Abstract 5669: Targeting post-surgical breast cancer metastasis through combining natural killer T cell immunotherapy and low dose chemotherapy
Bibliographic record
Abstract
Abstract Breast cancer is the most common cancer in Canadian women and the second leading cause of cancer deaths. Given that most mammary tumors are surgically resectable and over 90% of breast cancer-associated deaths are due to metastasis, new therapeutic strategies targeting metastasis are required. Natural killer T (NKT) cells are a rare population of immune cells that have been shown to limit primary tumor growth and target distant metastatic disease in various animal models. We have shown that NKT cell activation improves survival in a model of post-surgical metastatic breast cancer. We are now expanding this work to determine whether NKT cell activation can be combined with chemotherapies to improve outcomes. In our model, 4T1 mammary carcinoma cells were injected into the mammary fatpad of syngeneic BALB/c mice. Tumors were resected at day 12, and mice were treated with cyclophosphamide or gemcitabine. On day 17, NKT cells were activated by transfer of dendritic cells loaded with the glycolipid antigen α-GalCer. We also examined whether gemcitabine or mafosphamide (active component of cyclophosphamide) would induce immunogenic cell death of 4T1 cells in culture. Chemotherapeutics did not affect NKT cell activation as measured by serum IFNγ levels. Treatment with cyclophosphamide, gemcitabine, or α-GalCer-loaded dendritic cells alone reduced metastasis and prolonged survival. Combined treatments significantly enhanced survival. NKT cell activation decreased the frequency and immunosuppressive function of myeloid derived suppressor cells (MDSCs). Treatments resulted in enhanced tumor specific immunity as surviving mice exhibited slower tumor growth following secondary tumor challenge. Gemcitabine and mafosphamide also increase the immunogenicity of cancer cells in vitro by increasing the exposure/release of MHCI, MHCII, CD1d, Calreticulin, HMGB1 and ATP. NKT cell activation therapy can successfully be combined with low doses of gemcitabine or cyclophosphamide to enhance protection against tumor metastasis and recurrence. This work provides a clear rationale for combining chemotherapy with NKT cell immunotherapy to target metastatic disease in the clinical setting. Citation Format: Simon Gebremeskel, Kaitlyn Tanner, Lynnea Lobert, Brent Johnston. Targeting post-surgical breast cancer metastasis through combining natural killer T cell immunotherapy and low dose chemotherapy [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2017; 2017 Apr 1-5; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2017;77(13 Suppl):Abstract nr 5669. doi:10.1158/1538-7445.AM2017-5669
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
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".