Abstract 3453: Autophagic regulation of the Met receptor tyrosine kinase in breast cancer
Bibliographic record
Abstract
Abstract The Met receptor tyrosine kinase (RTK) and its ligand, hepatocyte growth factor (HGF), are potent mediators of epithelial-mesenchymal transition and an invasive growth program. The HGF-Met signaling axis plays a significant role in the development or progression of many human cancers, and elevated Met expression is associated with poor prognosis and the basal subtype in breast cancer. Met signaling is regulated temporally and spatially through endocytic trafficking to degradative or recycling compartments, and delayed Met trafficking to the degradative pathway promotes enhanced cell migration, adhesion-independent growth and tumorigenesis. It is now recognized that autophagy, an intracellular degradative process, utilizes the endocytic system in both formation and maturation of double-membraned autophagosomes. Autophagy can have both tumor promoting and tumor suppressor roles in different contexts or stages of disease. We hypothesized that reprogramming of endocytic membrane system to support an autophagic starvation response may alter Met RTK trafficking, and therefore modulate tumorigenic signaling. To test this, we utilized MDA-MB-231 and BT-549 triple-negative breast cancer cell lines, as well as Hela cells, as models to study the trafficking and signaling of the Met RTK under conditions of autophagic stimulation or inhibition. Following HGF stimulation and receptor internalization, Met engages with core autophagic machinery in a starvation-dependent manner. Increased autophagosome formation decreases Met recycling to the plasma membrane, which can be rescued by shRNA-mediated knockdown of genes required for autophagy initiation. We demonstrate that the autophagic process negatively regulates signaling of Met through the PI3K/Akt and MAPK pathways and decreases Met-dependent cellular responses. These findings identify Met RTK regulation as a potential tumor-suppressive function of autophagy. Citation Format: Emily S. Bell, Dongmei Zuo, Morag Park. Autophagic regulation of the Met receptor tyrosine kinase in breast cancer. [abstract]. In: Proceedings of the 105th Annual Meeting of the American Association for Cancer Research; 2014 Apr 5-9; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2014;74(19 Suppl):Abstract nr 3453. doi:10.1158/1538-7445.AM2014-3453
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 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) | 0.003 | 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".