Abstract 506: Targeting Y-box binding protein-1 (YB-1) overcomes drug resistance in triple-negative breast cancer.
Bibliographic record
Abstract
Abstract Despite advances in treating breast cancer, disease recurrence rates remain high and secondary tumors are often resistant to chemotherapy and incurable. Currently, the treatment for triple-negative breast cancer (TNBC) relies upon conventional chemotherapeutics as there are no targeted therapies available. Although these tumors initially respond well, they paradoxically have the highest relapse rates. Y-box binding protein-1 (YB-1) is an oncogenic transcription/translation factor abundantly expressed in TNBC (∼70% of patients). It is activated predominantly by phosphorylation via p90 ribosomal S6 kinase (RSK). Once activated it up-regulates the tumor-initiating-cell (TIC) marker CD44 and induces a TIC phenotype[1]. Due to their inherent drug-resistance, TICs survive chemotherapy and go on to drive relapse[2]. We recently identified RSK2 is critical to the survival of TNBC[3]. Inhibiting RSK2 blocks activation of YB-1 and induces apoptosis in TNBC, including CD44+/CD24- cells. Interestingly, inducing YB-1 is sufficient for transformation of human mammary epithelial cells into TNBC. Moreover, P-YB-1S102 is associated with poor overall survival (P<0.001) and relapse (P<0.001) in a cohort of 1057 patients with invasive breast cancer. Taken together, these data indicate YB-1 is important both in the genesis and maintenance of TNBC and implicate it as a key mediator of drug-resistance and relapse within this subtype. Residual cells after paclitaxel or epirubicin have increased P-RSKS221/7, P-YB-1S102 and CD44 and retain mammosphere-forming capability. Cells expressing high P-YB-1S102 exclusively proliferate in the presence of these chemotherapies. Inhibiting YB-1 suppresses growth and induces apoptosis in residual cells and in CD44+/CD24–sorted cells. Pre-emptive knockdown of YB-1 prevents induction of CD44 and sensitizes cells to treatment with paclitaxel. Moreover, blocking RSK/YB-1 signaling suppresses growth and induces cell death in primary TNBC cells (x43) derived from a patient that eventually relapsed. To investigate the role of RSK/YB-1 signaling in bona fide drug-resistant cells, we created paclitaxel-resistant SUM149 cells (SUM149-PTXR) which are cultured in 2 nM paclitaxel (PTX); a concentration that kills >90% of paclitaxel-naive SUM149’s (SUM149-DMSO) by 72 hrs. These cells express increased P-RSKS221/7 and P-YB-1S102 without alterations in total protein levels. Despite their resistance to paclitaxel, these cells remain sensitive to RSK/YB-1 signaling inhibition. We are currently comparing the response of TNBC either with or without YB-1 to paclitaxel in an in vivo orthotopic xenograft model. Collectively, these data indicate that inhibiting RSK/YB-1 signaling can overcome drug resistance and potentially reduce relapse in TNBC. 1.To K, Fotovati A et al. (2010) 2.Li X, Lewis MT et al. (2008) 3.Stratford A, Reipas K et al. (2012) Citation Format: Kristen Reipas, Anna Stratford, Arezoo Astanehe, Kaiji Hu, Sandra Dunn. Targeting Y-box binding protein-1 (YB-1) overcomes drug resistance in 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 506. doi:10.1158/1538-7445.AM2013-506
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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) | 0.001 | 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) | 0.002 | 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".