Abstract 1154: Investigating the functional role of GPNMB in glioblastoma and the tumor immune microenvironment and its targeted elimination using CAR-Ts
Bibliographic record
Abstract
Abstract Glycoprotein nonmetastatic melanoma protein B (GPNMB) is known to be active in the extracellular matrix of glioblastoma and has been identified as a promising immunotherapy target for both tumor cells and immunosuppressive macrophages. Methods: Immunohistochemistry was performed on patient derived xenograft (PDX) brains and tissue samples of 16 patient matched primary/recurrent GBMs as well as 23 normal organ tissues. Whole cell proteomics was performed on 43 matched primary/recurrent GBM samples. Flow cytometry measured surface expression levels of GPNMB to confirm CAR-T accessibility. CRISPR/Cas9 was used to eliminate expression in GBM lines to measure proliferation and mouse survival times. GPNMB knockout clones were generated in GL261 and engrafted in immunocompetent mice to examine single cell transcriptomes using sciRNAseq at endpoint. A second-generation CAR-T was developed to target GPNMB-expressing populations, and efficacy was interrogated using standard in vitro assays and GBM PDX models. Results: The absence of GPNMB throughout most normal tissues validates the rationale of administering CAR-Ts as a safe modality for patients. GPNMB detected in residual tumors of PDX models treated orthotopically with CD133 CAR-Ts revealed it as a targetable subpopulation of GBM cells and a rational co-target alongside CD133 in the heterogeneous tumor. Tissue microarrays and whole cell proteomics found GPNMB to be upregulated in recurrent GBMs compared to primary (p=0.0349 and p=0.0033 respectively) while being absent in normal tissues. Single cell sequencing data of patient GBMs revealed GPNMB was also highly expressed in tumor-associated macrophages. Eliminating GPNMB in GBM cell lines decreased proliferation (P<0.001) and prolonged survival times in all mouse models (P<0.01) indicating its functional relevance. GPNMB knockout clones displayed downregulation of hallmark signalling pathways of GBM such as PDGFR, TGF-beta, Integrins and Stats, as well as decreased innate/adaptive immune activation. CAR-T cytotoxicity and activation was observed in vitro and in vivo resulting in decreased tumor burden (P<0.001) and increased survival times (P<0.001). Ultimately a CD133+ population was observed in residual tumors of GPNMB CAR-T treated mice at endpoint and surface expression of CD133 and GPNMB revealed co-expression and distinct populations. Conclusions: We show GPNMB influences tumor-intrinsic biology of GBM and is also active in macrophages in the recurrent GBM immune microenvironment. By targeting GPNMB along with CD133, combinatorial therapeutic regimens could target both the cancer stem cell hierarchy and its supportive niche. Administration of both CAR-T cell therapies to humanized mice engrafted with patient-derived GBMs will provide better cytotoxic coverage and potentially provide more durable therapeutic efficacy for GBM patients. Citation Format: Neil Savage, Franz J. Zemp, Nick Mikolajewicz, Hong Han, Chitra Venugopal, Chirayu Chokshi, Nazanin Tatari, Thomas Kislinger, Jason Moffat, Doug Mahoney, Sheila K. Singh. Investigating the functional role of GPNMB in glioblastoma and the tumor immune microenvironment and its targeted elimination using CAR-Ts [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 1154.
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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) | 0.002 | 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".