Abstract 4007: The identification of a microRNA signature associated with risk of distant metastasis in nasopharyngeal carcinoma
Bibliographic record
Abstract
Abstract Purpose: Despite significant improvement in locoregional control following radiotherapy (RT) +/- chemotherapy (CT) in the contemporary era, nasopharyngeal carcinoma (NPC) patients still suffer from a significant risk (∼20%) of distant metastasis (DM). Identifying those patients at risk of DM would aid in personalized treatment in the future. It has become increasingly apparent that microRNAs (miRNAs) play important roles in human cancer, and a number of miRNAs have been identified whose expression is associated with prognosis in a variety of cancers; hence, we proceeded to address the primary hypothesis that there is a miRNA expression signature capable of predicting DM for NPC patients. Materials and Methods: The expression of 734 unique human and viral miRNAs was measured in 125 (Training Set) and 121 (Validation Set) clinically-annotated NPC diagnostic biopsy samples using the nCounter human microRNA panel from Nanostring®. A signature associated with risk of DM was generated by fitting a penalized Cox Proportion Hazard (PH) regression model to the Training data set, and this signature was subsequently tested in the Validation cohort. Pathway enrichment analysis was then performed on validated targets of the four miRNAs comprising the final signature, to determine the potential biological impact of their dysregulation. Results: A 4-miRNA-expression signature, consisting of miR-140-5p, miR-34c-5p, miR-154-5p, and miR-449b-5p was identified in the Training set, which was significantly associated with an increased risk of developing DM (HR 8.25; p=0.0008). This signature was then validated in an independent Validation set of 121 NPC patient samples (HR 3.2; p=0.01), and observed to be the strongest independent predictor when multivariate analysis was performed including other clinically relevant variables. Specifically, this 4-miRNA signature provided additional risk categorization value beyond nodal status. Finally, pathway enrichment analysis indicated that the targets of these miRNAs appear to be converging on cell cycle pathways. Conclusion: A new 4-miRNA signature set has been validated for DM in NPC, the major cause of death in the era of intensity-modulated radiation therapy. Importantly, this signature predicted for risk of DM independent of other clinical factors, including nodal stage, which is the current most important variable associated with DM in NPC. Important biological insights will be acquired with greater in-depth interrogation of these 4-miRNAs, which should facilitate the discovery and development of novel molecularly-targeted therapies that could improve outcome for future NPC patients. Citation Format: Jeffrey Phillip Bruce. The identification of a microRNA signature associated with risk of distant metastasis in nasopharyngeal carcinoma. [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 4007. doi:10.1158/1538-7445.AM2014-4007
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.001 | 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 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".