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Record W4383737510 · doi:10.1186/s40478-023-01609-7

Dynamic profiling of medulloblastoma surfaceome

2023· article· en· W4383737510 on OpenAlexafffund
David Bakhshinyan, Yujin Suk, Laura Kuhlmann, Ashley Adile, Vladimir Ignatchenko, Stefan Custers, William D. Gwynne, Andrew Macklin, Chitra Venugopal, Thomas Kislinger, Sheila K. Singh

Bibliographic record

VenueActa Neuropathologica Communications · 2023
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicCellular Mechanics and Interactions
Canadian institutionsMcMaster University Medical CentrePrincess Margaret Cancer CentreUniversity of TorontoMcMaster University
FundersCanadian Cancer Society Research InstituteCanadian Institutes of Health ResearchOntario Institute for Cancer ResearchMach-Gaensslen Foundation of Canada
KeywordsMedulloblastomaProfiling (computer programming)MedicineNeuroscienceComputational biologyBioinformaticsBiologyComputer sciencePathology

Abstract

fetched live from OpenAlex

Medulloblastoma (MB) is the most common type of malignant pediatric brain cancer. The current standard of care (SOC) involves maximal safe resection and chemoradiotherapy in individuals older than 3 years, often leading to devastating neurocognitive and developmental deficits. Out of the four distinct molecular subgroups, Group 3 and 4 have the poorest patient outcomes due to the aggressive nature of the tumor and propensity to metastasize and recur post therapy. The toxicity of the SOC and lack of response in specific subtypes to the SOC underscores the urgent need for developing and translating novel treatment options including immunotherapies. To identify differentially enriched surface proteins that could be evaluated for potential future immunotherapeutic interventions, we leveraged N-glycocapture surfaceome profiling on Group 3 MB cells from primary tumor, through therapy, to recurrence using our established therapy-adapted patient derived xenograft model. Integrin 𝛼5 (ITGA5) was one of the most differentially enriched targets found at recurrence when compared to engraftment and untreated timepoints. In addition to being enriched at recurrence, shRNA-mediated knockdown and small molecule inhibition of ITGA5 have resulted in marked decrease in proliferation and self-renewal in vitro and demonstrated a survival advantage in vivo. Together, our data highlights the value of dynamic profiling of cells as they evolve through therapy and the identification of ITGA5 as a promising therapeutic target for recurrent Group 3 MB.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.190
Threshold uncertainty score0.385

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.025
GPT teacher head0.293
Teacher spread0.268 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

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".

Quick stats

Citations4
Published2023
Admission routes2
Has abstractyes

Explore more

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