肠道菌群作为结直肠癌早期诊断标志物的研究进展
Research Progress of Intestinal Flora as an Early Diagnostic Marker of Colorectal Cancer
DOI: 10.12677/acm.2026.1652030, PDF,   
作者: 杨泽旭, 王延刚, 于照祥*：西安医学院第一附属医院普通外科，陕西 西安；彭朝胜：西安医学院研究生处，陕西 西安
关键词: 结直肠癌；肠道菌群；生物标志物；早期诊断；Colorectal Cancer； Intestinal Flora； Biomarkers； Early Diagnosis
摘要: 结直肠癌(CRC)是全球高发的恶性肿瘤，传统筛查手段的局限性凸显了开发新型非侵入性诊断标志物的迫切性。近年来，肠道菌群失调与CRC发生发展的密切关联已被广泛证实，基于微生物特征的检测展现出巨大的早期诊断潜力。本文系统综述了近年以来肠道菌群作为CRC早期诊断标志物的研究进展。文章首先阐述了粪便、血液、组织及口腔等不同来源样本中微生物标志物的特征与价值，随后重点介绍了基于机器学习的诊断模型构建、验证及多组学整合优化策略。同时，文章探讨了微生物标志物在“腺瘤–癌”演进过程中的动态变化，并分析了单核苷酸变异与功能基因等新型深层标志物的应用前景。此外，本文还讨论了肠道菌群在预后预测、左右半结肠癌区分及术后监测等临床特殊场景中的应用。最后，文章指出了当前研究面临的标准化、可重复性及因果机制阐释等挑战，并展望了未来通过技术标准化与跨学科合作推动肠道菌群从基础研究向CRC临床筛查与个体化诊疗转化的广阔前景。
Abstract: Colorectal cancer (CRC) is a high-incidence malignant tumor in the world. The limitations of traditional screening methods highlight the urgency of developing new non-invasive diagnostic markers. In recent years, the close relationship between intestinal flora imbalance and CRC has been widely confirmed, and the detection based on microbial characteristics shows great potential for early diagnosis. This paper systematically reviews the research progress of intestinal flora as an early diagnostic marker of CRC in recent years. In this paper, the characteristics and values of microbial markers in feces, blood, tissues and oral samples from different sources are firstly expounded, and then the diagnosis model construction, verification and multi-group integration optimization strategy based on machine learning are emphatically introduced. At the same time, the dynamic changes of microbial markers in the evolution of “adenoma-carcinoma” were discussed, and the application prospects of new deep markers such as single nucleotide variation and functional genes were analyzed. In addition, this paper also discusses the application of intestinal flora in clinical special scenes such as prognosis prediction, left and right colon cancer differentiation and postoperative monitoring. Finally, the paper points out the challenges of standardization, repeatability and explanation of causal mechanism, and looks forward to the broad prospect of promoting the transformation of intestinal flora from basic research to CRC clinical screening and individualized diagnosis and treatment through technical standardization and interdisciplinary cooperation in the future.
