Understanding CD8<sup>+</sup> T‐cell responses toward the native and alternate HLA‐A∗02:01‐restricted WT1 epitope
Bibliographic record
Abstract
The Wilms’ tumor 1 (WT1) antigen is expressed in solid and hematological malignancies, but not healthy tissues, making it a promising target for cancer immunotherapies. Immunodominant WT1 epitopes, the native HLA‐A2/WT1126‐134 (RMFPNAPYL) (HLA‐A2/RMFPNAPYL epitope (WT1A)) and its modified variant YMFPNAPYL (HLA‐A2/YMFPNAPYL epitope (WT1B)), can induce WT1‐specific CD8+ T cells, although WT1B is more stably bound to HLA‐A∗02:01. Here, to further determine the benefits of those two targets, we assessed the naive precursor frequencies; immunogenicity and cross‐reactivity of CD8+ T cells directed toward these two WT1 epitopes. Ex vivo naive WT1A‐ and WT1B‐specific CD8+ T cells were detected in healthy HLA‐A∗02:01+ individuals with comparable precursor frequencies (1 in 105–106) to other naive CD8+ T‐cell pools (for example, A2/HIV‐Gag77‐85), but as expected, ~100 × lower than those found in memory populations (influenza, A2/M158‐66; EBV, A2/BMLF1280‐288). Importantly, only WT1A‐specific naive precursors were detected in HLA‐A2.1 mice. To further assess the immunogenicity and recruitment of CD8+ T cells responding to WT1A and WT1B, we immunized HLA‐A2.1 mice with either peptide. WT1A immunization elicited numerically higher CD8+ T‐cell responses to the native tumor epitope following re‐stimulation, although both regimens produced functionally similar responses toward WT1A via cytokine analysis and CD107a expression. Interestingly, however, WT1B immunization generated cross‐reactive CD8+ T‐cell responses to WT1A and could be further expanded by WT1A peptide revealing two distinct populations of single‐ and cross‐reactive WT1A+CD8+ T cells with unique T‐cell receptor‐αβ gene signatures. Therefore, although both epitopes are immunogenic, the clinical benefits of WT1B vaccination remains debatable and perhaps both peptides may have separate clinical benefits as treatment targets.
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 | 0.000 |
| 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".