Abstract B11: mTOR pathway inhibition induces GPNMB expression and sensitizes breast cancer cells to an antibody-drug conjugate targeting GPNMB
Bibliographic record
Abstract
Abstract The biggest challenge in the effective management of breast cancer is the limited duration of therapeutic benefit that is achieved with the current treatment options. Patients diagnosed with triple-negative breast cancer (TNBC), a type of breast tumor with worst prognoses, are currently treated with surgery, radiation and chemotherapy. Unfortunately, despite initial responses cancer cells become resistant to drugs and tumors relapse. We previously identified the cell surface protein GPNMB as a key mediator of breast cancer metastasis. Recently, an antibody-drug conjugate targeting GPNMB (Cdx-011) was developed that has been tested as single agent for the treatment of metastatic TNBC in a clinical trial. We have recently uncovered a novel response of TNBCs to therapeutic treatments: GPNMB expression is greatly elevated following treatment with mTOR pathway inhibitors (i.e., rapamycin, INK-128, AZD2014 and Torin-1) as well as conventional chemotherapy agents (doxorubicin, paclitaxel or cisplatin) and experimental treatments, i.e., MEK pathway inhibitors. Pharmacologically induced enhancement of GPNMB was also observed in ER+ cancers treated with antiestrogens (i.e., Fulvestrant). Interestingly, tumor cells that developed resistance to chemotherapy or antiestrogens exhibit higher levels of GPNMB. We found that therapy-induced GPNMB upregulation is mediated by the mobilization of the stress-induced MiTF/TFE family of transcription factors. In TNBC cells, mTOR inhibition promotes TFE3 nuclear translocation and GPNMB transcription. In ER+ cells, antiestrogens inactivate mTOR pathway causing TFE3 nucleus localization and GPNMB expression. We are currently conducting preclinical studies to investigate whether the upregulation of GPNMB caused by treatment with mTOR inhibitors could sensitize breast cancer cells to the activity of an antibody-drug conjugate targeting GPNMB (Cdx-011). Citation Format: Marco Biondini, April Rose, Matthew Annis, Cristiano Ferrario, Rosa Puertollano, Mark Basik, Peter Siegel. mTOR pathway inhibition induces GPNMB expression and sensitizes breast cancer cells to an antibody-drug conjugate targeting GPNMB [abstract]. In: Proceedings of the AACR Special Conference on Targeting PI3K/mTOR Signaling; 2018 Nov 30-Dec 8; Boston, MA. Philadelphia (PA): AACR; Mol Cancer Res 2020;18(10_Suppl):Abstract nr B11.
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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 | 0.001 | 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 | 0.001 |
| 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".