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Abstract P3-07-03: GPNMB activates EGFR to overcome Mek-inhibition: Implications for the development of rational targeted therapy combinations in triple negative breast cancer

2017· article· en· W2592770830 on OpenAlexaff
April A. N. Rose, Matthew G. Annis, Dru Perkins, Peter M. Siegel

Bibliographic record

VenueCancer Research · 2017
Typearticle
Languageen
FieldMedicine
TopicHER2/EGFR in Cancer Research
Canadian institutionsMcGill UniversityOccupational Cancer Research Centre
Fundersnot available
KeywordsTriple-negative breast cancerMAPK/ERK pathwayMedicineCancer researchTargeted therapyBreast cancerMelanomaOncologyCancerInternal medicineSignal transductionBiologyCell biology

Abstract

fetched live from OpenAlex

Abstract Background: TNBC is an aggressive subtype that constitutes ~15% of all BC. Currently there are no targeted therapies available for patients with. As such, there is much interest in developing targeted therapies for this disease. Recently we identified GPNMB as a transmembrane protein that promotes breast tumor growth and metastasis. CDX-011 is an antibody drug conjugate that targets GPNMB, and has recently shown promising clinical activity in patients with GPNMB+TNBC. In subset analyses of the EMERGE trial, patients with high GPNMB expressing TNBC had a median OS of 10 vs. 5.5 months for CDX011 versus chemotherapy, respectively. Response rates to CDX011 correlated with degree of GPNMB expression. These findings support the hypothesis that TNBC with high GPNMB will respond better to CDX011. As such, we sought to identify therapies with intrinsic activity against TNBC that would also induce GPNMB expression, in order to synergize with CDX-011. We have recently shown that MAPK pathway inhibition induces GPNMB expression in melanoma. Therefore we sought to determine whether Mek inhibition (Mek-i) induced GPNMB in TNBC and the targeted therapies could synergize with CDX-011. Results: We interrogated the TCGA breast datasets to determine whether the MAPK pathway is more frequently altered in TNBC. Indeed, this pathway is altered in 94% of Basal compared to 60% LumA, 83% LumB, 73% Her2 subtypes. Furthermore, we show that a Mek-activation transcriptional signature is significantly higher in basal compared to Her2 or Luminal subtypes. Indeed, we show that Fra, a downstream target of activated Erk, is most highly expressed in BC cells of the basal subtype. We used immunoblot and FACS analysis to assess GPNMB expression in response to Mek-i; trametinib and cobimetinib markedly induced GPNMB protein expression in 12 of the 14 TNBC cell lines tested. Moreover, we show that in the TCGA dataset, low expression of the Mek-activity signature correlates with higher GPNMB, specifically within the basal subtype, thus providing clinical corroboration for our in vitro observations. We go on to show that Mek-i mediated GPNMB up-regulation is regulated by TFE3. We find that EGFR is upregulated in response to Mek inhibition in several TNBC cells. GPNMB heterodimerizes with EGFR in immunoprecipitation experiments. Using siRNA to knockdown GPNMB or ectopic GPNMB overexpression, we found that GPNMB is both necessary and sufficient for enhanced EGFR activation in response to Mek-i in TNBC. Finally, we used CRISPR-CAS9 to delete genomic GPNMB from murine lung-metastatic TNBC cell lines. 533LM2 grow in syngeneic Balb/c mice. Here we show that GPNMB is required for tumor growth and metastasis in vivo. Mek-i slows tumor growth; but the combination of GPNMB deletion with Mek-i led to tumor regression, and significantly impaired tumor growth and metastasis relative to all other groups. Conclusions: Together our data show that the MAPK pathway is hyperactivated in TNBC; inhibiting this pathway impairs tumor growth, but enhances GPNMB, which facilitates mammary tumor growth and metastasis in the setting of Mek-i. These data provide rationale for combined targeting of GPNMB and the MAPK pathway in TNBC. Citation Format: Rose A, Annis M, Perkins D, Siegel P. GPNMB activates EGFR to overcome Mek-inhibition: Implications for the development of rational targeted therapy combinations in triple negative breast cancer [abstract]. In: Proceedings of the 2016 San Antonio Breast Cancer Symposium; 2016 Dec 6-10; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2017;77(4 Suppl):Abstract nr P3-07-03.

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)0.001
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: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0030.001

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 head0.217
GPT teacher head0.507
Teacher spread0.291 · 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 designNot applicable
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".

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Citations0
Published2017
Admission routes1
Has abstractyes

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