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Record W7058254650

Mechanisms of MET-dependent tumour initiation and progression

2019· dissertation· en· W7058254650 on OpenAlexafffund

Bibliographic record

VenueeScholarship@McGill (McGill) · 2019
Typedissertation
Languageen
FieldMaterials Science
TopicHigh voltage insulation and dielectric phenomena
Canadian institutionsMcGill University
FundersFonds de Recherche du Québec - Santé
KeywordsCancerBreast cancerReceptor tyrosine kinaseTyrosine kinaseGene signatureEstrogen receptorSignal transductionTriple-negative breast cancerGene
DOInot available

Abstract

fetched live from OpenAlex

MET is a receptor tyrosine kinase that, when dysregulated, contributes to oncogenic progression in a wide range of human cancers. When activated, MET coordinates a program of invasive growth and migration that largely overlaps with the process of epithelial-mesenchymal transition (EMT). The induction of an EMT program can generate cells with increased tumourigenicity and properties associated with stem cells. Cells enriched with tumour-initiating capacity are commonly termed tumour-initiating cells (TICs) and have been found to be resistant to conventional therapies and thus can contribute to recurrence. Indeed, TICs possess a gene signature that converges with cells that have undergone an EMT. MET is implicated in TIC regulation in a number of cancers, however the mechanisms by which it promotes the propagation of TICs has yet to be fully elucidated. Breast cancer is a heterogeneous disease with multiple distinct subtypes that differ both in gene expression and prognosis. Triple negative breast cancer (TNBC) is an aggressive subtype that is negative for expression of estrogen receptor, progesterone receptor, and HER2 amplification, and therefore lacks targeted therapies and has poor prognosis. Elevated levels of MET are observed in 15-20% of all breast cancers and is associated with TNBC as well as poor survival. Using a MMTV-Metmt;Trp53fl/+;Cre murine model of the claudin-low subtype of TNBC, which features highly mesenchymal tumours with amplified and constitutively active Met protein, we show that a Met-dependent EMT program is required for an enhanced tumour-initiating capacity. We uncover a mechanism by which signaling through Met and fibroblast growth factor receptor 1 (FGFR1) can both independently regulate tumourigenic potential, and combinatorial targeting of both receptors is needed to abrogate TICs in both in vitro and in vivo studies. We find co-expression of MET and FGFR1 in human TNBC cell lines and in patient-derived xenografts of TNBC, and that dual inhibition of both receptors likewise depletes TIC populations. Importantly, human TNBCs with highly mesenchymal characteristics are significantly enriched for expression of HGF and FGFR1 expression, and co-expression predicts poor prognosis among these patients. These findings provide a role for MET in TNBC tumour initiation and maintenance, where it sustains a mesenchymal program that promotes a state of cellular plasticity conducive to tumourigenesis. Co-regulation of TICs by MET and FGFR1 is facilitated by pathways mediated through FGFR substrate 2 (FRS2), a scaffold protein first identified in FGFR signaling. While MET is not conventionally known to signal through FRS2, we find that FRS2 is in fact required for MET-dependent cellular processes such as invasion and survival in a number of MET-amplified cancer cell lines. We further show in breast cancer cell lines that HGF-stimulated activation of non-amplified and wildtype MET promotes FRS2 phosphorylation and maintains ERK1/2 phosphorylation in the absence of FGFR signaling. These findings describe a previously uncharacterized role for FRS2 in MET-driven biology.

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 imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.001

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.

Opus teacher head0.015
GPT teacher head0.256
Teacher spread0.241 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2019
Admission routes2
Has abstractyes

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