Elucidating Met Receptor Tyrosine Kinase Interactome to Identify Novel Regulators of Met Biology
Bibliographic record
Abstract
Met receptor tyrosine kinase is a growth factor receptor implicated in multiple diseases, including cancers, whereby aberrantly activated Met underlies metastasis, survival, sustained proliferation and angiogenesis of tumor cells, and thus is a sought-out target in cancer drug discovery. However, despite its critical role, Met and its associated functions are considerably understudied, and this is further underlined by paucity of successful therapeutics and precision medicine approaches targeting Met-mediated oncogenicity. Given that protein-protein interactions (PPIs) govern protein function and are, since recently, considered to be druggable, novel knowledge and new therapeutic strategies can be uncovered by identifying and characterizing interacting partners of Met. Using the Mammalian Membrane Two-Hybrid (MaMTH) PPI mapping technology developed in our lab, this thesis takes a PPI mapping approach to enable study of Met to uncover novel regulators of Met biology. In this study, I have generated and characterized a MaMTH-compatible PPI mapping platform, which expresses inducible full-length Met, recapitulates known Met localization, and can detect previously known interactors of Met. Utilizing this platform, I have further mapped a targeted interactome of Met against SH2/PTB-domain containing proteins and FpClass-predicted putative interactors of Met, and identified thirty-two, including sixteen novel, interactors of Met. Non-small cell lung cancer (NSCLC)-focused functional characterization of one of the novel Met-interacting protein, B cell LiNKer (BLNK), reveal that BLNK is a positive regulator of Met signalling, and modulates surface localization and HGF-dependent trafficking of Met in NSCLC cell lines. Molecular studies in HEK293 models reveal that in the presence of BLNK, interaction between Met and its known interacting protein, GRB2 is increased, while the known constitutive interaction between BLNK and GRB2 is also increased in the presence of active Met. Finally, tumor phenotypical assays further uncover roles for BLNK in anchorage independent growth and chemotaxis of NSCLC cell lines. Cumulatively, my PhD thesis provides a PPI mapping platform for Met, targeted PPI map of Met, and describes a role for BLNK, a novel PPI of Met identified through this study, in regulating Met biology in NSCLC.
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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".