The Prognostic Value of FoxP3+ Tumor-Infiltrating Lymphocytes in Cancer: A Critical Review of the Literature
Bibliographic record
Abstract
CD8+ tumor-infiltrating lymphocytes (TIL) are associated with survival in a variety of cancers. A second subpopulation of TIL, defined by forkhead box protein P3 (FoxP3) expression, has been reported to inhibit tumor immunity, resulting in decreased patient survival. On the basis of this premise, several groups are attempting to deplete FoxP3+ T cells to enhance tumor immunity. However, recent studies have challenged this paradigm by showing that FoxP3+ T cells exhibit heterogeneous phenotypes and, in some cohorts, are associated with favorable prognosis. These discrepant results could arise from differences in study methodologies or the biologic properties of specific cancer types. Here, we conduct the first systematic review of the prognostic significance of FoxP3+ T cells across nonlymphoid cancers (58 studies from 16 cancers). We assessed antibody specificity, cell-scoring strategy, multivariate modeling, use of single compared with multiple markers, and tumor site. Two factors proved important. First, when FoxP3 was combined with one additional marker, double-positive T cells were generally associated with poor prognosis. Second, tumor site had a major influence. FoxP3+ T cells were associated with poor prognosis in hepatocellular cancer and generally good prognosis in colorectal cancer, whereas other cancer types were inconsistent or understudied. We conclude that FoxP3+ T cells have heterogeneous properties that can be discerned by the use of additional markers. Furthermore, the net biologic effects of FoxP3+ T cells seem to depend on the tumor site, perhaps reflecting microenvironmental differences. Thus, depletion of FoxP3+ T cells might enhance tumor immunity in some patient groups but be detrimental in others.
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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 | 0.005 | 0.014 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.003 |
| Bibliometrics | 0.012 | 0.012 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".