DDDR-31. THE THERAPEUTIC POTENTIAL OF THE LONG NON-CODING RNA LNC-HLX-2-7 IN GROUP 3 MEDULLOBLASTOMAS IN CHILDREN
Bibliographic record
Abstract
Abstract Medulloblastoma (MB) is an aggressive brain tumor that predominantly affects children. Recent high-throughput sequencing studies suggest that the non-coding RNA genome, in particular long non-coding RNAs (lncRNAs), contributes to MB formation and tumor progression. Here we report the identification of a novel lncRNA, lnc-HLX-2-7, as a potential therapeutic target in group 3 MBs. In this study, we report that lnc-HLX-2-7 RNA specifically accumulates in the HLX (host gene of lnc-HLX-2-7) promoter region and activates HLX expression by recruiting multiple factors including enhancer elements. RNA sequencing and chromatin immunoprecipitation revealed that HLX directly binds to the promoters of several tumor-promoting genes, including MYC, and activates their expression. Furthermore, intravenous treatment with antisense oligonucleotides targeting lnc-HLX-2-7 coated with cerium-oxide nanoparticle (CNP-lnc-HLX-2-7) reduced tumor growth (40-50%) in intracranial MB xenograft mouse model (n = 10, p < 0.01, t-test). We found that the combinatorial therapy of CNP-lnc-HLX-2-7 and cisplatin further inhibits tumor growth and significantly prolongs mouse survival compared to CNP-lnc-HLX-2-7 monotherapy (n = 10, p < 0.01, t-test) only. We report here the importance of the lnc-HLX-2-7-HLX-MYC axis in regulating group 3 MB progression and provide a strong rationale for using lnc-HLX-2-7 as a specific and potent therapeutic target for the group 3 MBs in children.
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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".