The Interaction between Intratumoral Microbiome and Immunity Is Related to the Prognosis of Ovarian Cancer

Study information

Reviewed Marked as Reviewed by Svetlana up on 2024-4-8

study design

cross-sectional observational, not case-control

Citation

PMID PubMed identifier for scientific articles.

36975828

DOI Digital object identifier for electronic documents.

10.1128/spectrum.03549-22

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

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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

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Curated date: 2024/03/25

Curator: Scholastica

Revision editor(s): Scholastica

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)

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Aeromonas dhakensis
Bacillus subtilis
Coxiella endosymbiont of Amblyomma nuttalli
Cutibacterium modestum
Delftia acidovorans
Dermacoccus nishinomiyaensis
Fusobacterium nucleatum
Halopseudomonas phragmitis
Halopseudomonas sabulinigri
Mycobacteroides chelonae
Nitrospirillum amazonense
Pseudomonas asplenii
Aquipseudomonas campi
Pseudomonas cavernae
Pseudomonas citronellolis
Pseudomonas congelans
Pseudomonas cremoricolorata
Metapseudomonas furukawaii
Pseudomonas glycinae
Pseudomonas iranensis
Pseudomonas marincola
Pseudomonas oryzae
Pseudomonas promysalinigenes
Pseudomonas sp. 02C 26
Pseudomonas sp. B10
Pseudomonas sp. DR 5-09
Pseudomonas sp. DY-1
Pseudomonas sp. LPB0260
Pseudomonas sp. R3-18-08
Pseudomonas sp. R84
Pseudomonas sp. S11A 273
Pseudomonas sp. St316
Pseudomonas sp. Z003-0.4C(8344-21)
Pseudomonas syringae
Pseudomonas vanderleydeniana
Pseudomonas viciae
Pseudomonas xanthosomatis
Pseudomonas zeae
Sinorhizobium meliloti
Staphylococcus capitis
Streptococcus mitis
Pseudomonas sp. CFSAN084952
Pseudomonas sp. A214
Pseudomonas sp. OST1909
Legionella longbeachae
Pseudomonas sp. St29
Pseudomonas tensinigenes

Revision editor(s): Scholastica

Signature 2

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Reviewed Marked as Reviewed by Svetlana up on 2024-4-8

Curated date: 2024/03/25

Curator: Scholastica

Revision editor(s): Scholastica

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)

NCBI	Quality Control	Links
Pseudomonas aeruginosa
Acinetobacter baumannii
Hydrogenophaga sp. NH-16
Acinetobacter junii
Vibrio anguillarum
Comamonas thiooxydans
Burkholderia ubonensis
Pseudomonas sp. C27(2019)
Cupriavidus metallidurans
Arthrobacter woluwensis
Aquisphaera giovannonii

Revision editor(s): Scholastica