Dynamic Src Tyrosine Kinase Signaling Directs Invadopodia Formation and Function in Head and Neck Cancer: Novel Insights into the Original Oncogene
Bibliographic record
Abstract
Cancer cell invasion and motility is mediated through actin-rich protrusions that facilitate migration through extracellular matrix and degradation of tissue barriers. Src tyrosine kinase is an essential catalyst of motile actin networks and is a potent mediator of the metastatic program. The Src substrate cortactin is a critical scaffold that links kinase signaling to cytoskeletal dynamics. Both Src and cortactin are overexpressed in several human cancers and their expression is associated with poor prognosis. These proteins are not associated with the initiation of tumorigenesis, but are thought to play a vital role in the metastatic process. The overall aim of my work is to determine the molecular mechanisms by which Src and cortactin promote the invasive cancer phenotype. Further understanding of these processes provided by the following studies, could provide clinical benefits for cancer patients with advanced disease. Study one demonstrates treatment with the Src-targeted small molecule inhibitor saracatinib impairs tumor cell invasion in vitro and lymph node metastasis in vivo. Further, we identify that Src inhibition decreased invadopodia formation and MMP expression in HNSCC cell lines. Study two identifies regulated WT Src activity as essential for governing invadopodia maturation in HNSCC cells and Src transformed fibroblasts. In addition, we establish cortactin phosphorylation downstream of Src as central to this process. In study three we examine the role of the EGFR/MEK pathway upstream of Src and cortactin in regulating cell migration and lamellipodia dynamics. Lastly, study four outlines an attempt to create a transgenic model of HNSCC tumor cell invasion in which cortactin is overexpressed in the oral cavity of tumorigenic mice.
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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 | 0.000 |
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".