Abstract A014: The novel anti-inflammatory agent GML (GM1-targeted linoleate-containing TLR2 ligand) inhibits sarcoma metastasis to the lung
Bibliographic record
Abstract
Abstract Sarcomas are a heterogeneous group of cancers occurring in tissues derived from the mesenchyme. Despite improved treatment strategies that include surgery and broad-based chemotherapeutics, survival of patients with sarcoma remains unchanged in the last 40 years with 5-year overall survival less than 25%. In part, this high rate of mortality can be attributed to the development of pulmonary metastases, a process that occurs in up to 50% of patients. We propose that preventing the occurrence or growth of lung metastases can improve the outcome for many of these patients. Our growing understanding of the dynamic relationship between inflammation and cancer has led to the investigation of anti-inflammatory approaches to treat cancer, including metastasis. Specifically, recent studies suggest a role for neutrophils in cancer metastasis, identifying a promising target for therapeutic intervention. The aim of the present study is to investigate the role of myeloid cells in the metastatic process, and their potential to act as therapeutic targets during the development of lung metastases. Herein we used human and syngeneic osteosarcoma lung metastatic models together with in vitro assays to assess the role of neutrophils in this process. Our results demonstrate that neutrophils are essential to facilitate the development of osteosarcoma pulmonary metastases and that treatment with the novel anti-inflammatory agent GM1-targeted linoleate-containing TLR2 ligand (GML), known to inhibit neutrophil recruitment, diminishes their occurrence. Overall, our results suggest that neutrophils play a role in mediating osteosarcoma lung metastasis and reveal GML as a potential anti-metastatic drug therapy. Citation Format: Liane Babes, Lauren A. Wierenga, Ngoc-Ha Dan, Xueqing Lun, Kimberly-Ann R. Goring, Stephen M. Robbins, Donna L. Senger. The novel anti-inflammatory agent GML (GM1-targeted linoleate-containing TLR2 ligand) inhibits sarcoma metastasis to the lung [abstract]. In: Proceedings of the AACR Special Conference: Sarcomas; 2022 May 9-12; Montreal, QC, Canada. Philadelphia (PA): AACR; Clin Cancer Res 2022;28(18_Suppl):Abstract nr A014.
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) | 0.003 | 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".