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Data from Association of <i>Fusobacterium nucleatum</i> with Specific T-cell Subsets in the Colorectal Carcinoma Microenvironment

2023· preprint· en· W4361958391 on OpenAlexfundno aff
Jennifer Borowsky, Koichiro Haruki, Mai Chan Lau, Andressa Dias Costa, Juha P. Väyrynen, Tomotaka Ugai, Kota Arima, Annacarolina da Silva, Kristen D. Felt, Melissa Zhao, Carino Gurjao, Tyler S. Twombly, Kenji Fujiyoshi, Sara A. Väyrynen, Tsuyoshi Hamada, Kosuke Mima, Susan Bullman, Tabitha A. Harrison, Amanda I. Phipps, Kimmie Ng, Jeffrey A. Meyerhardt, Mingyang Song, Edward L. Giovannucci, Kana Wu, Xuehong Zhang, Gordon J. Freeman, Curtis Huttenhower, Wendy S. Garrett, Andrew T. Chan, Barbara Leggett, Vicki Whitehall, Neal I. Walker, I.G. Brown, Mark Bettington, Reiko Nishihara, Charles S. Fuchs, Jochen K. Lennerz, Marios Giannakis, Jonathan A. Nowak, Shuji Ogino

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicGut microbiota and health
Canadian institutionsnot available
FundersGary Bennett Family FundStand Up To CancerOrionin TutkimussäätiöSuomen KulttuurirahastoMitsukoshi Health and Welfare FoundationAmerican Society of Clinical OncologyNational Institutes of HealthCancer Research UKConquer Cancer FoundationJapan Society for the Promotion of ScienceAmerican Association for Cancer Research
KeywordsFusobacterium nucleatumColorectal cancerMicrosatellite instabilityBiologyCancer researchMedicineMolecular biologyInternal medicineCancerPeriodontitisGeneticsPorphyromonas gingivalis

Abstract

fetched live from OpenAlex

AbstractPurpose: While evidence indicates that Fusobacterium nucleatum (F. nucleatum) may promote colorectal carcinogenesis through its suppressive effect on T-cell–mediated antitumor immunity, the specific T-cell subsets involved remain uncertain. Experimental Design: We measured F. nucleatum DNA within tumor tissue by quantitative PCR on 933 cases (including 128 F. nucleatum–positive cases) among 4,465 incident colorectal carcinoma cases in two prospective cohorts. Multiplex immunofluorescence combined with digital image analysis and machine learning algorithms for CD3, CD4, CD8, CD45RO (PTPRC isoform), and FOXP3 measured various T-cell subsets. We leveraged data on Bifidobacterium, microsatellite instability (MSI), tumor whole-exome sequencing, and M1/M2-type tumor-associated macrophages [TAM; by CD68, CD86, IRF5, MAF, and MRC1 (CD206) multimarker assay]. Using the 4,465 cancer cases and inverse probability weighting method to control for selection bias due to tissue availability, multivariable-adjusted logistic regression analysis assessed the association between F. nucleatum and T-cell subsets. Results: The amount of F. nucleatum was inversely associated with tumor stromal CD3+ lymphocytes [multivariable OR, 0.47; 95% confidence interval (CI), 0.28–0.79, for F. nucleatum–high vs. -negative category; Ptrend = 0.0004] and specifically stromal CD3+CD4+CD45RO+ cells (corresponding multivariable OR, 0.52; 95% CI, 0.32–0.85; Ptrend = 0.003). These relationships did not substantially differ by MSI status, neoantigen load, or exome-wide tumor mutational burden. F. nucleatum was not significantly associated with tumor intraepithelial T cells or with M1 or M2 TAMs. Conclusions: The amount of tissue F. nucleatum is associated with lower density of stromal memory helper T cells. Our findings provide evidence for the interactive pathogenic roles of microbiota and specific immune cells.

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 imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Dataset · Consensus signal: none
Teacher disagreement score0.003
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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.

Opus teacher head0.021
GPT teacher head0.231
Teacher spread0.210 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreDataset

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".

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Citations0
Published2023
Admission routes1
Has abstractyes

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