Identification of fallopian tube microbiota and its association with ovarian cancer

  1. Bo Yu  Is a corresponding author
  2. Congzhou Liu
  3. Sean C Proll
  4. Enna Manhardt
  5. Shuying Liang
  6. Sujatha Srinivasan
  7. Elizabeth Swisher
  8. David N Fredricks  Is a corresponding author
  1. Department of Obstetrics and Gynecology, United States
  2. Stanford Maternal & Child Health Research Institute, Stanford University School of Medicine, United States
  3. Vaccine and Infectious Disease Division, Fred Hutchinson Cancer Center, United States
  4. Department of Obstetrics and Gynecology, University of Washington, United States
5 figures, 1 table and 6 additional files

Figures

Bacterial concentration of each swab sample and DNA extraction controls as measured by broad-range 16S rRNA gene PCR.

*p-value <0.001, paired t-test, comparing each sample type with fallopian tube/ovarian surface (FTO) samples. PG = paracolic gutter; LP = laparoscopic port.

Diversity of identified bacterial species.

(A) PCA plot of candidate fallopian tube (FT) microbiota (84 bacterial species). FT (green) samples have more similarities with paracolic gutter (blue) than with cervical (red) samples. (B) Shannon diversity plot of 726 bacterial species identified after filtering step #5 in Supplementary file 3. *p-value <0.001, paired t-test, comparing between sample types and between cancer versus non-cancer samples within the same sample type. FTO = fallopian tube/ovarian surface; PG = paracolic gutter.

Overview of all participants with processing batch, cancer status, menopausal status, and age in relation to fallopian tube (FT) microbiome taxa.

Each column is a patient, and each row is a bacterial species. The top rows indicate the metadata of each sample as denoted by the color coding of batch, cancer status, menopausal status, and age group.

Prevalence of the 84 bacterial species in ovarian cancer versus non-cancer cases.

Each number is the percentage of individuals in each category with the presence of each bacterial species. G = gastrointestinal; O = oral; V = vaginal; S = skin; B = broadly present.

Figure 4—source data 1

Prevalence of the 84 bacterial species in ovarian cancer versus non-cancer cases.

https://cdn.elifesciences.org/articles/89830/elife-89830-fig4-data1-v1.xlsx
The bacterial prevalence in fallopian tube (FT) samples from ovarian cancer patients by histology subtypes (non-serous versus serous carcinoma).

Each number is the percentage of individuals in each category with the presence of each bacterial species.

Figure 5—source data 1

Prevalence in ovarian cancer patients by histology subtypes.

https://cdn.elifesciences.org/articles/89830/elife-89830-fig5-data1-v1.xlsx

Tables

Table 1
Demographic characteristics of participants.
Ovarian cancer patients (n = 81)Non-cancer patients (n = 106)p-value
Average age at diagnosis59.755.30.052
Average age at surgery59.651.6<0.001
Post-menopausal62 (76.5%)48 (45.3%)<0.001
Race0.492
- Asian7 (8.6%)4 (3.8%)
- Black1 (1.2%)3 (2.8%)
- Other6 (7.4%)5 (4.7%)
- White64 (79.0%)92 (86.80%)
 - Undisclosed3 (3.7%)2 (1.9%)
Ethnicity0.218
- Hispanic3 (3.7%)1 (0.9%)
- Non-Hispanic73 (90.1%)102 (96.2%)
- Undisclosed5 (6.2%)3 (2.8%)
Cancer stage at surgeryN/A
   119 (23.5%)-
   26 (7.45%)-
   339 (48.2%)-
   416 (19.8%)-
   NA1 (1.2%)-
Cancer gradeN/A
   16 (7.4%)-
   23 (3.7%)-
   364 (79.0%)-
   41 (1.2%)-
Tumor histology typeN/A
- Adenocarcinoma3-
- Carcinosarcoma1-
- Clear cell8-
- Endometrioid10-
- Granulosa cell1-
- Mucinous2-
- Serous53-
- Transitional cell1-
- Borderline serous*-8
- Other-98
Surgical type<0.001
- Laparotomy75 (92.6%)28 (26.4%)
- Laparoscopy3 (3.7%)42 (39.6%)
- Robotic assisted3 (3.7%)36 (34.0%)
Pelvic washing<0.001
- Positive43 (53.1%)3 (2.8%)
- Negative22 (27.2%)99 (93.4%)
- NA16 (19.8%)4 (3.8%)
  1. *

    Borderline serous tumors are considered in the non-cancer category in this study due to the non-invasiveness of these tumors.

Additional files

Supplementary file 1

Summary of samples sequenced.

https://cdn.elifesciences.org/articles/89830/elife-89830-supp1-v1.docx
Supplementary file 2

Bacterial concentration (log10[16S rRNA genes/μl of DNA]) of each sample type and the p-value of each comparison.

https://cdn.elifesciences.org/articles/89830/elife-89830-supp2-v1.docx
Supplementary file 3

Processing steps and result summary after each step.

https://cdn.elifesciences.org/articles/89830/elife-89830-supp3-v1.docx
Supplementary file 4

Comparison of overall and laparotomy cases in the bacterial prevalence in fallopian tube (FT) samples from ovarian cancer versus non-cancer patients.

Each number is the percentage of individuals in each category with the presence of each bacterial species.

https://cdn.elifesciences.org/articles/89830/elife-89830-supp4-v1.docx
Supplementary file 5

The bacterial prevalence in fallopian tube (FT) samples from non-cancer patients: comparison of laparoscopic/robotic and laparotomy cases.

Each number is the percentage of individuals in each category with the presence of each bacterial species.

https://cdn.elifesciences.org/articles/89830/elife-89830-supp5-v1.docx
MDAR checklist
https://cdn.elifesciences.org/articles/89830/elife-89830-mdarchecklist1-v1.pdf

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  1. Bo Yu
  2. Congzhou Liu
  3. Sean C Proll
  4. Enna Manhardt
  5. Shuying Liang
  6. Sujatha Srinivasan
  7. Elizabeth Swisher
  8. David N Fredricks
(2024)
Identification of fallopian tube microbiota and its association with ovarian cancer
eLife 12:RP89830.
https://doi.org/10.7554/eLife.89830.3