文章引用：杨泽旭, 王延刚, 彭朝胜, 于照祥. 肠道菌群作为结直肠癌早期诊断标志物的研究进展[J]. 临床医学进展, 2026, 16(5): 2211-2218. https://doi.org/10.12677/acm.2026.1652030

参考文献

[1] Wong, C.C. and Yu, J. (2023) Gut Microbiota in Colorectal Cancer Development and Therapy. Nature Reviews Clinical Oncology, 20, 429-452. [Google Scholar] [CrossRef] [PubMed]
[2] Olovo, C.V., Huang, X., Zheng, X. and Xu, M. (2021) Faecal Microbial Biomarkers in Early Diagnosis of Colorectal Cancer. Journal of Cellular and Molecular Medicine, 25, 10783-10797. [Google Scholar] [CrossRef] [PubMed]
[3] Qu, R., Zhang, Y., Ma, Y., Zhou, X., Sun, L., Jiang, C., et al. (2023) Role of the Gut Microbiota and Its Metabolites in Tumorigenesis or Development of Colorectal Cancer. Advanced Science, 10, e2205563. [Google Scholar] [CrossRef] [PubMed]
[4] Liu, Y., Lau, H.C., Cheng, W.Y. and Yu, J. (2023) Gut Microbiome in Colorectal Cancer: Clinical Diagnosis and Treatment. Genomics, Proteomics & Bioinformatics, 21, 84-96. [Google Scholar] [CrossRef] [PubMed]
[5] Zhou, P., Yang, D., Sun, D. and Zhou, Y. (2022) Gut Microbiome: New Biomarkers in Early Screening of Colorectal Cancer. Journal of Clinical Laboratory Analysis, 36, e24359. [Google Scholar] [CrossRef] [PubMed]
[6] Zhou, Y. and Sun, G. (2022) Improve the Colorectal Cancer Diagnosis Using Gut Microbiome Data. Frontiers in Molecular Biosciences, 9, Article 921945. [Google Scholar] [CrossRef] [PubMed]
[7] Konishi, Y., Okumura, S., Matsumoto, T., Itatani, Y., Nishiyama, T., Okazaki, Y., et al. (2022) Development and Evaluation of a Colorectal Cancer Screening Method Using Machine Learning-Based Gut Microbiota Analysis. Cancer Medicine, 11, 3194-3206. [Google Scholar] [CrossRef] [PubMed]
[8] Zou, J., Xiao, Z., Wu, Y., Yang, J. and Cui, N. (2022) Noninvasive Fecal Testing for Colorectal Cancer. Clinica Chimica Acta, 524, 123-131. [Google Scholar] [CrossRef] [PubMed]
[9] Hanna, M., Dey, N. and Grady, W.M. (2023) Emerging Tests for Noninvasive Colorectal Cancer Screening. Clinical Gastroenterology and Hepatology, 21, 604-616. [Google Scholar] [CrossRef] [PubMed]
[10] Wang, Z., Dan, W., Zhang, N., Fang, J. and Yang, Y. (2023) Colorectal Cancer and Gut Microbiota Studies in China. Gut Microbes, 15, Article 2236364. [Google Scholar] [CrossRef] [PubMed]
[11] Yang, J., Li, D., Yang, Z., Dai, W., Feng, X., Liu, Y., et al. (2020) Establishing High-Accuracy Biomarkers for Colorectal Cancer by Comparing Fecal Microbiomes in Patients with Healthy Families. Gut Microbes, 11, 918-929. [Google Scholar] [CrossRef] [PubMed]
[12] Prusa, J., Gorelik, M.G., Blake, K.S. and Dantas, G. (2025) State of Omics-Based Microbial Diagnostics of CRC. Gut Microbes, 17, Article 2526132. [Google Scholar] [CrossRef] [PubMed]
[13] Zouiouich, S., Mariadassou, M., Rué, O., Vogtmann, E., Huybrechts, I., Severi, G., et al. (2022) Comparison of Fecal Sample Collection Methods for Microbial Analysis Embedded within Colorectal Cancer Screening Programs. Cancer Epidemiology, Biomarkers & Prevention, 31, 305-314. [Google Scholar] [CrossRef] [PubMed]
