Abstract 4741: Biomarker significance of plasma and tumor miR-21, miR-221, and miR-106a in pediatric osteosarcoma
Bibliographic record
Abstract
Abstract Osteosarcoma is the most common malignant bone tumor in children and young adults. Despite the use of surgery and multi-agent chemotherapy, osteosarcoma patients who respond poorly towards chemotherapy or develop relapses have a dismal outcome. Identification of biomarkers for active disease may help to monitor tumor burden, detect early relapses, and predict prognosis in these patients, so that they can be treated as early as possible to improve their survival. In this study, we examined if circulating microRNAs (miRNAs) can be used as biomarkers in osteosarcoma patients. We performed genome-wide miRNA profiling on a discovery cohort of OS plasma samples (n=32) collected from the Texas Children’s Hospital. A total of 56 miRNAs were upregulated and 164 miRNAs were downregulated in osteosarcoma samples when compared to normal plasma samples (n=8). miRNA-21, miR-221 and miRNA-106a were selected for further validation based on their known biological importance. We showed that all three circulating miRNAs were expressed significantly higher in OS samples (n=29) than normal samples (n=17) in an independent cohort obtained from the Children’s Oncology Group. Furthermore, we demonstrated that miR-21 was expressed significantly higher in osteosarcoma tumors (n=89) compared with normal bone controls. More importantly, lower expressions of miR-21 and miR-221, but not miR-106a, significantly correlated with a poor outcome. In conclusion, our results indicate that miR-21, miR-221 and miR-106a are elevated in the circulation of osteosarcoma patients, whereas tumor expressions of miR-21 and miR-221 are prognostically significant. Further investigation of the miRNAs may lead to a better prognostic method and potential miRNA therapeutics for osteosarcoma. Citation Format: Manjula Nakka, Wendy Allen-Rhoades, Yiting Li, Aaron Kelly, Jianhe Shen, Aaron Taylor, Donald A. Barkauskas, Jason Yustein, Irene Andrulis, Jay Wunder, Richard Gorlick, Paul Meltzer, Ching Lau, Tsz-Kwong Man. Biomarker significance of plasma and tumor miR-21, miR-221, and miR-106a in pediatric osteosarcoma [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2017; 2017 Apr 1-5; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2017;77(13 Suppl):Abstract nr 4741. doi:10.1158/1538-7445.AM2017-4741
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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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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".