{"title":"Pan-Cancer Integrative Analyses Reveal the Crosstalk Between the Intratumoral Microbiome, TP53 Mutation and Tumour Microenvironment","authors":"Baoling Wang, Bo Zhang, Chun Li","doi":"10.1049/syb2.70035","DOIUrl":null,"url":null,"abstract":"<p>Accumulating evidence suggests that the TP53 mutation, intratumoral microbiome, and tumour microenvironment (TME) are closely linked to tumourigenesis, yet the biological mechanisms underlying these connections remain unclear. To explore this, we collected multi-omics data—including genome, transcriptome, and tumour microbiome data—from a wide range of cancer types in The Cancer Genome Atlas (TCGA). Through a pan-cancer analysis, we identified significant correlations between intratumoral microbiota diversity and TP53 mutation status, particularly in hepatocellular carcinoma (HCC) and endometrial cancer (EC). Despite notable differences in microbiota composition between these two cancer types, we consistently observed that TP53 mutations were associated with reduced alpha-diversity. Additionally, we found that TP53 mutation status significantly influenced stromal components within the TME, such as a strong correlation between decreased endothelial cell abundance and TP53 mutation. Our integrated approach reveals the complex interplay between TP53 and factors regulating the host TME, offering new insights into cancer progression and potential therapeutic targets for future research.</p>","PeriodicalId":50379,"journal":{"name":"IET Systems Biology","volume":"19 1","pages":""},"PeriodicalIF":1.9000,"publicationDate":"2025-08-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ietresearch.onlinelibrary.wiley.com/doi/epdf/10.1049/syb2.70035","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"IET Systems Biology","FirstCategoryId":"99","ListUrlMain":"https://ietresearch.onlinelibrary.wiley.com/doi/10.1049/syb2.70035","RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"CELL BIOLOGY","Score":null,"Total":0}
引用次数: 0
Abstract
Accumulating evidence suggests that the TP53 mutation, intratumoral microbiome, and tumour microenvironment (TME) are closely linked to tumourigenesis, yet the biological mechanisms underlying these connections remain unclear. To explore this, we collected multi-omics data—including genome, transcriptome, and tumour microbiome data—from a wide range of cancer types in The Cancer Genome Atlas (TCGA). Through a pan-cancer analysis, we identified significant correlations between intratumoral microbiota diversity and TP53 mutation status, particularly in hepatocellular carcinoma (HCC) and endometrial cancer (EC). Despite notable differences in microbiota composition between these two cancer types, we consistently observed that TP53 mutations were associated with reduced alpha-diversity. Additionally, we found that TP53 mutation status significantly influenced stromal components within the TME, such as a strong correlation between decreased endothelial cell abundance and TP53 mutation. Our integrated approach reveals the complex interplay between TP53 and factors regulating the host TME, offering new insights into cancer progression and potential therapeutic targets for future research.
期刊介绍:
IET Systems Biology covers intra- and inter-cellular dynamics, using systems- and signal-oriented approaches. Papers that analyse genomic data in order to identify variables and basic relationships between them are considered if the results provide a basis for mathematical modelling and simulation of cellular dynamics. Manuscripts on molecular and cell biological studies are encouraged if the aim is a systems approach to dynamic interactions within and between cells.
The scope includes the following topics:
Genomics, transcriptomics, proteomics, metabolomics, cells, tissue and the physiome; molecular and cellular interaction, gene, cell and protein function; networks and pathways; metabolism and cell signalling; dynamics, regulation and control; systems, signals, and information; experimental data analysis; mathematical modelling, simulation and theoretical analysis; biological modelling, simulation, prediction and control; methodologies, databases, tools and algorithms for modelling and simulation; modelling, analysis and control of biological networks; synthetic biology and bioengineering based on systems biology.