Prognostic Significance of Tumor-Infiltrating B Cells and Plasma Cells in Human Cancer
Bibliographic record
Abstract
Abstract There is abundant evidence that tumor-infiltrating CD8+ T cells contribute positively to antitumor immunity; however, the role of tumor-infiltrating B cells (TIL-B) and plasma cells (PC) remains controversial, leading to differing opinions about whether immunotherapies should be designed to enhance or inhibit these cells. Through a comprehensive PubMed search, we reviewed publications with cohorts of 50 or more cases in which the prognostic value of TIL-B/PC was assessed by immunohistochemistry and/or gene-expression analysis. Sixty-nine studies representing 19 cancers met our review criteria. The large majority of studies assessed TIL-B by immunohistochemical detection of CD20. Of these, 50.0% reported a positive prognostic effect for CD20+ TIL-B, whereas the remainder found a neutral (40.7%) or negative (9.3%) effect. These differences in prognostic effect were not attributable to cancer type, other clinicopathologic factors, or differing technical approaches. The prognostic significance of TIL-B/PC was generally concordant with that of CD3+ and/or CD8+ T cells, and the prognostic effect of T cells was generally stronger when TIL-B and/or PC were also present. Additionally, 21 studies inferred the presence of TIL-B/PC from gene-expression data, and a large majority reported a positive prognostic effect. Although more studies are required involving additional cancer types and independent patient cohorts, the weight of evidence supports a positive role for TIL-B and PC in antitumor immunity, suggesting that enhancement of these responses should be considered in the design of cancer immunotherapies.
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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 | 0.004 | 0.014 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.007 | 0.009 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".