[14] Tito, R.Y., Verbandt, S., Aguirre Vazquez, M., Lahti, L., Verspecht, C., Lloréns-Rico, V., et al. (2024) Microbiome Confounders and Quantitative Profiling Challenge Predicted Microbial Targets in Colorectal Cancer Development. Nature Medicine, 30, 1339-1348. [Google Scholar] [CrossRef] [PubMed]
[15] Piccinno, G., Thompson, K.N., Manghi, P., Ghazi, A.R., Thomas, A.M., Blanco-Míguez, A., et al. (2025) Pooled Analysis of 3,741 Stool Metagenomes from 18 Cohorts for Cross-Stage and Strain-Level Reproducible Microbial Biomarkers of Colorectal Cancer. Nature Medicine, 31, 2416-2429. [Google Scholar] [CrossRef] [PubMed]
[16] Cao, Y., Wang, J., Hou, W., Ding, Y., Zhu, Y., Zheng, J., et al. (2023) Colorectal Cancer-Associated T Cell Receptor Repertoire Abnormalities Are Linked to Gut Microbiome Shifts and Somatic Cell Mutations. Gut Microbes, 15, Article 2263934. [Google Scholar] [CrossRef] [PubMed]
[17] Han, S., Zhuang, J., Pan, Y., Wu, W. and Ding, K. (2022) Different Characteristics in Gut Microbiome between Advanced Adenoma Patients and Colorectal Cancer Patients by Metagenomic Analysis. Microbiology Spectrum, 10, e0159322. [Google Scholar] [CrossRef] [PubMed]
[18] Wu, Y., Jiao, N., Zhu, R., Zhang, Y., Wu, D., Wang, A., et al. (2021) Identification of Microbial Markers across Populations in Early Detection of Colorectal Cancer. Nature Communications, 12, Article No. 3063. [Google Scholar] [CrossRef] [PubMed]
[19] Wu, X., Tang, Z., Zhao, R., Wang, Y., Wang, X., Liu, S., et al. (2023) Taxonomic and Functional Profiling of Fecal Metagenomes for the Early Detection of Colorectal Cancer. Frontiers in Oncology, 13, Article 1218056. [Google Scholar] [CrossRef] [PubMed]
[20] Xiao, Q., Lu, W., Kong, X., Shao, Y.W., Hu, Y., Wang, A., et al. (2021) Alterations of Circulating Bacterial DNA in Colorectal Cancer and Adenoma: A Proof-of-Concept Study. Cancer Letters, 499, 201-208. [Google Scholar] [CrossRef] [PubMed]
[21] Giacconi, R., Donghia, R., Arborea, G., Savino, M.T., Provinciali, M., Lattanzio, F., et al. (2023) Plasma Bacterial DNA Load as a Potential Biomarker for the Early Detection of Colorectal Cancer: A Case-Control Study. Microorganisms, 11, Article 2360. [Google Scholar] [CrossRef] [PubMed]
[22] Russo, E., Gloria, L.D., Nannini, G., Meoni, G., Niccolai, E., Ringressi, M.N., et al. (2023) From Adenoma to CRC Stages: The Oral-Gut Microbiome Axis as a Source of Potential Microbial and Metabolic Biomarkers of Malignancy. Neoplasia, 40, Article 100901. [Google Scholar] [CrossRef] [PubMed]
[23] Xu, Y., Zhao, J., Ma, Y., Liu, J., Cui, Y., Yuan, Y., et al. (2023) The Microbiome Types of Colorectal Tissue Are Potentially Associated with the Prognosis of Patients with Colorectal Cancer. Frontiers in Microbiology, 14, Article 1100873. [Google Scholar] [CrossRef] [PubMed]
[24] Zhang, C., Hu, A., Li, J., Zhang, F., Zhong, P., Li, Y., et al. (2022) Combined Non-Invasive Prediction and New Biomarkers of Oral and Fecal Microbiota in Patients with Gastric and Colorectal Cancer. Frontiers in Cellular and Infection Microbiology, 12, Article 830684. [Google Scholar] [CrossRef] [PubMed]
