Abstract A036: Surfaceome profiling of rhabdomyosarcoma reveals B7-H3 as a mediator of immune evasion
Bibliographic record
Abstract
Abstract Introduction: Pediatric rhabdomyosarcoma (RMS) is the most common soft tissue tumor in children, with nearly 20% of children presenting with locally aggressive and/or metastatic disease. Despite aggressive chemotherapy and radiotherapy, the 5-year overall survival rate is still less than 40%. In addition, resistance to chemotherapy remains the major cause of cancer-related mortality. Therefore, there is an unmet need to develop more effective and tolerable therapeutic strategies for the treatment of RMS. Our overall objective is to leverage transcriptomic and proteomic profiling methods to identify RMS-specific surface proteins targetable with immune-based therapies. Methods: To identify therapeutic targets, we performed cell-surface capture and mass spectrometry on fusion-positive (FP), fusion-negative (FN) RMS and normal skeletal muscle. Transcriptomic datasets of RMS tumor specimens and normal tissue were employed to identify high-confidence RMS-specific cell-surface proteins. Expression of immune checkpoint molecules was confirmed by flow cytometry, western blot and PCR. Paraffin-embedded tissue sections were used to determine protein expression and prognostic value in RMS patients. We developed an in vitro T-cell killing assay to assess the functional role of immune checkpoint molecules on the antitumor immune response. Results: Surfaceome profiling of RMS cells revealed unique protein signatures specific for each tumor type and normal tissue. We have identified 5061 cell-surface proteins in RMS and 31.6% of proteins were correctly located at the plasma membrane. By integrating proteomic and transcriptomic data, we have identified 30 and 38 proteins significantly overexpressed in fusion-negative and fusion-positive RMS respectively compared to normal muscle. We have identified the immune checkpoint molecule B7-H3 as cell-surface protein overexpressed in both RMS subtypes. Strong expression of B7-H3 was also observed in patient’s tumor specimens. Genetic deletion of B7-H3 gene in RMS cells was associated with higher antitumor immune response in tumor cells co-cultured with CD8+-T cells. No difference was observed in tumor cell proliferation and radioresistance. Conclusions: Through integrated transcriptomic and proteomic profiling, we have discovered B7-H3 as a key regulator of tumor immune-evasion in RMS. B7-H3 is a suitable immunotherapy target for the treatment of RMS. Further studies are warranted to elucidate underlying mechanisms of B7-H3 function in RMS. Citation Format: Roxane R. Lavoie, Fabrice Lucien, Patricio C. Gargollo, Mohamed E. Ahmed, Yohan Kim, Emily Baer, Doris Phelps, Cristine M. Charlesworth, Benjamin J. Madden, Liguo Wang, Peter J. Hougthon, John Cheville, Haidong Dong, Candace F. Granberg. Surfaceome profiling of rhabdomyosarcoma reveals B7-H3 as a mediator of immune evasion [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 A036.
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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) | 0.001 | 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 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".