Abstract 265: Mechanisms of Met-dependent tumorigenesis in models of triple negative breast cancer.
Bibliographic record
Abstract
Abstract Human breast cancer is a heterogeneous disease encompassing multiple subtypes. The basal-like and claudin-low subtypes, collectively known as triple negative (TN) breast cancer, are predominantly negative for the expression of therapeutic targets (Her2 and estrogen receptors) and have poor prognosis. In human breast cancer, elevated levels of MET are correlated with TN subtypes and poor outcome, but the reasons for this are relatively unknown. The Met receptor tyrosine kinase (RTK) is a cell surface protein that is activated in response to the Hepatocyte Growth Factor (HGF). Upon stimulation, Met signaling pathways initiate a program of cell survival, migration, and invasive growth. To investigate the role of Met in tumourigenesis, we generated transgenic mice with mammary specific expression of an oncogenic variant of Met (MMTV-Metmut). These mice develop tumours with features of TN breast cancer. Tumour-initiating cells (TICs) have emerged as a key concept in prevailing models of tumour development. In breast and other solid tumours, where the bulk of the tumour mass consists of differentiated non-tumourigenic cells, TICs constitute a cell fraction of less differentiated tumourigenic cells, and have been shown to be highly resistant to radiation and chemotherapy. TICs are thus a key therapeutic target, yet little is known about TICs in TN breast cancer. Using tumoursphere assays, we have established the presence of TICs in tumours derived from MMTV-Metmut transgenic mice. MMTV-Metmut TICs have constitutively active Met. Interestingly, treatment with a small molecule inhibitor targeting Met can diminish both tumoursphere formation and proliferation. Thus, in TN breast cancers, elevated levels of Met signaling may promote TIC tumourigenicity. Here, mechanisms of Met-dependent TIC propagation and tumourigenicity will be addressed and supporting data presented. The molecular events that lead to human basal-like and claudin-low breast cancers are poorly understood. Validating a role for Met in TICs could identify key pathways involved in the pathogenesis of TN breast cancer, providing information for new therapeutic targets. Citation Format: Vanessa Y.C. Sung, Jennifer F. Knight, Morag Park. Mechanisms of Met-dependent tumorigenesis in models of triple negative breast cancer. [abstract]. In: Proceedings of the 104th Annual Meeting of the American Association for Cancer Research; 2013 Apr 6-10; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2013;73(8 Suppl):Abstract nr 265. doi:10.1158/1538-7445.AM2013-265
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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 | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".