B7–H3 as a Prognostic Biomarker and Therapeutic Target in Pediatric central nervous system Tumors
Bibliographic record
Abstract
B7-H3 (CD276), a member of the B7 superfamily, is an important factor in downregulating immune responses against tumors. It is also aberrantly expressed in many human malignancies. Beyond immune regulatory roles, its overexpression has been linked to invasive metastatic potential and poor prognosis in patients with cancer. Antibody-dependent cell-mediated cytotoxicity strategies targeting B7-H3 are currently in development, and early-phase clinical trials have shown encouraging preliminary results. To understand the role of B7-H3 in pediatric central nervous system (CNS) malignancies, a comprehensive panel of primary CNS tumors of childhood was examined by immunohistochemistry for levels and extent of B7-H3 expression. In addition, B7-H3 m-RNA expression status and association with overall survival in various pediatric CNS tumor types was accessed by curating publicly available patient gene expression data sets derived from bioinformatics analysis and visualization platforms (GlioVis). We demonstrate that B7-H3 is broadly expressed in pediatric glial and nonglial CNS tumors, and its aberrant expression, as determined by immunohistochemical staining intensity, correlates with tumor grade. Moreover, high B7-H3 m-RNA expression is significantly associated with worse survival and could potentially improve prognostication in various brain tumor types of childhood. B7-H3 can be used as a therapeutic target, given its tumor selectivity and the availability of targeted therapeutic agents to this antigen.
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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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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".