Inflammatory Bowel Disease Mediates the Causal Relationship Between Gut Microbiota and Colorectal Cancer: Identification of Therapeutic Targets and Predictive Modeling.

IF 3.2 3区 医学 Q2 ONCOLOGY
Journal of Cancer Pub Date : 2025-09-22 eCollection Date: 2025-01-01 DOI:10.7150/jca.114687
Jin-Bei Wang, Zhen-Guo Wu, Guan-Wei Bi, Yu Li, Zhi-Wen Yao, Yan-Bo Yu
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引用次数: 0

Abstract

Background: Colorectal cancer (CRC) is the second leading cause of cancer-related mortality. Given its established associations with gut microbiota and inflammatory bowel disease (IBD), elucidating their relationships and developing predictive models are critical for early detection and therapy. Methods: Using Mendelian randomization (MR), we integrated data from the MiBioGen Consortium and multiple genome-wide association studies (GWAS). Single nucleotide polymorphisms (SNPs) associated with gut microbiota were mapped to genes, followed by gene selection via least absolute shrinkage and selection operator (LASSO) regression. Transcriptome analyses identified differential gene expressions and immune cell infiltration patterns. Six machine learning models were integrated through soft voting to predict CRC risk, validated by single-cell sequencing analysis. Results: Mediation MR identified 12 gut microbial taxa causally associated with CRC, mediated partially by IBD. SNP mapping and expression analysis highlighted eight CRC-associated genes, five of which (FAM120A, GBE1, MCM6, MSRA, ZDHHC4) were further underscored by drug target MR and summary-data-based MR (SMR). Transcriptomics implicated dysregulation in the neuroactive ligand-receptor interactions and the G2/M DNA checkpoint pathway. Immune infiltration analysis demonstrated elevated CD4⁺ T cells and M0 macrophages in the high-LASSO score group. Integrated machine learning models built using the five key genes achieved robust predictive performance. Single-cell sequencing analysis confirmed gene expression patterns. Conclusion: By integrating mediation MR, transcriptomics, and machine learning, this study demonstrated causal relationships between specific gut microbiota and CRC, with IBD as a mediator. We identified potential therapeutic targets and developed robust predictive models, providing crucial insights into the pathogenesis and clinical detection of CRC.

炎症性肠病介导肠道微生物群与结直肠癌之间的因果关系:治疗靶点的确定和预测模型
背景:结直肠癌(CRC)是癌症相关死亡的第二大原因。鉴于其与肠道微生物群和炎症性肠病(IBD)之间已建立的关联,阐明它们之间的关系并建立预测模型对于早期发现和治疗至关重要。方法:使用孟德尔随机化(MR),我们整合了来自MiBioGen联盟和多个全基因组关联研究(GWAS)的数据。将与肠道微生物群相关的单核苷酸多态性(snp)定位到基因上,然后通过最小绝对收缩和选择算子(LASSO)回归进行基因选择。转录组分析确定了差异基因表达和免疫细胞浸润模式。通过软投票整合六种机器学习模型来预测CRC风险,并通过单细胞测序分析进行验证。结果:调解MR鉴定出12个与结直肠癌相关的肠道微生物分类群,部分由IBD介导。SNP定位和表达分析突出了8个crc相关基因,其中5个(FAM120A、GBE1、MCM6、MSRA、ZDHHC4)通过药物靶MR和基于汇总数据的MR (SMR)进一步突出。转录组学涉及神经活性配体-受体相互作用和G2/M DNA检查点通路的失调。免疫浸润分析显示,高lasso评分组CD4 + T细胞和M0巨噬细胞升高。使用五个关键基因构建的集成机器学习模型实现了稳健的预测性能。单细胞测序分析证实了基因表达模式。结论:通过整合介导MR、转录组学和机器学习,本研究证明了特定肠道微生物群与结直肠癌之间的因果关系,其中IBD是中介。我们确定了潜在的治疗靶点,并建立了强大的预测模型,为CRC的发病机制和临床检测提供了重要的见解。
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来源期刊
Journal of Cancer
Journal of Cancer ONCOLOGY-
CiteScore
8.10
自引率
2.60%
发文量
333
审稿时长
12 weeks
期刊介绍: Journal of Cancer is an open access, peer-reviewed journal with broad scope covering all areas of cancer research, especially novel concepts, new methods, new regimens, new therapeutic agents, and alternative approaches for early detection and intervention of cancer. The Journal is supported by an international editorial board consisting of a distinguished team of cancer researchers. Journal of Cancer aims at rapid publication of high quality results in cancer research while maintaining rigorous peer-review process.
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