Gao Yan, Zhang Haohong, Chu Dongliang, Ning Kang
Key Laboratory of Molecular Biophysics of the Ministry of Education, Hubei Key Laboratory of Bioinformatics and Molecular-imaging, Center of AI Biology, Department of Bioinformatics and Systems Biology, College of Life Science and Technology, Huazhong University of Science and Technology, Wuhan, Hubei, China.
Geneis Beijing Co. Ltd., Beijing, China.
mSystems. 2025 Jul 22;10(7):e0031225. doi: 10.1128/msystems.00312-25. Epub 2025 Jun 25.
Growing research evidence indicates a substantial influence of the intra-tumor microbiome on tumor outcome. However, there is currently no consistent criterion for identifying the association of microbes with tumor progression and response to treatment across various types of cancer. In this study, we concentrate on the intra-tumor microbiome and develop the Tumor Microbiome Survival Index (TMSI), a measure indicative of cancer patient survival risk. Our indices revealed notable distinctions between two stratified risk groups for each of the 10 cancer types and could precisely predict patients' overall survival. For each type of cancer, our findings unveiled two distinct gene expression profiles and shed light on the varying patterns of immune and stromal cell enrichment between the two risk groups. Additionally, we noted that the high-TMSI group exhibited substantially elevated IC50 values for a number of drugs, indicating that individuals in the low-TMSI group might experience superior therapeutic effects from chemotherapy. These findings illuminate the complex dynamics between the tumor microbiome, the patient's immune reaction, and medical outcomes, thus shedding light on microbiome-based personalized therapeutic interventions.
This work presents the Tumor Microbiome Survival Index (TMSI), a crucial innovation. It stratifies cancer patients into risk groups across 10 cancer types, accurately predicting survival. By uncovering distinct gene expression and immune/stromal cell patterns, it deepens understanding of tumor complexity. The finding of altered drug sensitivity in different TMSI groups offers insights for personalized chemotherapy. Overall, it paves the way for microbiome-targeted cancer therapies and enhanced patient prognostication.
越来越多的研究证据表明肿瘤内微生物群对肿瘤预后有重大影响。然而，目前尚无一致的标准来确定微生物与各种癌症类型的肿瘤进展及治疗反应之间的关联。在本研究中，我们专注于肿瘤内微生物群，并开发了肿瘤微生物群生存指数（TMSI），这是一种指示癌症患者生存风险的指标。我们的指数揭示了10种癌症类型中两个分层风险组之间的显著差异，并能够精确预测患者的总生存期。对于每种癌症类型，我们的研究结果揭示了两种不同的基因表达谱，并阐明了两个风险组之间免疫和基质细胞富集的不同模式。此外，我们注意到高TMSI组对多种药物的IC50值显著升高，这表明低TMSI组的个体可能从化疗中获得更好的治疗效果。这些发现揭示了肿瘤微生物群、患者免疫反应和医疗结果之间的复杂动态关系，从而为基于微生物群的个性化治疗干预提供了线索。
这项工作提出了肿瘤微生物群生存指数（TMSI），这是一项关键创新。它将癌症患者分为10种癌症类型的风险组，准确预测生存率。通过揭示不同的基因表达以及免疫/基质细胞模式，加深了对肿瘤复杂性的理解。不同TMSI组中药物敏感性改变的发现为个性化化疗提供了见解。总体而言，它为以微生物群为靶点的癌症治疗和改善患者预后铺平了道路。
