Abstract B009: GBM cells mimic regulatory T cell function to protect the CSC pool from immune surveillance in recurrent GBM
Bibliographic record
Abstract
Abstract Glioblastoma (GBM) is the most lethal and aggressive form of brain cancer, with incredibly high recurrence rates and virtually no long-term survival. Despite our growing understanding of GBM at the molecular level, we still don’t fully comprehend the molecular mechanisms driving recurrence in GBM. Current knowledge indicates that Glioma Stem Cells (GSCs) drive a resistant cell phenotype in GBM. Understanding the molecular events coordinated by GSCs leading to therapy-resistance can provide key advancements on how we treat recurrent GBM (rGBM). Mechanisms of GSC immune escape are considered fundamental to clinical GBM growth and recurrence. The cross talk between cancer cells and the immune system is now classified as a hallmark of cancer. The current dogma is that cancer cells, including GSCs, influence recruitment of immune-suppressive cell subsets to tumor tissue, however how subsets of GSCs mimic this immune-suppressive effect within the tumor microenvironment remains to be elucidated. Single-cell RNA sequencing analysis of GBM neurospheres revealed a previously unrecognized Oct4/Sox2high/FOXP3− cell subpopulation with high expression of TGFb1, CD39, CD73, PD-L1, and Galectin-1, a gene expression fingerprint typically associated with regulatory T cell (Tregs) and their immune suppressive functions within the tumor microenvironment. Bioinformatics analysis of public databases shows that the above-mentioned genes are enriched in the mesenchymal GBM subtype and highly correlated with TGFb type II receptor (TGFBR2) expression in clinical GBM. Mechanistically, we show that blocking TGFBR2 or XBP1 signaling, key intermediary of this process, counteracts the immune-suppressive phenotype of rGBM cells by restoring CD4 and CD8 tumor killing capacity and reversing exhaustion. By combining miRNA-based network analysis and advanced nanoparticle formulation for miRNA delivery we show that miR-16/124-3p effectively target all nodes of this immunosuppressive axis successfully blocking the immunosuppressive nature of rGBM cells. This research provides the first description of such neoplastic cells in any malignancy and has high potential translational impact since targeting these tumor cell subsets and their immunosuppressive mechanisms may be critical to the successful development of GBM immunotherapies. Citation Format: Hernando Lopez-Bertoni, Sophie Sall, Harmon Khela, Jack Korleski, Katherine Luly, Maya Johnson, Amanda Johnson, Jordan Green, John Laterra. GBM cells mimic regulatory T cell function to protect the CSC pool from immune surveillance in recurrent GBM [abstract]. In: Proceedings of the AACR Special Conference in Cancer Research: Tumor Immunology and Immunotherapy; 2023 Oct 1-4; Toronto, Ontario, Canada. Philadelphia (PA): AACR; Cancer Immunol Res 2023;11(12 Suppl):Abstract nr B009.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.001 | 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 teacher head, 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".