Identification of a microRNA signature associated with risk of distant metastasis in nasopharyngeal carcinoma
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Bibliographic record
Abstract
// Jeff P. Bruce 1, 2 , Angela B. Y. Hui 3 , Wei Shi 1 , Bayardo Perez-Ordonez 4 , Ilan Weinreb 4 , Wei Xu 5 , Benjamin Haibe-Kains 1, 2 , Daryl M. Waggott 3 , Paul C. Boutros 2, 6, 7 , Brian O’Sullivan 8, 9 , John Waldron 8, 9 , Shao Hui Huang 8, 9 , Eric X. Chen 10 , Ralph Gilbert 11 , Fei-Fei Liu 1, 2, 8, 9 1 Princess Margaret Cancer Centre, University Health Network, Toronto, ON, Canada 2 Department of Medical Biophysics, University of Toronto, Toronto, ON, Canada 3 Department of Medicine, Stanford University, Stanford, CA, United States 4 Department of Pathology, Princess Margaret Cancer Centre, University Health Network, Toronto, ON, Canada 5 Division of Biostatistics, Princess Margaret Cancer Centre, University Health Network, Toronto, ON, Canada 6 Informatics and Biocomputing Program, Ontario Institute for Cancer Research, Toronto, ON, Canada 7 Department of Pharmacology and Toxicology, University of Toronto, Toronto, ON, Canada 8 Department of Radiation Oncology, Princess Margaret Cancer Centre, University Health Network, Toronto, ON, Canada 9 Department of Radiation Oncology, University of Toronto, Toronto, ON, Canada 10 Division of Medical Oncology, University of Toronto, Toronto, ON, Canada 11 Department of Otolaryngology, University of Toronto, Toronto, ON, Canada Correspondence to: Fei-Fei Liu, e-mail: Fei-Fei.Liu@rmp.uhn.on.ca Keywords: microRNA, Nasopharyngeal Carcinoma, Distant Metastasis, Prognosis Received: November 19, 2014 Accepted: December 21, 2014 Published: January 23, 2015 ABSTRACT Purpose Despite significant improvement in locoregional control in the contemporary era of nasopharyngeal carcinoma (NPC) treatment, patients still suffer from a significant risk of distant metastasis (DM). Identifying those patients at risk of DM would aid in personalized treatment in the future. MicroRNAs (miRNAs) play many important roles in human cancers; hence, we proceeded to address the primary hypothesis that there is a miRNA expression signature capable of predicting DM for NPC patients. Methods and results The expression of 734 miRNAs was measured in 125 (Training) and 121 (Validation) clinically annotated NPC diagnostic biopsy samples. A 4-miRNA expression signature associated with risk of developing DM was identified by fitting a penalized Cox Proportion Hazard regression model to the Training data set (HR 8.25; p < 0.001), and subsequently validated in an independent Validation set (HR 3.2; p = 0.01). Pathway enrichment analysis indicated that the targets of miRNAs associated with DM appear to be converging on cell-cycle pathways. Conclusions This 4-miRNA signature adds to the prognostic value of the current “gold standard” of TNM staging. In-depth interrogation of these 4-miRNAs will provide important biological insights that could facilitate the discovery and development of novel molecularly targeted therapies to improve outcome for future NPC patients.
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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 | 0.000 |
| 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 it