Colorectal tumor-specific regulatory and effector CD4+ T cell responses: translating laboratory results to the clinic (P2159)
Bibliographic record
Abstract
Abstract The adaptive immune response to colorectal cancer (CRC) has a crucial role in prolonging host survival. Increased tumor infiltrates of CD3+ T cells can improve patient outcome, yet other T cell subsets exist that are capable of suppressing anti-tumor responses. Our lab has found that suppression of tumor-specific Th1 responses is associated with progression of CRC. Here, the phenotype and function of CD4+ T cells derived from PBMC, colon and tumor samples were analysed for suppressive markers by FACS, and anti-tumor responses by IFN-γ ELISPOT. CRC patients with more advanced tumors responded to fewer epitopes and generated a significantly weaker epitope-specific T cell response to the oncofetal antigen, 5T4 than healthy donors (p=0.0006). The mechanism of loss of T cell response is independent of HLA-DR subtype or patient age, but human depletion experiments both in vitro and in vivo indicates suppression by Foxp3+ regulatory CD4+ T cells. These cells were found in abundance amongst tumor-infiltrating lymphocytes; however, another equally prominent population of IL-10 and TGF-β-producing CD4+Foxp3- T cells were found to be >100-fold more suppressive. Thus, a major caveat to cancer immunotherapy is the suppressive tumor microenvironment, which contributes to the selective decline of measurable anti-tumor CD4+ T cell responses as tumors progress. These responses are enhanced in CRC patients by depleting regulatory T cells.
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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 | 0.000 |
| 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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 0.002 |
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".