Comprehensive analysis of microbiota signature across 32 cancer types

被引:3
|
作者
Yang, Xia [1 ]
An, Huimin [1 ]
He, Yongtao [1 ]
Fu, Guoxiang [1 ]
Jiang, Zhinong [1 ]
机构
[1] Zhejiang Univ, Sir Run Run Shaw Hosp, Sch Med, Dept Pathol, Hangzhou, Peoples R China
来源
FRONTIERS IN ONCOLOGY | 2023年 / 13卷
关键词
microbiota signature; survival outcomes; genomic features; immune profiles; bacteria in cancer; the Cancer Genome Atlas; FUSOBACTERIUM-NUCLEATUM; HELICOBACTER-PYLORI; CELL-CYCLE; ENRICHMENT; IMMUNITY; TISSUE;
D O I
10.3389/fonc.2023.1127225
中图分类号
R73 [肿瘤学];
学科分类号
100214 ;
摘要
Microbial communities significantly inhabit the human body. Evidence shows the interaction between the human microbiome and host cells plays a central role in multiple physiological processes and organ microenvironments. However, the majority of related studies focus on gut microbiota or specific tissues/organs, and the component signature of intratumor microbiota across various cancer types remains unclear. Here, we systematically analyzed the correlation between intratumor microbial signature with survival outcomes, genomic features, and immune profiles across 32 cancer types based on the public databases of Bacteria in Cancer (BIC) and The Cancer Genome Atlas (TCGA). Results showed the relative abundance of microbial taxa in tumors compared to normal tissues was observed as particularly noticeable. Survival analysis found that specific candidate microbial taxa were correlated with prognosis across various cancers. Then, a microbial-based scoring system (MS), which was composed of 64 candidate prognostic microbes, was established. Further analyses showed significant differences in survival status, genomic function, and immune profiles among the distinct MS subgroups. Taken together, this study reveals the diversity and complexity of microbiomes in tumors. Classifying cancer into different subtypes based on intratumor microbial signatures might reasonably reflect genomic characteristics, immune features, and survival status.
引用
收藏
页数:10
相关论文
共 50 条
  • [21] LinkedOmics: Analyzing multi-omics data within and across 32 cancer types
    Vasaikar, Suhas
    Straub, Peter
    Wang, Jing
    Zhang, Bing
    CANCER RESEARCH, 2019, 79 (13)
  • [22] LinkedOmics: Analyzing multi-omics data within and across 32 cancer types
    Vasaikar, Suhas
    Straub, Pater
    Wang, Jing
    Zhang, Bing
    CANCER RESEARCH, 2018, 78 (13)
  • [23] LinkedOmics: analyzing multi-omics data within and across 32 cancer types
    Vasaikar, Suhas V.
    Straub, Peter
    Wang, Jing
    Zhang, Bing
    NUCLEIC ACIDS RESEARCH, 2018, 46 (D1) : D956 - D963
  • [24] Global Gene Coexpression Analysis Identifies a Poor Prognosis Signature across Tumor Types
    Ladd, A. C.
    Dumur, C. I.
    Powers, C. N.
    Wilkinson, D. S.
    Garrett, C. T.
    LABORATORY INVESTIGATION, 2009, 89 : 373A - 373A
  • [25] Global Gene Coexpression Analysis Identifies a Poor Prognosis Signature across Tumor Types
    Ladd, A. C.
    Dumur, C. I.
    Powers, C. N.
    Wilkinson, D. S.
    Garrett, C. T.
    MODERN PATHOLOGY, 2009, 22 : 373A - 373A
  • [26] Gut Microbiota Signature of Obese Adults Across Different Classifications
    Hu, Junqing
    Guo, Pengsen
    Mao, Rui
    Ren, Zhengyun
    Wen, Jun
    Yang, Qin
    Yan, Tong
    Yu, Jiahui
    Zhang, Tongtong
    Liu, Yanjun
    DIABETES METABOLIC SYNDROME AND OBESITY, 2022, 15 : 3933 - 3947
  • [27] Analysis of Tumor-Infiltrating T-Cell Transcriptomes Reveal a Unique Genetic Signature across Different Types of Cancer
    Vidal, Mabel
    Fraga, Marco
    Llerena, Faryd
    Vera, Agustin
    Hernandez, Mauricio
    Koch, Elard
    Reyes-Lopez, Felipe
    Vallejos-Vidal, Eva
    Cabrera-Vives, Guillermo
    Nova-Lamperti, Estefania
    INTERNATIONAL JOURNAL OF MOLECULAR SCIENCES, 2022, 23 (19)
  • [28] Comprehensive analysis of hypoxia-related gene signature in cervical cancer
    He, Tingting
    Tang, Xiaoyu
    Chen, Siru
    Chen, Xin
    Lin, Fuye
    Yu, Minmin
    Lin, Changsong
    EUROPEAN JOURNAL OF GYNAECOLOGICAL ONCOLOGY, 2023, 44 (06) : 105 - 121
  • [29] Erratum: Comprehensive identification of mutational cancer driver genes across 12 tumor types
    David Tamborero
    Abel Gonzalez-Perez
    Christian Perez-Llamas
    Jordi Deu-Pons
    Cyriac Kandoth
    Jüri Reimand
    Michael S. Lawrence
    Gad Getz
    Gary D. Bader
    Li Ding
    Nuria Lopez-Bigas
    Scientific Reports, 3
  • [30] Sigflow: an automated and comprehensive pipeline for cancer genome mutational signature analysis
    Wang, Shixiang
    Tao, Ziyu
    Wu, Tao
    Liu, Xue-Song
    BIOINFORMATICS, 2021, 37 (11) : 1590 - 1592