Abstract 3133: Reprogramming of tumor-associated macrophages by a short synthetic peptide eradicates ovarian cancer
Bibliographic record
Abstract
Abstract Purpose: Ovarian cancer is the deadliest gynecologic malignancy with limited treatment options and novel therapies urgently needed. Immunosuppressive microenvironment is critical for tumor progression and immune checkpoint inhibitors, which enable T-cell anticancer immunity revolutionized the outcomes in multiple cancer types. However, this approach had limited success in ovarian cancer. Our small therapeutic peptides, derived from an endogenous type 2 tumor suppressor, Pigment Epithelium-Derived Factor (PEDF), act through an alternative immune mechanism, repolarization of tumor-associated macrophages (TAMs) to the tumor-suppressive phenotype.Experimental Design: Short peptides based on the PEDF's active domain were modified for improved stability and efficacy. Two peptides (PMD-427, PMD-336) were tested in preclinical ovarian cancer models using the human chemoresistant cell line, OvCar-3, and transformed mouse cell line ID8. We also performed mechanistic analysis of the peptides' anti-tumor action, including effects on macrophages cytotoxic, cytokine secretion and migratory activity in vitro and in vivo. Results: PEDF peptide PMD-427 caused > 20-fold reduction in tumor burden. PMD-427 induced selective apoptosis in ovarian cancer cells but not in normal ovarian epithelium. This selectivity was based on context-specific modulation of extrinsic death cascades, Fas and FasL. More importantly, PMD-427 peptides also stimulated macrophage polarization from M2 to M1 phenotype as was evidenced by the shift in cytokine profile (decreased IL-10 and increased IL-12 expression), altered morphology (increased number of dendrite-like-processes) and other changes in M2 markers (attenuated PD-L1 expression). M2/M1 macrophage polarization was also evident by tumor immunostaining. Critically, PMD peptides ovarian cancer cell killing by macrophages as was determined in co-culture studies; this fratricidal activity was reliant on the expression of TRAIL by the macrophages and of its cognate receptor, DR5 by ovarian cancer cells, respectively. Combined with enhanced macrophage motility as observed by time-lapse micropscopy, these changes resulted in increased macrophage recruitment to the tumors and enhance killing of the cancer cells in vivo. The key role of macrophages in the anti-cancer effects of PMD peptides was confirmed by depletion of macrophages in ovarian tumor bearing mice using clodronate liposomes. Conclusions: We have generated a first-in-class multi-targeted peptide drug, which promotes macrophage polarization that results in eradication of ovarian tumors in mice. Citation Format: Reshma Bhowmick, Elena Vinokour, Michael Paul Plebanek, Marisol Villanueva, Victor Shifrin, Jack Henkin, Ignacio Melgar-Asensio, James Petrik, Raghu Kallurie, Olga V. Volpert. Reprogramming of tumor-associated macrophages by a short synthetic peptide eradicates ovarian cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2018; 2018 Apr 14-18; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2018;78(13 Suppl):Abstract nr 3133.
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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".