Abstract 2274: An immune-educating therapy, Maveropepimut-S, elicits a diverse and active anti-tumor T cell response in patients with advanced recurrent ovarian cancer
Bibliographic record
Abstract
Abstract Maveropepimut-S (MVP-S) is a T cell activating immunotherapy designed within the novel DPX® immune delivery platform. MVP-S is comprised of 5 HLA class I peptides from the tumor antigen, survivin, along with the A16L T helper peptide, and the innate immune activator, polydIdC. Analysis of PBMCs collected from advanced recurrent ovarian cancer patients treated with MVP-S based therapy in the DeCidE1 trial (NCT02785250) showed robust survivin-specific T cell induction that persisted in some patients up to 420 days. Herein, we analyzed the T cell repertoires of pre- and on-treatment (on-Tx) tumor biopsies from these patients to further investigate the fate of T cells elicited by the MVP-S based therapy. Analysis of the T cell receptor beta (TCRβ) sequences revealed that MVP-S treatment actively promotes the infiltration of a new, diverse T cell repertoire with 51.6% to 94.9% new clones recruited to the on-Tx tumors. These novel clones cumulatively comprise 29.8% to 90.5% of the total intra-tumoral T cell population. Profiling of patients achieving partial response (by RECISTv1.1) versus those achieving only progressive disease indicated an increase in clonal diversity, with reduction in clonal domination, in the on-Tx tumors, suggestive of epitope spreading in these responsive patients. To evaluate frequency of survivin-specific T cells within the tumor tissue, a library of survivin-specific T cell clonotypes was prepared using in vitro expanded and sorted PBMCs. Across 33 patients of various clinical outcomes and timepoints, 309 unique, survivin-specific clones were identified. Clonotypes were found to be strongly subject-specific with very limited overlap across subjects. TCRβ sequences of circulating survivin-specific T cells were compared with TCβ repertoire in the tumor biopsies to determine clonal sequence overlap. Sixty-four of the identified survivin-specific clones (20.7%) were found in tumor samples (pre- and on-treatment); of these, 71.9% (46/64) were detected in on-treatment samples only, compared to 12.5% (8/64) in pre-treatment samples only. Importantly, survivin-specific clones were recurrently found within the top 1-10% of the most frequent clones in the on-treatment tumoral T cell population, suggesting that MVP-S therapy promoted strong enrichment and expansion of survivin-specific T cells within tumour tissue. These data indicate that treatment of advanced recurrent ovarian cancer patients with MVP-S based therapy induced robust, persistent survivin-specific T cells that were detected in circulation up to 420 days. These de novo elicited T cells were demonstrated to migrate into tumor tissues, where MVP-S therapy promoted reinvigoration of the total T cell population with new highly diverse clones including strong expansion of survivin-specific T cells. Citation Format: Kelcey Patterson, Barry Kennedy, Walead Ebrahimizadeh, Aurelio Lobo, Heather Hirsch, Heather Torrey, Valarmathy Kaliaperumal, Lisa MacDonald, Jeremy Graff, Stephan Fiset, Olga Hrytsenko. An immune-educating therapy, Maveropepimut-S, elicits a diverse and active anti-tumor T cell response in patients with advanced recurrent ovarian cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 2274.
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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 | 0.000 |
| 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".