CD271+ Cells Are Diagnostic and Prognostic and Exhibit Elevated MAPK Activity in SHH Medulloblastoma
Bibliographic record
Abstract
Abstract The extensive heterogeneity both between and within the medulloblastoma subgroups underscores a critical need for variant-specific biomarkers and therapeutic strategies. We previously identified a role for the CD271/p75 neurotrophin receptor (p75NTR) in regulating stem/progenitor cells in the SHH medulloblastoma subgroup. Here, we demonstrate the utility of CD271 as a novel diagnostic and prognostic marker for SHH medulloblastoma using IHC analysis and transcriptome data across 763 primary tumors. RNA sequencing of CD271+ and CD271− cells revealed molecularly distinct, coexisting cellular subsets, both in vitro and in vivo. MAPK/ERK signaling was upregulated in the CD271+ population, and inhibiting this pathway reduced endogenous CD271 levels, stem/progenitor cell proliferation, and cell survival as well as cell migration in vitro. Treatment with the MEK inhibitor selumetinib extended survival and reduced CD271 levels in vivo, whereas, treatment with vismodegib, a well-known smoothened (SMO) inhibitor currently in clinical trials for the treatment of recurrent SHH medulloblastoma, had no significant effect in our models. Our study demonstrates the clinical utility of CD271 as both a diagnostic and prognostic tool for SHH medulloblastoma tumors and reveals a novel role for MEK inhibitors in targeting CD271+ SHH medulloblastoma cells. Significance: This study identifies CD271 as a specific and novel biomarker of SHH-type medulloblastoma and that targeting CD271+ cells through MEK inhibition represents a novel therapeutic strategy for the treatment of SHH medulloblastoma. Cancer Res; 78(16); 4745–59. ©2018 AACR.
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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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".