EXTH-81. ITGA5 IS A NOVEL IMMUNOTHERAPEUTIC TARGET AGAINST TREATMENT REFRACTORY MEDULLOBLASTOMA
Bibliographic record
Abstract
Abstract Medulloblastoma (MB) is the most common type of malignant pediatric brain cancer. Current standard of care (SOC) involves maximal safe resection and neuraxis radiotherapy and chemotherapy in individuals older than 3 years. To date, these cytotoxic SOC combined with craniospinal irradiation led to devastating neurocognitive and developmental deficits impacting quality of life for pediatric patients. The biological heterogeneity of MB is highlighted by the existence of four distinct molecular subgroups (WNT, SHH, Group 3, and Group 4). Group 3 and Group 4 have the poorest patient outcomes because of their aggressive, metastatic nature, and so often remain treatment refractory to SOC. Group 3 has a poor prognosis due to its high incidence of leptomeningeal spread and an overall survival rate of less than 50%. The cytotoxic nature and lack of response in specific subtypes to SOC underscores the urgent need for developing and translating novel treatment options including immunotherapies. In our earlier work, we have developed a therapy-adapted patient derived xenograft (PDX) model of the Group 3 MB as the tumor cells undergoes therapy in vitro and in vivo. N-glycocapture surfaceome profiling of the MB cells through this PDX model identified Integrin α5 (ITGA5) as one of the most differentially expressed targets found at recurrence when compared to engraftment and untreated timepoints. Through shRNA knockdown and small molecule inhibition, we identify ITGA5 expression marks a MB cell subpopulation with increased self-renewal ability both in vitro and in vivo. Access to recurrent MB (rMB) post-therapy allowed us to investigate the changes in the surfaceome of MB cells using proteomics profiling to identify promising rMB-specific targets for rational development of novel immunotherapies.
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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 | 0.000 |
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".