Adoptive Transfer of Tumor-Reactive Melan-A-Specific CTL Clones in Melanoma Patients Is Followed by Increased Frequencies of Additional Melan-A-Specific T Cells
Bibliographic record
Abstract
In this study, we report the adoptive transfer of highly tumor-reactive Melan-A-specific T cell clones to patients with metastatic melanoma, and the follow-up of these injected cells. These clones were generated from HLA-A*0201 patients by in vitro stimulations of total PBMC with the HLA-A*0201-binding Melan-A peptide analog ELAGIGILTV. Ten stage IV melanoma patients were treated by infusion of these CTL clones with IL-2 and IFN-alpha. The generated T cell clones, of effector/memory phenotype were selected on the basis of their ability to produce IL-2 in response to HLA-A*0201 Melan-A-positive melanoma lines. Infused clones were detected, by quantitative PCR, in the blood of three patients for periods ranging from 7 to 60 days. Six patients showed regression of individual metastases or disease stabilization, and one patient experienced a complete response, but no correlation was found between the detection of the infused clones in PBMC or tumor samples and clinical responses. Nonetheless, frequencies of Melan-A/A2-specific lymphocytes, measured by tetramer labeling, increased after treatment in most patients. In one of these patients, who showed a complete response, this increase corresponded to the expansion of new clonotypes of higher avidity than those detected before treatment. Together, our results suggest that infused CTL clones may have initiated an antitumor response that may have resulted in the expansion of a Melan-A-specific CTL repertoire.
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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".