Abstract C232: B-raf/Mek/Erk Pathway inhibition induces GPNMB expression and sensitizes melanoma cells to the antibody-drug conjugate glembatumumab vedotin.
Bibliographic record
Abstract
Abstract Background: Recent advances with B-raf and Mek targeted therapies have transformed the therapeutic landscape for metastatic melanoma and improved survival times for patients. Despite this progress, resistance to targeted therapies remains a universal problem that limits treatment efficacy. Combination therapy strategies represent a viable option to overcome the problem of therapeutic resistance. Glycoprotein Non-Metastatic B (GPNMB) is a cell surface protein that is highly expressed in a wide variety of cancer types, and regulates: tumor growth, cancer cell migration, invasion and metastasis. Glembatumumab vedotin (CDX-011) is a GPNMB-targeted antibody-drug conjugate that is in clinical trials for the treatment of melanoma and breast cancer. Interestingly, a wide spectrum of kinase inhibitors (KI) has been reported to induce GPNMB expression in a variety of cell types. Here we investigate the mechanism(s) responsible for elevated GPNMB levels in melanoma cells treated with clinically relevant KI, determine whether KI-mediated induction of GPNMB expression synergizes with CDX-011 in the treatment of melanoma. Methods: B-raf mutant (A375, WM-2664) and N-ras mutant (SkMel2) melanoma cells were exposed to inhibitors of B-raf (vemurafenib, dabrafenib), or Mek (trametinib, selumetinib). Immunoblot analysis or fluorescence-activated cell sorting was used to assess GPNMB expression. B-raf mutant cells were passaged in the presence of vemurafenib over the course of several weeks to months to generate vemurafenib-resistant cells. Transient siRNA knockdown studies were used to assess the requirement for the transcription factor, MiTF, in KI-mediated induction of GPNMB. To assess the interaction between individual KI and CDX011, dose response curves for the KI and CDX-011 alone or in combination in melanoma cells in vitro were generated. Melanoma cells were either 1) pretreated or 2) pre and co-treated with KI for 48 hours prior to treatment with CDX011 for 96 hours. Cell viability was assessed by XTT assay. Results: B-raf inhibition led to an induction of total and cell surface GPNMB protein in B-raf mutant, but not in B-raf WT melanoma cells. Mek inhibition induced GPNMB expression in all three melanoma cell lines. In addition to acute inhibitor treatment, Vemurafenib-resistant cells also expressed higher levels of GPNMB when compared to parental cells (inhibitor sensitive). Knock-down of the MiTF transcription factor abrogated the vemurafenib-mediated induction of GPNMB. Pretreatment of melanoma cells with Mek inhibitors led to a reduction in cell viability, compared to untreated cells, that was further exacerbated by exposure to CDX-011, in a dose-dependent manner. Interestingly, sub-optimal doses with B-raf inhibitors did not significantly affect cell viability of WM-2664 cells when used in isolation, but did enhance the sensitivity of melanoma cells to CDX-011. Conclusions: Induction of GPNMB in response to B-raf/Mek inhibition is a MiTF-dependent process that occurs in both B-raf mutant and WT cells. In this context, induction of GPNMB expression sensitizes cells to CDX-011 mediated cell killing. As such, the combination of B-raf/Mek inihibitors with CDX-011 represents an intriguing new combination therapy strategy for the treatment of melanoma, and warrants further validation in in vivo mouse models. Citation Information: Mol Cancer Ther 2013;12(11 Suppl):C232. Citation Format: April A.N. Rose, Peter M. Siegel. B-raf/Mek/Erk Pathway inhibition induces GPNMB expression and sensitizes melanoma cells to the antibody-drug conjugate glembatumumab vedotin. [abstract]. In: Proceedings of the AACR-NCI-EORTC International Conference: Molecular Targets and Cancer Therapeutics; 2013 Oct 19-23; Boston, MA. Philadelphia (PA): AACR; Mol Cancer Ther 2013;12(11 Suppl):Abstract nr C232.
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) | 0.000 | 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".