagnostic tool for CRC, offering a promising avenue for non-invasive screening and risk assessment. The identification of specific microbial signatures, particularly those linked to metabolic functions and resistance traits, could open new doors for understanding the role of the microbiome in CRC progression and treatment resistance.
肠道微生物群（GM）的改变与包括结直肠癌（CRC）在内的多种疾病相关。随着下一代测序技术的发展，宏基因组测序以及代谢功能和抗生素抗性基因分析已被用于研究CRC患者与健康对照之间GM的差异。从7名CRC患者和6名健康受试者中获取粪便样本，并对测序数据进行相似性、α多样性、主成分分析（PCA）和线性判别分析（LDA）。关于放线菌，鉴定出3个目、5个科、9个属和19个物种，CRC组与对照组之间无差异，而CRC组中 和 的水平较高， 水平低于健康对照组（ = 0.053）。此外，发现2个属（ 和 ）以及7种细菌（ 、未分类 ）在CRC患者和健康对照之间的分布存在显著差异。PCA-LDA成功地以令人满意的准确率对这两组进行了分类（代谢功能方面为84.52%，抗性基因方面为77.38%）。这些发现强调了GM作为CRC诊断工具的潜力，为非侵入性筛查和风险评估提供了一条有前景的途径。特定微生物特征的鉴定，特别是那些与代谢功能和抗性特征相关的特征，可能为理解微生物群在CRC进展和治疗抗性中的作用打开新的大门。
