Advances in Molecular Targets for the Treatment of Medulloblastomas
Bibliographic record
Abstract
PURPOSE: To present an assortment of molecular targets evident from a variety of signal transduction pathways and downstream effectors, which may have clinical relevance for the treatment of medulloblastomas. SOURCE: Data were archived from MEDLINE, using Boolean-formatted queries on the keywords including: medulloblastoma, pathology, prognosis, classification, tumor regression, inhibition, therapy, clinical trial, therapeutic agent, drug, molecular inhibitor, and signalling pathway. Only the most reputable articles were selected for critical analyses based on the qualitative assessment of the citation index, novelty of the findings and relevance to prospective novel ways of targeted therapies for medulloblastomas. PRINCIPAL FINDINGS: Medulloblastomas are highly aggressive embryonal tumors of the cerebellum, akin to primitive neuroectodermal tumors elsewhere in the brain. Current treatments for medulloblastomas which include a combination of surgery, chemotherapy and radiation, remain challenging especially, for younger patients; however, advances in understanding regulatory pathways in medulloblastomas are crucial to develop more effective therapeutic targets. Evidence showing several molecular and pharmacological targets within key signalling pathways, such as HEDGEHOG, WNT, NOTCH, Receptor Tyrosine Kinase (ERB, IGF-IR, c-MET, PDGF, Estrogen, p75NTR) , their downstream effectors like PI3K/AKT, c-MYC and STAT3, and as well as other targets such as telomerase and cytoskeletal elements, is summarized. All molecular and pharmacological targets have pivotal roles in the pathogenesis of medulloblastomas. Most importantly, these pathways can be effectively pharmacologically targeted to regress the growth of medulloblastomas. Pre-clinical studies were routinely undertaken with a variety of human and murine cell lines and as well as murine models of medulloblastomas. Thus far, two drugs which target the NOTCH and HEDGEHOG signalling have completed Phase I clinical trials, but with evidence of low efficacies; hence, reinforcing the importance of continuing investigations in search of new therapeutic agents and targets. CONCLUSION: Novel therapies, based on better understanding key biological pathways in medulloblastomas, hold promise for improved treatments in due course among patients with medulloblastomas.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.002 |
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".