Integration of immunohistochemistry, RNA sequencing, and multiplex ligation-dependent probe amplification for molecular classification of pediatric medulloblastoma.
Hsin-Yi HuangChih-Hsiang YuYung-Li YangYa-Hsuan ChangShiann-Tarng JouKai-Hsin LinMeng-Yao LuHsiu-Hao ChangShu-Wei ChouYu-Ling NiDong-Tsamn LinHsuan-Yu ChenSteven Shinn-Forng PengMeng-Fai KuoShih-Hung YangPublished in: Pediatric blood & cancer (2022)
Our study revealed that integration of these diagnostic tools can provide a precise and timely classification of MB, optimizing an individualized, risk-directed postoperative adjuvant therapy for these patients. This workflow can be applied in a countrywide fashion to guide future clinical trials for patients with MB.
Keyphrases
- clinical trial
- machine learning
- single cell
- deep learning
- end stage renal disease
- ejection fraction
- newly diagnosed
- prognostic factors
- patients undergoing
- high throughput
- peritoneal dialysis
- randomized controlled trial
- current status
- young adults
- study protocol
- single molecule
- phase ii
- open label
- patient reported
- fluorescent probe