Identification of Protein-tyrosine Phosphatase 1B as the Major Tyrosine Phosphatase Activity Capable of Dephosphorylating and Activating c-Src in Several Human Breast Cancer Cell Lines
Bibliographic record
Abstract
c-Src tyrosine kinase activity is elevated in several types of human cancer, and this has been attributed to elevated c-Src expression levels, increased c-Src specific activity, and activating mutations in c-Src. We have found a number of human breast cancer cell lines with elevated c-Src specific activity that also possess elevated phosphatase activity directed against the carboxyl-terminal negative regulatory domain of Src family kinases. To identify this phosphatase, cell extracts from MDA-MB-435S cells were chromatographed and the fractions were assayed for phosphatase activity. Four peaks of phosphatase activity directed against the nonspecific substrate poly(Glu/Tyr) were detected. One peak also dephosphorylated a peptide modeled against the c-Src carboxyl-terminal negative regulatory domain and intact human c-Src. Immunoblotting and immunodepletion experiments identified the phosphatase as protein-tyrosine phosphatase 1B (PTP1B). Examination of several human breast cancer cell lines with increased c-Src activity showed elevated levels of PTP1B protein relative to normal control breast cells. In vitro c-Src reactivation experiments confirmed the ability of PTP1B to dephosphorylate and activate c-Src. In vivo overexpression of PTP1B in 293 cells caused a 2-fold increase of endogenous c-Src kinase activity. Our findings indicate that PTP1B is the primary protein-tyrosine phosphatase capable of dephosphorylating c-Src in several human breast cancer cell lines and suggests a regulatory role for PTP1B in the control of c-Src kinase activity.
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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 | 0.001 | 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".