Altered PTPN13–β-catenin interaction by pathogenic mutations and involvement of this axis in B-cell receptor signalling
Bibliographic record
Abstract
Protein tyrosine phosphatase non-receptor type 13 (PTPN13) is a non-receptor protein tyrosine phosphatase with context-dependent roles as tumour suppressor or promoter. Its modular structure supports multiple molecular interactions, including a critical one with β-catenin, a regulator of the haematopoietic system. We previously identified three pathogenic PTPN13 mutations in families with acute lymphoblastic leukaemia (ALL), anaemia, and/or inherited bone marrow failure (IBMF). Our current findings reveal that these mutations impair the PTPN13-β-catenin interaction. β-catenin and PTPN13 are stabilised upon B-cell receptor (BCR) activation, while PTPN13 silencing reduces Bruton's tyrosine kinase (BTK) activation and β-catenin levels, indicating that PTPN13 modulates BCR signalling at multiple points. Together with prior evidence showing that PTPN13 mutations compromise protein stability and decrease β-catenin levels, these data support a role for disrupted lymphoid signalling. Altered expression of key surface markers (CD25 and CD38) upon silencing of either PTPN13 or β-catenin further supports this interpretation. In conclusion, our study identifies the PTPN13-β-catenin axis as a critical regulator of lymphoid cell homeostasis and highlights its disruption as a potential driver of haematological abnormalities in patients carrying PTPN13 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".