Ca2+ Release from the Endoplasmic Reticulum of NY-ESO-1–Specific T Cells Is Modulated by the Affinity of TCR and by the Use of the CD8 Coreceptor
Bibliographic record
Abstract
Although several cancer immunotherapy strategies are based on the use of analog peptides and on the modulation of the TCR affinity of adoptively transferred T cells, it remains unclear whether tumor-specific T cell activation by strong and weak TCR stimuli evoke different Ca(2+) signatures from the Ca(2+) intracellular stores and whether the amplitude of Ca(2+) release from the endoplasmic reticulum (ER) can be further modulated by coreceptor binding to peptide/MHC. In this study, we combined functional, structural, and kinetic measurements to correlate the intensity of Ca(2+) signals triggered by the stimulation of the 1G4 T cell clone specific to the tumor epitope NY-ESO-1(157-165). Two analogs of the NY-ESO-1(157-165) peptide, having similar affinity to HLA-A2 molecules, but a 6-fold difference in binding affinity for the 1G4 TCR, resulted in different Ca(2+) signals and T cell activation. 1G4 stimulation by the stronger stimulus emptied the ER of stored Ca(2+), even in the absence of CD8 binding, resulting in sustained Ca(2+) influx. In contrast, the weaker stimulus induced only partial emptying of stored Ca(2+), resulting in significantly diminished and oscillatory Ca(2+) signals, which were enhanced by CD8 binding. Our data define the range of TCR/peptide MHC affinities required to induce depletion of Ca(2+) from intracellular stores and provide insights into the ability of T cells to tailor the use of the CD8 coreceptor to enhance Ca(2+) release from the ER. This, in turn, modulates Ca(2+) influx from the extracellular environment, ultimately controlling T cell activation.
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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 | 0.000 | 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".