Gut microbial subtypes and clinicopathological value for colorectal cancer

IF 2.9 2区医学 Q2 ONCOLOGY

Cancer Medicine Pub Date : 2024-09-05 DOI:10.1002/cam4.70180

Shuwen Han, Jing Zhuang, Yifei Song, Xinyue Wu, Xiaojian Yu, Ye Tao, Jian Chu, Zhanbo Qu, Yinhang Wu, Shugao Han, Xi Yang

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引用次数: 0

Abstract

Background

Gut bacteria are related to colorectal cancer (CRC) and its clinicopathologic characteristics.

Objective

To develop gut bacterial subtypes and explore potential microbial targets for CRC.

Methods

Stool samples from 914 volunteers (376 CRCs, 363 advanced adenomas, and 175 normal controls) were included for 16S rRNA sequencing. Unsupervised learning was used to generate gut microbial subtypes. Gut bacterial community composition and clustering effects were plotted. Differences of gut bacterial abundance were analyzed. Then, the association of CRC-associated bacteria with subtypes and the association of gut bacteria with clinical information were assessed. The CatBoost models based on gut differential bacteria were constructed to identify the diseases including CRC and advanced adenoma (AA).

Results

Four gut microbial subtypes (A, B, C, D) were finally obtained via unsupervised learning. The characteristic bacteria of each subtype were Escherichia-Shigella in subtype A, Streptococcus in subtype B, Blautia in subtype C, and Bacteroides in subtype D. Clinical information (e.g., free fatty acids and total cholesterol) and CRC pathological information (e.g., tumor depth) varied among gut microbial subtypes. Bacilli, Lactobacillales, etc., were positively correlated with subtype B. Positive correlation of Blautia, Lachnospiraceae, etc., with subtype C and negative correlation of Coriobacteriia, Coriobacteriales, etc., with subtype D were found. Finally, the predictive ability of CatBoost models for CRC identification was improved based on gut microbial subtypes.

Conclusion

Gut microbial subtypes provide characteristic gut bacteria and are expected to contribute to the diagnosis of CRC.

Abstract Image

查看原文本刊更多论文

肠道微生物亚型与结直肠癌的临床病理学价值。

背景：肠道细菌与结直肠癌（CRC）及其临床病理特征有关：肠道细菌与结直肠癌（CRC）及其临床病理特征有关：方法：采集 914 名志愿者（376 名 CRC、363 名晚期腺癌患者）的粪便样本：方法：对 914 名志愿者（376 名 CRC 患者、363 名晚期腺瘤患者和 175 名正常对照者）的粪便样本进行 16S rRNA 测序。利用无监督学习生成肠道微生物亚型。绘制了肠道细菌群落组成图和聚类效应图。分析了肠道细菌丰度的差异。然后，评估了 CRC 相关细菌与亚型的关联以及肠道细菌与临床信息的关联。基于肠道差异细菌构建的 CatBoost 模型可识别包括 CRC 和晚期腺瘤（AA）在内的疾病：结果：通过无监督学习，最终获得了四种肠道微生物亚型（A、B、C、D）。各亚型的特征细菌分别为 A 亚型的埃希氏-志贺氏菌、B 亚型的链球菌、C 亚型的布劳氏菌和 D 亚型的乳杆菌。临床信息（如游离脂肪酸和总胆固醇）和 CRC 病理信息（如肿瘤深度）在不同的肠道微生物亚型之间存在差异。发现芽孢杆菌、乳酸杆菌等与 B 亚型呈正相关，而 Blautia、Lachnospiraceae 等与 C 亚型呈正相关，Coriobacteriia、Coriobacteriales 等与 D 亚型呈负相关。最后，基于肠道微生物亚型的 CatBoost 模型提高了对 CRC 鉴定的预测能力：结论：肠道微生物亚型提供了特征性肠道细菌，有望为诊断 CRC 做出贡献。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Cancer Medicine ONCOLOGY-

CiteScore

5.50

自引率

2.50%

发文量

907

审稿时长

19 weeks

期刊介绍： Cancer Medicine is a peer-reviewed, open access, interdisciplinary journal providing rapid publication of research from global biomedical researchers across the cancer sciences. The journal will consider submissions from all oncologic specialties, including, but not limited to, the following areas: Clinical Cancer Research Translational research ∙ clinical trials ∙ chemotherapy ∙ radiation therapy ∙ surgical therapy ∙ clinical observations ∙ clinical guidelines ∙ genetic consultation ∙ ethical considerations Cancer Biology: Molecular biology ∙ cellular biology ∙ molecular genetics ∙ genomics ∙ immunology ∙ epigenetics ∙ metabolic studies ∙ proteomics ∙ cytopathology ∙ carcinogenesis ∙ drug discovery and delivery. Cancer Prevention: Behavioral science ∙ psychosocial studies ∙ screening ∙ nutrition ∙ epidemiology and prevention ∙ community outreach. Bioinformatics: Gene expressions profiles ∙ gene regulation networks ∙ genome bioinformatics ∙ pathwayanalysis ∙ prognostic biomarkers. Cancer Medicine publishes original research articles, systematic reviews, meta-analyses, and research methods papers, along with invited editorials and commentaries. Original research papers must report well-conducted research with conclusions supported by the data presented in the paper.

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