[25] Rezasoltani, S., Azizmohammad Looha, M., Asadzadeh Aghdaei, H., Jasemi, S., Sechi, L.A., Gazouli, M., et al. (2024) 16S rRNA Sequencing Analysis of the Oral and Fecal Microbiota in Colorectal Cancer Positives versus Colorectal Cancer Negatives in Iranian Population. Gut Pathogens, 16, Article No. 9. [Google Scholar] [CrossRef] [PubMed]
[26] Tsai, Y., Lyu, W., Liao, N., Chen, P., Tsai, M. and Chuang, E.Y. (2025) Gut Microbiome-Based Machine Learning Model for Early Colorectal Cancer and Adenoma Screening. Gut Pathogens, 17, Article No. 80. [Google Scholar] [CrossRef] 
[27] Lu, F., Lei, T., Zhou, J., Liang, H., Cui, P., Zuo, T., et al. (2023) Using Gut Microbiota as a Diagnostic Tool for Colorectal Cancer: Machine Learning Techniques Reveal Promising Results. Journal of Medical Microbiology, 72, No. 6. [Google Scholar] [CrossRef] [PubMed]
[28] Armour, C.R., Topçuoğlu, B.D., Garretto, A. and Schloss, P.D. (2022) A Goldilocks Principle for the Gut Microbiome: Taxonomic Resolution Matters for Microbiome-Based Classification of Colorectal Cancer. mBio, 13, e0316121. [Google Scholar] [CrossRef] [PubMed]
[29] Kong, C., Liang, L., Liu, G., Du, L., Yang, Y., Liu, J., et al. (2022) Integrated Metagenomic and Metabolomic Analysis Reveals Distinct Gut-Microbiome-Derived Phenotypes in Early-Onset Colorectal Cancer. Gut, 72, 1129-1142. [Google Scholar] [CrossRef] [PubMed]
[30] Gou, H., Zeng, R., Lau, H.C.H. and Yu, J. (2024) Gut Microbial Metabolites: Shaping Future Diagnosis and Treatment against Gastrointestinal Cancer. Pharmacological Research, 208, Article 107373. [Google Scholar] [CrossRef] [PubMed]
[31] Bosch, S., Acharjee, A., Quraishi, M.N., Bijnsdorp, I.V., Rojas, P., Bakkali, A., et al. (2022) Integration of Stool Microbiota, Proteome and Amino Acid Profiles to Discriminate Patients with Adenomas and Colorectal Cancer. Gut Microbes, 14, Article 2139979. [Google Scholar] [CrossRef] [PubMed]
[32] Okumura, S., Konishi, Y., Kitano, T., Matsumoto, T., Obama, K., Nagayama, S., et al. (2025) Refining the Feasibility of Machine-Learning-Based Diagnostic Model Utilizing Gut Microbiota Analysis for Colorectal Cancer Screening. Cancer Medicine, 14, e70935. [Google Scholar] [CrossRef] [PubMed]
[33] Yao, Y., Ni, H., Wang, X., Xu, Q., Zhang, J., Jiang, L., et al. (2021) A New Biomarker of Fecal Bacteria for Non-Invasive Diagnosis of Colorectal Cancer. Frontiers in Cellular and Infection Microbiology, 11, Article 744049. [Google Scholar] [CrossRef] [PubMed]
[34] Liu, H., Song, C., Wang, J., Chen, Z., Zhang, X., Zhou, H., et al. (2024) Development of Fecal Microbial Diagnostic Marker Sets of Colorectal Cancer Using Natural Language Processing Method. The International Journal of Biological Markers, 39, 31-39. [Google Scholar] [CrossRef] [PubMed]
[35] Fan, J., Zhao, W., Lu, Q., Zha, F., Lv, L., Ye, G., et al. (2023) Fecal Microbial Biomarkers Combined with Multi-Target Stool DNA Test Improve Diagnostic Accuracy for Colorectal Cancer. World Journal of Gastrointestinal Oncology, 15, 1424-1435. [Google Scholar] [CrossRef] [PubMed]
[36] Guodong, W., Yinhang, W., Xinyue, W., Hong, S., Jian, C., Zhanbo, Q., et al. (2025) Fecal Occult Blood Affects Intestinal Microbial Community Structure in Colorectal Cancer. BMC Microbiology, 25, Article No. 34. [Google Scholar] [CrossRef] [PubMed]
