Background After resection surgery, recurrence occurs in more than 30% of colorectal cancer (CRC) patients. Previous studies have highlighted the role of the gut microbiota in CRC initiation and progression; however, the microbial features associated with recurrence remain not completely understood. In particular, integrated multi-omics biomarkers, the interactions between microorganisms, as well as those between microbes and the host, and their relevance to recurrence risk require further investigation. Results In this study, 120 tumor mucosal samples collected during surgery from CRC patients underwent 16S rRNA gene sequencing and LC–MS metabolomic profiling. Recurrence status was determined through postoperative follow-up. Compared to the relatively minor variations in mucosal microbial and metabolomic signatures across different tumor node metastasis (TNM) stages, recurrent patients exhibited a distinct landscape. Machine learning analysis identified an integrated signature comprising five bacterial genera (Peptostreptococcus, Fusobacterium, Bacteroides, Porphyromonas, and Prevotella) and five metabolites (alanylglutamic acid, putrescine, arginine, histidine, and sebacic acid), which demonstrated strong discriminatory performance between recurrent and non-recurrent patients (AUC = 0.89). By integrating 10 biomarkers, a comprehensive risk score for patient stratification was derived. After adjusting for TNM stage, patients classified as high-risk had a significantly shorter recurrence-free survival (adjusted HR = 1.59, 95% CI 1.35–1.88, P < 0.0001). The microbial biomarkers Fusobacterium and Peptostreptococcus displayed positive correlation and were observed to co-aggregate and form dense dual-species biofilms. Further cellular and murine experiments revealed that P. anaerobius significantly enhanced the adhesion of F. nucleatum to tumor cells and its colonization of colonic mucosa. KEGG pathway analysis of differential metabolites identified enrichment of arginine and proline metabolism pathways in the recurrence group. Concurrently, arginine was found to disrupt F. nucleatum–P. anaerobius co-aggregation, while its metabolite putrescine significantly promoted dual-species biofilm formation. Conclusion Our study identified integrated microbial and metabolic features associated with CRC recurrence and proposes an exploratory risk stratification framework. Furthermore, a previously unrecognized link between pathobionts and metabolites relevant to recurrence was reported, which requires further validation in a larger independent cohort. <MediaObject ID="MOESM5"> <VideoObject FileRef="MediaObjects/40168_2026_2378_MOESM5_ESM.mp4" VideoID="1WBvwp8c_-z9vmkz7fSxvz"> <Caption Language="En" xml:lang="en"> <CaptionContent> Video Abstract </CaptionContent> </Caption> </VideoObject> </MediaObject>

The interplay between Peptostreptococcus and Fusobacterium as novel signatures in colorectal cancer recurrence

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2026年3月18日

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Yunhui Zhang,
Bowei Zhang,
Wenwen Pang,
Wentao Gu,
Xiaotong Wang,
Hao Yuan,
Shiyu Fang,
Jie Zhang,
Xiang Li,
Xiaolong Xing,
Xuemeng Ji,
Tianxu Liu,
Fan Wei,
Chunze Zhang,
Shuo Wang

摘要

Background

After resection surgery, recurrence occurs in more than 30% of colorectal cancer (CRC) patients. Previous studies have highlighted the role of the gut microbiota in CRC initiation and progression; however, the microbial features associated with recurrence remain not completely understood. In particular, integrated multi-omics biomarkers, the interactions between microorganisms, as well as those between microbes and the host, and their relevance to recurrence risk require further investigation.

Results

In this study, 120 tumor mucosal samples collected during surgery from CRC patients underwent 16S rRNA gene sequencing and LC–MS metabolomic profiling. Recurrence status was determined through postoperative follow-up. Compared to the relatively minor variations in mucosal microbial and metabolomic signatures across different tumor node metastasis (TNM) stages, recurrent patients exhibited a distinct landscape. Machine learning analysis identified an integrated signature comprising five bacterial genera (Peptostreptococcus, Fusobacterium, Bacteroides, Porphyromonas, and Prevotella) and five metabolites (alanylglutamic acid, putrescine, arginine, histidine, and sebacic acid), which demonstrated strong discriminatory performance between recurrent and non-recurrent patients (AUC = 0.89). By integrating 10 biomarkers, a comprehensive risk score for patient stratification was derived. After adjusting for TNM stage, patients classified as high-risk had a significantly shorter recurrence-free survival (adjusted HR = 1.59, 95% CI 1.35–1.88, P < 0.0001). The microbial biomarkers Fusobacterium and Peptostreptococcus displayed positive correlation and were observed to co-aggregate and form dense dual-species biofilms. Further cellular and murine experiments revealed that P. anaerobius significantly enhanced the adhesion of F. nucleatum to tumor cells and its colonization of colonic mucosa. KEGG pathway analysis of differential metabolites identified enrichment of arginine and proline metabolism pathways in the recurrence group. Concurrently, arginine was found to disrupt F. nucleatum–P. anaerobius co-aggregation, while its metabolite putrescine significantly promoted dual-species biofilm formation.

Conclusion

Our study identified integrated microbial and metabolic features associated with CRC recurrence and proposes an exploratory risk stratification framework. Furthermore, a previously unrecognized link between pathobionts and metabolites relevant to recurrence was reported, which requires further validation in a larger independent cohort.

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