Abstract 6535: Association of <i>Bacteroides fragilis</i> and enterotoxigenic <i>Bacteroides fragilis</i> with specific T-cell subsets in the colorectal carcinoma microenvironment
Bibliographic record
Abstract
Abstract Objectives: Experimental studies indicate that Bacteroides fragilis (BF), including enterotoxigenic Bacteroides fragilis (ETBF), could contribute to colorectal tumorigenesis through immune-mediated inflammation. However, the interactive effect of BF, ETBF, and T cell infiltrates in colorectal tumors is still unclear. In particular, not all T cells are the same, and the implications of different T cell subsets are uncertain; therefore, it is crucial to identify specific T cell subsets associated with BF and ETBF. We hypothesized that infiltration of certain T cell subsets might differ by tumor BF and ETBF status in colorectal cancer tissue. Methods: The abundance of BF and ETBF was measured by the quantitative polymerase chain reaction in 827 incident colorectal cancer cases that had occurred in the Health Professionals Follow-up Study and Nurses’ Health Study. T cell density in intraepithelial and stromal regions was assessed by a customized 9-plex multispectral immunofluorescence assay (CD3, CD4, CD8, CD45RA, CD45RO, FOXP3, KRT, MKI67, and DAPI) with digital image analyses and pathologist-supervised machine learning algorithms. We analyzed the association of the abundance of BF and ETBF with T cell subset densities using logistic regression models adjusted for age at diagnosis, sex, primary tumor location (proximal, distal, rectal), MSI, CIMP status, and BRAF and KRAS mutation status. We also applied the multivariable-adjusted Cox proportional hazards model using the same covariates to estimate the hazard ratios (HRs) for colorectal cancer-specific mortality according to BF or ETBF status. Two-sided P values <0.005 were considered statistically significant as recommended by the expert statisticians. Results: Among 827 cases with available tumor BF, ETBF, and T cell data, BF levels were negative, low, and high in 416 (51%), 205 (25%), and 206 (25%) cases, respectively. ETBF levels were negative, low, and high in 753 (91%), 36 (4%), and 38 (5%) cases, respectively. High abundance of BF was statistically significantly associated with a lower stromal CD3+CD4+FOXP3+ regulatory T cell density [multivariable OR, 0.61; 95% confidence interval (CI), 0.45-0.84, for BF-high vs. -negative category; P trend = 0.0034]. ETBF was not significantly associated with the densities of any T cell subsets. Neither BF (HR of high vs. negative, 0.84; 95% CI, 0.59−1.26) nor ETBF (HR of high vs. negative, 0.65; 95% CI, 0.34−1.25) was associated with colorectal cancer-specific mortality. Conclusions: We observed that a high abundance of BF was associated with lower stromal CD3+CD4+FOXP3+ regulatory T cell density in the tumor microenvironment. Our findings support the interactive effect of BF on specific T cells, which could explain why colorectal tumors harbor highly variable BF abundances and T cell densities. Citation Format: Satoko Ugai, Yuxue Zhong, Yasutoshi Takashima, Kosuke Matsuda, Claire E. Thomas, Daniel D. Buchanan, Conghui Qu, Li Hsu, Steven Gallinger, Robert C. Grant, Marios Giannakis, Meredith Hullar, Jeroen R. Huyghe, Sushma S. Thomas, Ulrike Peters, Amanda I. Phipps, Jonathan A. Nowak, Tomotaka Ugai, Shuji Ogino. Association of Bacteroides fragilis and enterotoxigenic Bacteroides fragilis with specific T-cell subsets in the colorectal carcinoma microenvironment [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2025; Part 1 (Regular Abstracts); 2025 Apr 25-30; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2025;85(8_Suppl_1):Abstract nr 6535.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".