The Interaction between Intratumoral Microbiome and Immunity Is Related to the Prognosis of Ovarian Cancer
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Study information
-
Quality control
- Retracted paper
- Contamination issues suspected
- Batch effect issues suspected
- Uncontrolled confounding suspected
- Results are suspect (various reasons)
- Tags applied
study design
Citation
PMID PubMed identifier for scientific articles.
DOI Digital object identifier for electronic documents.
URI
Authors
Sheng D, Yue K, Li H, Zhao L, Zhao G, Jin C, Zhang L
Journal
Microbiology spectrum
Year
2023
Keywords:
gynecological, microbiome, ovarian cancer, prognostic biomarkers, tumor microenvironment
Microbiota can influence the occurrence, development, and therapeutic response of a wide variety of cancer types by modulating immune responses to tumors. Recent studies have demonstrated the existence of intratumor bacteria inside ovarian cancer (OV). However, whether intratumor microbes are associated with tumor microenvironment (TME) and prognosis of OV still remains unknown. The RNA-sequencing data and clinical and survival data of 373 patients with OV in The Cancer Genome Atlas (TCGA) were collected and downloaded. According to the knowledge-based functional gene expression signatures (Fges), OV was classified into two subtypes, termed immune-enriched and immune-deficient subtypes. The immune-enriched subtype, which had higher immune infiltration enriched with CD8+ T cells and the M1 type of macrophages (M1) and higher tumor mutational burden, exhibited a better prognosis. Based on the Kraken2 pipeline, the microbiome profiles were explored and found to be significantly different between the two subtypes. A prediction model consisting of 32 microbial signatures was constructed using the Cox proportional-hazard model and showed great prognostic value for OV patients. The prognostic microbial signatures were strongly associated with the hosts' immune factors. Especially, M1 was strongly associated with five species (Achromobacter deleyi and Microcella alkaliphila, Devosia sp. strain LEGU1, Ancylobacter pratisalsi, and Acinetobacter seifertii). Cell experiments demonstrated that Acinetobacter seifertii can inhibit macrophage migration. Our study demonstrated that OV could be classified into immune-enriched and immune-deficient subtypes and that the intratumoral microbiota profiles were different between the two subtypes. Furthermore, the intratumoral microbiome was closely associated with the tumor immune microenvironment and OV prognosis. IMPORTANCE Recent studies have demonstrated the existence of intratumoral microorganisms. However, the role of intratumoral microbes in the development of ovarian cancer and their interaction with the tumor microenvironment are largely unknown. Our study demonstrated that OV could be classified into immune-enriched and -deficient subtypes and that the immune enrichment subtype had a better prognosis. Microbiome analysis showed that intratumor microbiota profiles were different between the two subtypes. Furthermore, the intratumor microbiome was an independent predictor of OV prognosis that could interact with immune gene expression. Especially, M1 was closely associated with intratumoral microbes, and Acinetobacter seifertii could inhibit macrophage migration. Together, the findings of our study highlight the important roles of intratumoral microbes in the TME and prognosis of OV, paving the way for further investigation into its underlying mechanisms.
Experiment 1
Reviewed Marked as Reviewed by Svetlana up on 2024-4-8
Curated date: 2024/03/18
Curator: Muqtadirat
Revision editor(s): Muqtadirat, Scholastica, Peace Sandy
Subjects
- Location of subjects
- China
- Host species Species from which microbiome was sampled. Contact us to have more species added.
- Homo sapiens
- Body site Anatomical site where microbial samples were extracted from according to the Uber Anatomy Ontology
- Ovary Animal ovary,Female gonad,Female organism genitalia gonad,Female organism genitalia gonada,Female organism reproductive system gonad,Female organism reproductive system gonada,Female reproductive system gonad,Female reproductive system gonada,Genitalia of female organism gonad,Genitalia of female organism gonada,Gonad of female organism genitalia,Gonad of female organism reproductive system,Gonad of female reproductive system,Gonad of genitalia of female organism,Gonad of reproductive system of female organism,Gonada of female organism genitalia,Gonada of female organism reproductive system,Gonada of female reproductive system,Gonada of genitalia of female organism,Gonada of reproductive system of female organism,Ovaries,Ovarium,Ovum-producing ovary,Reproductive system of female organism gonad,Reproductive system of female organism gonada,Ovary,ovary
- Condition The experimental condition / phenotype studied according to the Experimental Factor Ontology
- Ovarian cancer cancer of ovary,cancer of the ovary,malignant neoplasm of ovary,malignant neoplasm of the ovary,malignant ovarian neoplasm,malignant ovarian tumor,malignant ovary neoplasm,malignant tumor of ovary,malignant tumor of the ovary,malignant tumour of ovary,ovarian cancer,ovarian cancer, epithelial,ovarian malignant tumor,ovarian neoplasm,ovary cancer,ovary neoplasm,primary ovarian cancer,tumor of the ovary,Ovarian cancer
- Group 0 name Corresponds to the control (unexposed) group for case-control studies
- Immune-enriched subtype (clust2)
- Group 1 name Corresponds to the case (exposed) group for case-control studies
- Immune-deficient subtype (clust1)
- Group 1 definition Diagnostic criteria applied to define the specific condition / phenotype represented in the case (exposed) group
- Patients with the ovarian cancer subtype which is characterized by the lack of immune infiltration and high tumor purity
- Group 0 sample size Number of subjects in the control (unexposed) group
- 191
- Group 1 sample size Number of subjects in the case (exposed) group
- 182
- Antibiotics exclusion Number of days without antibiotics usage (if applicable) and other antibiotics-related criteria used to exclude participants (if any)
- None
Lab analysis
- Sequencing type
- PCR
- 16S variable region One or more hypervariable region(s) of the bacterial 16S gene
- Not specified
- Sequencing platform Manufacturer and experimental platform used for quantifying microbial abundance
- Illumina
Statistical Analysis
- Data transformation Data transformation applied to microbial abundance measurements prior to differential abundance testing (if any).
- relative abundances
- Statistical test
- LEfSe
- Significance threshold p-value or FDR threshold used for differential abundance testing (if any)
- 0.05
- MHT correction Have statistical tests be corrected for multiple hypothesis testing (MHT)?
- Yes
- LDA Score above Threshold for the linear discriminant analysis (LDA) score for studies using the popular LEfSe tool
- 2
Alpha Diversity
- Shannon Estimator of species richness and species evenness: more weight on species richness
- unchanged
- Richness Number of species
- unchanged
Signature 1
Reviewed Marked as Reviewed by Svetlana up on 2024-4-8
Source: Fig. 3C
Description: Significant differentially abundant taxonomic biomarkers between immune-deficient subtype (clust1) and immune-enriched subtype (clust2) identified by LEfSe
Abundance in Group 1: increased abundance in Immune-deficient subtype (clust1)
Revision editor(s): Scholastica
Signature 2
Reviewed Marked as Reviewed by Svetlana up on 2024-4-8
Source: Fig. 3C
Description: Significant differentially abundant taxonomic biomarkers between immune-deficient subtype (clust1) and immune-enriched subtype (clust2) identified by LEfSe
Abundance in Group 1: decreased abundance in Immune-deficient subtype (clust1)
Revision editor(s): Scholastica
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