Abstract 2864: RPS4X, a new prognostic and predictive biomarker of ovarian and breast cancer
Bibliographic record
Abstract
Abstract Epithelial ovarian cancer (EOC) is a disease responsible for more cancer deaths among women in the Western world than all other gynecologic malignancies and breast cancer is leading cause of cancer death among the women worldwide. A major problem with such cancers is chemoresistance; hence the need to identify predictive biomarkers. Interestingly, overexpression of YB-1 in ovarian and breast cancer cells induces cisplatin resistance. Platinum coumpounds like cisplatin is often used in the treatments of these cancers. Y box-binding protein 1 (YB-1) is a multifunctional protein that affects transcription, splicing and translation of mRNA. In this study, we used a tagged YB-1 construct to identify by mass spectrometry the proteins that interacted with YB-1 and required for cisplatin resistance. Using the combination of two bioinformatics databases (Oncomine public microarray and genomic hybridization), we focused on the YB-1 protein partners that are potentially involved in cancer progression. We used the siRNA technique to screen different partners of YB-1 that are directly involve in the cisplatin resistance of MCF7 and MDA-MB-231 cells lines. From this analysis, we found that the RPS4X protein, a new partner of YB-1, would be a good marker of cisplatin resistance in breast cancer patients. Interestingly, the YB-1/RPS4X complex was also found in ovarian cancer cells. Like in the breast cancer cell lines, the depletion of RPS4X protein induced the cisplatin resistance of ovarian cancer cells lines (SKOV3 and OVCAR3). Finally, we used a validate antibodies to assess by immunohistochemistry the protein levels of RPS4X and YB-1 in tumor tissue samples from 192 high-grade serous epithelial ovarian cancer patients. We found that RPS4X correlated significantly with ovarian cancer patient outcome. Taken together, these results suggest that, the YB-1/RPS4X complex is a significant potential target to counteract cisplatin resistance in breast and ovarian cancers. Also, we have established that RPS4X is a new promising prognostic marker for patients with high-grade ovarian cancer. More importantly, RPS4X is shown to be predictive of cisplatin response. Additional immunohistochemistry studies on low-grade ovarian cancers and breast cancers are required to confirm the predictive value of RPS4X. Citation Format: Serges P. Tsofack, Liliane Meunier, Anne-Marie Mes-Masson, Michel Lebel. RPS4X, a new prognostic and predictive biomarker of ovarian and breast cancer. [abstract]. In: Proceedings of the 105th Annual Meeting of the American Association for Cancer Research; 2014 Apr 5-9; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2014;74(19 Suppl):Abstract nr 2864. doi:10.1158/1538-7445.AM2014-2864
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.002 |
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".