Abstract 3832: Defining molecular mechanisms controlling FES activation and microtubule binding as a potential strategy to limit mast cell recruitment to tumors via the SCF/KIT axis
Bibliographic record
Abstract
Abstract FES protein-tyrosine kinase (PTK) is activated downstream of the KIT receptor in mast cells, and promotes mast cell migration towards Stem cell factor (SCF), the ligand for KIT. Recently, tumor-derived SCF has been implicated in promoting mast cell recruitment leading to increased tumor vascularity and poor prognosis. FES is also a potential therapeutic target in leukemias driven by oncogenic KIT receptors that are constitutively active. Thus, defining FES activation and signaling mechanisms could lead to development of FES inhibitors as potential therapeutics in mast cell-involved tumors or KIT-driven leukemias. FES was previously shown to phosphorylate Tubulin, and localize to microtubules (MTs) in an SH2 domain-dependent manner. We hypothesized that defects in MT reorganization in FES-deficient mast cells may account for the observed defects in migration towards SCF. To map potential MT binding site(s) in FES, we performed MT binding assays, and identified two modes of FES binding, one via the N-terminal F-BAR/FX domains, and also via the SH2 domain. Interestingly, mutations predicted to disrupt oligomerization of the F-BAR/FX domains enhanced MT binding in vitro, and MT localization in vivo. Using in vitro kinase assays, we show that FES preferentially phosphorylates soluble tubulin compared to MTs, suggesting that FES recruitment to MTs may depend on their phosphorylation by other PTKs (such as Src family PTKs). In mast cells treated with SCF, FES co-localizes with MTs, including some localization to the MT organizing center (MTOC). We are currently comparing MTOC orientation in polarized wild-type and FES-deficient mast cells, and examining MT subsets marked by γ-tubulin, acetylation, and detyrosination. In conclusion, we find that FES interacts directly with MTs in vitro, and co-localizes with MTs in vivo, and hypothesize that disruption of FES-MT interaction and/or activation will be relevant therapeutic targets to limit mast cell recruitment in solid tumors, and growth of KIT-driven leukemias. Funded by an operating grant from Canadian Institutes for Health Research (MOP82882) to AWBC. Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the 102nd Annual Meeting of the American Association for Cancer Research; 2011 Apr 2-6; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2011;71(8 Suppl):Abstract nr 3832. doi:10.1158/1538-7445.AM2011-3832
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 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 | 0.000 | 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 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".