[37] Mizutani, S., Yamada, T. and Yachida, S. (2020) Significance of the Gut Microbiome in Multistep Colorectal Carcinogenesis. Cancer Science, 111, 766-773. [Google Scholar] [CrossRef] [PubMed]
[38] Zwezerijnen-Jiwa, F.H., Sivov, H., Paizs, P., Zafeiropoulou, K. and Kinross, J. (2023) A Systematic Review of Microbiome-Derived Biomarkers for Early Colorectal Cancer Detection. Neoplasia, 36, Article 100868. [Google Scholar] [CrossRef] [PubMed]
[39] Casimiro-Soriguer, C.S., Loucera, C., Peña-Chilet, M. and Dopazo, J. (2022) Towards a Metagenomics Machine Learning Interpretable Model for Understanding the Transition from Adenoma to Colorectal Cancer. Scientific Reports, 12, Article No. 450. [Google Scholar] [CrossRef] [PubMed]
[40] Ma, C., Chen, K., Wang, Y., Cen, C., Zhai, Q. and Zhang, J. (2021) Establishing a Novel Colorectal Cancer Predictive Model Based on Unique Gut Microbial Single Nucleotide Variant Markers. Gut Microbes, 13, Article 1869505. [Google Scholar] [CrossRef] [PubMed]
[41] Gao, W., Gao, X., Zhu, L., Gao, S., Sun, R., Feng, Z., et al. (2023) Multimodal Metagenomic Analysis Reveals Microbial Single Nucleotide Variants as Superior Biomarkers for Early Detection of Colorectal Cancer. Gut Microbes, 15, Article 2245562. [Google Scholar] [CrossRef] [PubMed]
[42] Cai, Z., Li, P., Zhu, W., Wei, J., Lu, J., Song, X., et al. (2023) Metagenomic Analysis Reveals Gut Plasmids as Diagnosis Markers for Colorectal Cancer. Frontiers in Microbiology, 14, Article 1130446. [Google Scholar] [CrossRef] [PubMed]
[43] Huh, J., Kim, M.J., Kim, J., Lee, H.G., Ryoo, S., Ku, J., et al. (2022) Enterotypical Prevotella and Three Novel Bacterial Biomarkers in Preoperative Stool Predict the Clinical Outcome of Colorectal Cancer. Microbiome, 10, Article No. 203. [Google Scholar] [CrossRef] [PubMed]
[44] Liu, Y., Geng, R., Liu, L., Jin, X., Yan, W., Zhao, F., et al. (2020) Gut Microbiota-Based Algorithms in the Prediction of Metachronous Adenoma in Colorectal Cancer Patients Following Surgery. Frontiers in Microbiology, 11, Article 1106. [Google Scholar] [CrossRef] [PubMed]
[45] Yao, Q., Tang, M., Zeng, L., Chu, Z., Sheng, H., Zhang, Y., et al. (2021) Potential of Fecal Microbiota for Detection and Postoperative Surveillance of Colorectal Cancer. BMC Microbiology, 21, Article No. 156. [Google Scholar] [CrossRef] [PubMed]
[46] Severino, A., Marchitto, S.A., Bisegna, P., Porcari, S., Rondinella, D., Schepis, T., et al. (2025) Measuring Gut Microbiome as a Colorectal Cancer Screening Tool: Potential and Challenges. Expert Review of Gastroenterology & Hepatology, 19, 1285-1298. [Google Scholar] [CrossRef] 
[47] Zhang, R., Li, M., Tan, H., Liu, J., Wang, L., Dai, W., et al. (2025) A New Gut Pathogenic Bacteria and Its Metabolites Promote Colorectal Cancer Development and Act as Non-Invasive Early Diagnostic Biomarkers. Gut Microbes, 17, Article 2555446. [Google Scholar] [CrossRef] 
[48] González, A., Badiola, I., Fullaondo, A., et al. (2024) Personalised Medicine Based on Host Genetics and Microbiota Applied to Colorectal Cancer. Advanced Genetics, 112, 411-485.

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