Quantitative Phospho-Proteomic Profiling of Hepatocyte Growth Factor (HGF)-MET Signaling in Colorectal Cancer
Bibliographic record
Abstract
Colorectal cancer (CRC) is the second leading cause of death from cancer. The MET receptor tyrosine kinase and/or its ligand HGF are frequently amplified or overexpressed in CRC. It is known that tyrosine phosphorylated proteins are involved in progression and metastasis of colorectal cancer; however, little is known about the MET phospho-proteome in CRC. High resolution mass spectrometry was used to characterize immunoaffinity-purified, phosphotyrosine (pY)-containing tryptic peptides of the MET-expressing CRC cell model, DLD1. A total of 266 unambiguously identified pY sites spanning 168 proteins were identified. Quantification of mass spectrometry ion currents identified 161 pY sites, including many not previously linked to MET signaling, that were modulated in abundance by HGF stimulation. Overlay of these data with protein-protein interaction data sets suggested that many of the identified HGF-modulated phospho-proteins may be directly or indirectly associated with MET. Analysis of pY sequence motifs indicated a prevalence of Src family kinase consensus sequences, and reciprocal signaling between Src and MET was confirmed by using selective small molecule inhibitors of these kinases. Therefore, using quantitative phospho-proteomics profiling, kinase modulation by ligand and inhibitors, and data integration, an outline of the MET signaling network was generated for the CRC model.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.000 | 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 teacher head, 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".