What is already known
The presence of microbiota in the tumor environment is well known. However, it’s still unclear how these microorganisms contribute to the immunity and prognosis of different types of tumors.
What this research adds
The authors of this study aimed to reanalyse the whole transcriptome data of several cancer types, focusing on tumor-resident bacteria and fungi at the species level. This information was then integrated to provide insights about tumor occurrence, prognosis, and immunity.
Conclusions
This article presents “The Cancer Microbiota Database,” an interactive and customizable tool to investigate 33 types of cancers. Through this comprehensive atlas, the user can retrieve information about the resident microbiota and its potential prognostic value.
Intratumoral bacteria and fungi vary across various cancer types, demonstrating the widespread presence of microbiota within tumors. Moreover, a specific microbiome profile showed an association with both tumor immunity and prognosis.
This information, related to 33 cancer types and retrieved from more than 9800 patients, can be found in the comprehensive and customizable “Cancer Microbiota database” recently published in Cancer Letters by Dashuang Sheng and colleagues from the Shandong University (China). The main findings emerging from the dataset are described below.
Microbiome and tumor immunity
Resident microbiota and tumorigenesis showed a strict connection across the different types of cancer. In particular:
- Escherichia coli, Pseudomonas sp. CIP-10, Acinetobacter baumannii, Staphylococcus aureus, Klebsiella pneumoniae, Cutibacterium acnes, Staphylococcus epidermidis, Pseudomonas yamanorum, Ralstonia insidiosa, and Staphylococcus simulans were found to be the top 10 most abundant bacteria, with E. coli being the most present in 27 cancer types.
- Among fungi, Malassezia restricta, Saccharomyces cerevisiae, Schizosaccharomyces pombe, Fusarium pseudograminearum, Penicillium oxalicum, Fusarium fujikuroi, Puccinia striiformis, Zymoseptoria tritici, Aspergillus chevalieri, and Psilocybe cubensis showed the highest expression.
- Alpha diversity correlates with tumor occurrence.
- Higher bacterial diversity was found in glioblastoma multiforme, kidney renal clear cell carcinoma, and lung adenocarcinoma. Lower bacterial diversity was identified for breast invasive carcinoma and stomach adenocarcinoma.
- High-immunity tumor subtypes exhibited greater bacterial and fungal richness then low-immunity subtypes.
- Specific microbial signatures were correlated with different immune cell populations and immune-related pathways within the tumor microenvironment. In particular, bacterial composition influenced 10 types of cancer (0.5% to 3.5% of the variation), and fungal composition influenced 6 types of cancer (0.5% to 6.5% of the variation).
Impact on prognosis
The tumor-resident microbiome has a prognostic significance. Indeed, the integration of the collected data provided predictive models based on local bacteria and fungi profiles showing a great correlation with overall survival. In particular, 13 out of 33 cancer types showed more than 100 potentially prognostic bacteria, less of fungi. For example:
- Four species of bacteria (Prevotella oris, Veillonella parvula, Prevotella melaninogenica, and Streptococcus cristatus) and 3 species of fungi (Fusarium fujikuroi, Colletotrichum higginsianum, and Fusarium pseudograminearum) showed a significant correlation between immunotypes and survival outcomes.
- Among the strongest correlations between bacteria and cancers, we have the models for adenoid cystic carcinoma, uveal melanoma, and uterine carcinosarcoma.
- Among the immune cells, naïve B cells, mast cells, CD8+ T cells, Treg, and M2 macrophages demonstrated the best correlation with the risk.
The “Cancer Microbiota Database”
To integrate all the information related to the tumor microbiome and its functions, the researchers developed an interactive and comprehensive tool, the Cancer Microbiota database, or TCMbio.
What can this database provide? Microbiota´s diversity and richness, differential microbiome analyses, survival projections, correlations, and microbiome functionality. The editable parameters allow the users to customize their research. The results are then delivered through tables and images to download.
In conclusion, this comprehensive study highlights the importance of the tumor-resident microbiome in cancer biology, immunity, and patient prognosis across multiple cancer types. The Cancer Microbiota database is a valuable resource for future research and potential clinical applications in cancer diagnosis, prognosis, and treatment.
