Gab1 but not Grb2 mediates tumor progression in Met overexpressing colorectal cancer cells
Bibliographic record
Abstract
Hepatocyte growth factor receptor (Met) plays an important role in the progression of multiple cancer types. The overexpression of Met in DLD-1 colon carcinoma cells with kirsten rat sarcoma oncogene homolog (KRAS) oncogene activation resulted in enhanced subcutaneous and orthotopic tumor growth rate and increased metastatic potential. To elucidate the mechanism of this effect, we stably expressed kinase-inactive Met(K1110A), Src homology 2 (SH2)-binding domain-inactive Met(Y1349/1356F), growth factor receptor-bound protein 2 (Grb2) non-binding Met(N1358H) and mutant receptors with ability to selectively recruit signaling proteins Grb2, src homology domain c-terminal adaptor homolog (Shc), phospholipase c-gamma (PLCgamma) and p85 phosphatidyl inositol 3 kinase. As subcutaneous implants, DLD-1 cells that expressed the majority of these receptor constructs failed to recapitulate the tumor growth-enhancing effect of the wild-type Met receptor. The Grb2- and Shc-recruiting Met mutants demonstrated slight but consistent tumor-suppressive activity, whereas the expression of N1358H mutant stimulated tumor growth rate comparable with the wild-type receptor. This suggests that direct Grb2/Shc binding does not contribute to the tumor progression activity of Met receptor. The tumors expressing Grb2- and Shc-recruiting Met receptors demonstrated a marked loss in Grb2-associated adaptor protein 1 (Gab1) protein levels, which was not observed in the cell lines, consistent with a post-translationally regulated process. Moreover, a moderate level of Gab1 overexpression stimulated tumor growth. The findings suggest a delicate balance for intact Y1349/1356 SH2-binding domain to mediate the tumor progression activity of the coactivated Met-rat sarcoma oncogene homolog (RAS) pathways. Selectivity for specific adaptor protein involvement may be the key that determines the tissue- and cell-type specificity of Met-mediated tumorigenicity in human cancers.
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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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".