PTP1B Contributes to the Oncogenic Properties of Colon Cancer Cells through Src Activation
Bibliographic record
Abstract
Src-specific activity has been reported to be elevated in a high percentage of colon cancer cell lines and tumors, but the underlying mechanisms are largely unknown. In this study, we report that, in the seven cancer cell lines tested, Src-specific activity was elevated (5.2- to 18.7-fold) relative to normal colon cells (FHC). This activation of Src correlated with reduced phosphorylation at Y530 of Src, whereas there was no significant change in the level of phosphorylation at Y419. The membrane tyrosine phosphatase activity for a Src family-specific phosphopeptide substrate FCP (Fyn COOH-terminal peptide phosphorylated by Csk) was greatly increased in the cancer cells and was attributed to PTP1B in most of the cell lines. Membrane PTP1B protein levels were also greatly increased. Overexpression of PTP1B increased Src specific activity in colon cancer cells by reducing phosphorylation at Y530 of Src. It also increased anchorage-independent cell growth and this increase was blocked by the Src inhibitor PP2 and Src small interfering RNA (siRNA). Down-regulating PTP1B activity by PTP1B inhibitor CinnGEL 2Me or knocking down PTP1B using siRNA also reduced Src kinase activity and colony formation ability of colon cancer cells. PTP1B siRNA reduced tumor growth in nonobese diabetic/severe combined immunodeficient mice. This study suggests that (a) PTP1B can act as an important activator of Src in colon cancer cells via dephosphorylation at Y530 of Src and (b) elevated levels of PTP1B can increase tumorigenicity of colon cancer cells by activating Src.
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 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 | 0.001 |
| 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".