TGF-β/β2-spectrin/CTCF-regulated tumor suppression in human stem cell disorder Beckwith-Wiedemann syndrome
Bibliographic record
Abstract
Beckwith-Wiedemann syndrome (BWS) is a human stem cell disorder, and individuals with this disease have a substantially increased risk (~800-fold) of developing tumors. Epigenetic silencing of β2-spectrin (β2SP, encoded by SPTBN1), a SMAD adaptor for TGF-β signaling, is causally associated with BWS; however, a role of TGF-β deficiency in BWS-associated neoplastic transformation is unexplored. Here, we have reported that double-heterozygous Sptbn1+/- Smad3+/- mice, which have defective TGF-β signaling, develop multiple tumors that are phenotypically similar to those of BWS patients. Moreover, tumorigenesis-associated genes IGF2 and telomerase reverse transcriptase (TERT) were overexpressed in fibroblasts from BWS patients and TGF-β-defective mice. We further determined that chromatin insulator CCCTC-binding factor (CTCF) is TGF-β inducible and facilitates TGF-β-mediated repression of TERT transcription via interactions with β2SP and SMAD3. This regulation was abrogated in TGF-β-defective mice and BWS, resulting in TERT overexpression. Imprinting of the IGF2/H19 locus and the CDKN1C/KCNQ1 locus on chromosome 11p15.5 is mediated by CTCF, and this regulation is lost in BWS, leading to aberrant overexpression of growth-promoting genes. Therefore, we propose that loss of CTCF-dependent imprinting of tumor-promoting genes, such as IGF2 and TERT, results from a defective TGF-β pathway and is responsible at least in part for BWS-associated tumorigenesis as well as sporadic human cancers that are frequently associated with SPTBN1 and SMAD3 mutations.
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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".