Abstract 384: T cell infiltration into tumors induced by DPX-Survivac combination immunotherapy demonstrated by PET/MRI imaging in an orthotopic ovarian cancer model
Bibliographic record
Abstract
Abstract Introduction: Epithelial ovarian cancers are highly aggressive and often diagnosed at late stages. To date, a limited number of these patients benefit from immunotherapies, and recurrent ovarian cancer remains an area of unmet medical need. Novel immunotherapies that generate and drive activated T cells into tumors, such as DPX-Survivac, represent a promising approach. To better understand the underlying mechanisms of action of this novel immunotherapy and how it may correlate with clinical outcomes, we used an orthotopic ovarian cancer model and a dual approach using molecular imaging to track immune cells in vivo followed by biological assays. Methods: Humanized transgenic mice (HLA-A2.1-/HLA-DR1; H-2 class-I/II knockout) were implanted with 104 syngeneic mouse ovarian surface epithelial cells in the left ovarian bursa and were either untreated or treated with DPX-Survivac, intermittent low dose cyclophosphamide and anti-PD-1. The CD8+ cytotoxic T cells (CTLs) and myeloid cells (MCs) were isolated from disease matched mice, cultured in vitro, loaded with superparamagnetic iron oxide (SPIO) nanoparticles, and injected i.v. in recipient mice. The next day, recipient mice were injected with 500µCi of 18F-fluorodeoxyglucose and imaged by magnetic resonance (MRI) and positron emission tomography (PET). Anatomical images and tumor volumes were collected with a balance steady-state free precession sequence, cells were semi-quantified using R2* maps from a multi-echo single point imaging sequence (TurboSPI) and tumor metabolism was assessed by simultaneous acquisition of PET. Mice were imaged days 41, 49, and 56 post-implant. CTLs and MCs were characterized by flow cytometry (FC) before injection into recipient mice. Following imaging completion, tumors and lymph nodes (LN) were assayed for tumor infiltrating lymphocytes. Ascites were analyzed for tumor cell to lymphocyte content by FC. Results: PET/MRI images showed that the combination immunotherapy significantly decreased primary tumor burden and improved survival rates. The recruitment of isolated CTLs and MCs was detected in both tumors and LNs. CTL recruitment to tumors was increased in mice receiving combination immunotherapy while MCs recruitment was decreased. CTLs were recruited at a higher rate to the DPX-Survivac draining LN than tumor draining LN and MCs were equally recruited to both. The expression of checkpoint inhibitor molecules on CTL did not appear to vary with treatment. CTLs from treated mice expressed higher rates of Ki67 (a proliferative marker) than CTLs from untreated mice. The treatment increased the lymphocyte:tumor cell ratio within the tumors of treated animals and included a population of CD8/CD4 double positive (DP) T cells. Differences in tumor infiltrating lymphocyte phenotype correlated with tumor burden. Conclusions: DPX-Survivac combination immunotherapy induces the recruitment of CD8+ T cells into tumors, resulting in tumor control in an orthotopic ovarian cancel model. Citation Format: Marie-Laurence Tremblay, Caitrin Sobey-Skelton, Hailey Wyatt, Victoria Gonzalez, Andrea Nuschke, Christa Davis, Alecia Mackay, Kim Bobbit, Andrea West, Barbara Vanderhyden, Genevieve Weir, Alexandra Merkx-Jacques, Kimberly Brewer, Marianne Stanford. T cell infiltration into tumors induced by DPX-Survivac combination immunotherapy demonstrated by PET/MRI imaging in an orthotopic ovarian cancer model [abstract]. In: Proceedings of the Annual Meeting of the American Association for Cancer Research 2020; 2020 Apr 27-28 and Jun 22-24. Philadelphia (PA): AACR; Cancer Res 2020;80(16 Suppl):Abstract nr 384.
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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) | 0.002 | 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".