Identification of Immunogenic Cytotoxic T Lymphocyte Epitopes Containing Drug Resistance Mutations in Antiretroviral Treatment-Naïve HIV-Infected Individuals
Bibliographic record
Abstract
BACKGROUND: Therapeutic HIV vaccines may prove helpful to intensify antiretroviral treatment (ART) efficacy and may be an integral part of future cure strategies. METHODS: We examined IFN-gamma ELISpot responses to a panel of 218 HIV clade B consensus-based HIV protease-reverse transcriptase peptides, designed to mimic previously described and predicted cytotoxic T lymphocyte epitopes overlapping drug resistance (DR) positions, that either included the consensus sequence or the DR variant sequence, in 49 ART-naïve HIV-infected individuals. Next generation sequencing was used to assess the presence of minority DR variants in circulating viral populations. RESULTS: Although a wide spectrum of differential magnitudes of response to DR vs. WT peptide pairs was observed, responses to DR peptides were frequent and strong in the study cohort. No difference between the median magnitudes of response to DR vs. WT peptides was observed. Interestingly, of the 22 peptides that were recognized by >15% of the participants, two-thirds (64%) corresponded to DR peptides. When analysing responses per peptide pair per individual, responses to only WT (median 4 pairs/individual) or DR (median 6 pairs/individual) were more common than responses to both WT and DR (median 2 pairs/individual; p<0.001). While the presence of ELISpot responses to WT peptides was frequently associated with the presence of the corresponding peptide sequence in the patient's virus (mean 68% of cases), responses to DR peptides were generally not associated with the presence of DR mutations in the viral population, even at low frequencies (mean 1.4% of cases; p = 0.0002). CONCLUSIONS: Our data suggests that DR peptides are frequently immunogenic and raises the potential benefit of broadening the antigens included in a therapeutic vaccine approach to immunogenic epitopes containing common DR sequences. Further studies are needed to assess the quality of responses elicited by DR peptides.
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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 | 0.001 |
| 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 | 0.001 | 0.000 |
| 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".