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Record W4406219590 · doi:10.3390/curroncol32010035

Single-Cell RNA Sequencing Reveals LEF1-Driven Wnt Pathway Activation as a Shared Oncogenic Program in Hepatoblastoma and Medulloblastoma

2025· article· en· W4406219590 on OpenAlexvenueno aff
Christophe Desterke, Yuanji Fu, Jenny Bonifacio-Mundaca, Claudia Monge, Pascal Pineau, Jorge Mata-Garrido, Raquel Francés

Bibliographic record

VenueCurrent Oncology · 2025
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicHippo pathway signaling and YAP/TAZ
Canadian institutionsnot available
Fundersnot available
KeywordsMedulloblastomaWnt signaling pathwayHepatoblastomaCancer researchTranscriptomeBiologyMedicineOncologyGeneticsInternal medicineGene expressionGene

Abstract

fetched live from OpenAlex

(1) Background: Hepatoblastoma and medulloblastoma are two types of pediatric tumors with embryonic origins. Both tumor types can exhibit genetic alterations that affect the β-catenin and Wnt pathways; (2) Materials and Methods: This study used bioinformatics and integrative analysis of multi-omics data at both the tumor and single-cell levels to investigate two distinct pediatric tumors: medulloblastoma and hepatoblastoma; (3) Results: The cross-transcriptome analysis revealed a commonly regulated expression signature between hepatoblastoma and medulloblastoma tumors. Among the commonly upregulated genes, the transcription factor LEF1 was significantly expressed in both tumor types. In medulloblastoma, LEF1 upregulation is associated with the WNT-subtype. The analysis of LEF1 genome binding occupancy in H1 embryonic stem cells identified 141 LEF1 proximal targets activated in WNT medulloblastoma, 13 of which are involved in Wnt pathway regulation: RNF43, LEF1, NKD1, AXIN2, DKK4, DKK1, LGR6, FGFR2, NXN, TCF7L1, STK3, YAP1, and NFATC4. The ROC curve analysis of the combined expression of these 13 WNT-related LEF1 targets yielded an area under the curve (AUC) of 1.00, indicating 100% specificity and sensitivity for predicting the WNT subtype in the PBTA medulloblastoma cohort. An expression score based on these 13 WNT-LEF1 targets accurately predicted the WNT subtype in two independent medulloblastoma transcriptome cohorts. At the single-cell level, the WNT-LEF1 expression score was exclusively positive in WNT-medulloblastoma tumor cells. This WNT-LEF1-dependent signature was also confirmed as activated in the hepatoblastoma tumor transcriptome. At the single-cell level, the WNT-LEF1 expression score was higher in tumor cells from both human hepatoblastoma samples and a hepatoblastoma patient-derived xenotransplant model; (4) Discussion: This study uncovered a shared transcriptional activation of a LEF1-dependent embryonic program, which orchestrates the regulation of the Wnt signaling pathway in tumor cells from both hepatoblastoma and medulloblastoma.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.003
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

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 science0.0000.000
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 head0.046
GPT teacher head0.336
Teacher spread0.290 · 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 source (direct Gemma or distilled Codex), 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

Citations6
Published2025
Admission routes1
Has abstractyes

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