Maximizing Small Biopsy Patient Samples: Unified RNA-Seq Platform Assessment of over 120,000 Patient Biopsies.
P Sean WalshYangyang HaoJie DingJianghan QuJonathan WildeRuochen JiangRichard T KloosJing HuangGiulia C KennedyPublished in: Journal of personalized medicine (2022)
Despite its wide-ranging benefits, whole-transcriptome or RNA exome profiling is challenging to implement in a clinical diagnostic setting. The Unified Assay is a comprehensive workflow wherein exome-enriched RNA-sequencing (RNA-Seq) assays are performed on clinical samples and analyzed by a series of advanced machine learning-based classifiers. Gene expression signatures and rare and/or novel genomic events, including fusions, mitochondrial variants, and loss of heterozygosity were assessed using RNA-Seq data generated from 120,313 clinical samples across three clinical indications (thyroid cancer, lung cancer, and interstitial lung disease). Since its implementation, the data derived from the Unified Assay have allowed significantly more patients to avoid unnecessary diagnostic surgery and have played an important role in guiding follow-up decisions regarding treatment. Collectively, data from the Unified Assay show the utility of RNA-Seq and RNA expression signatures in the clinical laboratory, and their importance to the future of precision medicine.
Keyphrases
- rna seq
- single cell
- high throughput
- gene expression
- machine learning
- interstitial lung disease
- electronic health record
- systemic sclerosis
- minimally invasive
- dna methylation
- big data
- oxidative stress
- coronary artery bypass
- poor prognosis
- deep learning
- idiopathic pulmonary fibrosis
- acute coronary syndrome
- percutaneous coronary intervention