Abstract A008: Mechanisms of immune escape in NF1-associated peripheral nerve sheath tumors
Bibliographic record
Abstract
Abstract Background: Neurofibromatosis type 1 (NF1) is a neurogenetic condition characterized by neurocognitive symptoms, cutaneous findings, and a predisposition for benign and malignant tumors including peripheral nerve sheath tumors (PNST). About half of patients with NF1 develop plexiform neurofibromas (pNF), non-malignant tumors that often grow rapidly during childhood and can cause significant deformity, disruption of function, and pain. Some lesions, denoted atypical neurofibromatous neoplasms of uncertain biologic potential (ANNUBP), exhibit atypia, loss of neurofibroma architecture, high cellularity and mitotic activity, as an immediate precursor to malignant transformation. For people with NF1 there is a 10-15% overall lifetime risk of developing the aggressive soft tissue sarcoma malignant peripheral nerve sheath tumors (MPNST). Despite many clinical trials of chemotherapy and targeted agents, there has been little advancement in treatment outcomes and overall patient survival remains poor; therefore, new therapeutic approaches are needed. PNST are made up of transformed Schwann cell precursors, which do not grow and survive in isolation but rather interact with infiltrating immune cells. A deeper understanding of the relationship between the pre-existing immunity and the tumor microenvironment (TME) will help unveil potential for new combinations and adjuvant therapies for patients with PNST. Methods: We have developed a unique Johns Hopkins biospecimen repository of human NF1-associated PNST specimens. We use quantitative and spatial resolution of the geography and nature of tumor infiltrating immune cells in human PNST and have determined the interactions of T cells, myeloid cells, and immunoregulatory molecules, using a combination of multiplex chromogenic, high-dimensional flow cytometry and gene expression profiling studies. We have also analyzed existing transcriptomic datasets from 21 pNF and 34 MPNST cases. Results: RNA sequence analysis revealed an accumulation of immunosuppressive Th2 cells and tumor infiltrating myeloid cells (TIM) in the TME of PNST, which we postulate generates an anti-inflammatory response against tumors. Immunophenotyping of 17 pNF, 8 ANNUBP, and 15 MPNST human specimens confirmed the higher presence of infiltrating myeloid compared to lymphoid cells, with a predominance of CD163+ myeloid cells (TIM) during progression to malignancy. We also detected a significant increase in regulatory T cells and cytotoxic CD8+ T cells in MPNST vs ANNUBP vs pNF and near absence of CD19+ B cells in all tumor types. Multiparameter flow cytometry of single cells suspensions are being studied to further investigate the association of myeloid inflammation leading to the immune evasion of PNST. Conclusions: An immunosuppressive microenvironment characterizes PNST during the process of malignant transformation, generating an immune-excluded phenotype. Leveraging the immune contexture and the mechanisms of immune modulation in PNST will inform interventions to stimulate anti-tumor immunity in this dire disease. Citation Format: Lindy Zhang, Kai Pollard, Ana Calizo, Alexandre Maalouf, Aditya Suru, Jiawan Wang, Jineeta Banerjee, Christine A. Pratilas, Nicolas J. Llosa. Mechanisms of immune escape in NF1-associated peripheral nerve sheath tumors [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 A008.
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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 | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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".