Contemporary analyses focused on a limited number of clinical and molecular biomarkers have been unable to accurately predict clinical outcomes in pancreatic ductal adenocarcinoma. Here we describe a precision medicine platform known as the Molecular Twin consisting of advanced machine-learning models and use it to analyze a dataset of 6,363 clinical and multi-omic molecular features from patients with resected pancreatic ductal adenocarcinoma to accurately predict disease survival (DS). We show that a full multi-omic model predicts DS with the highest accuracy and that plasma protein is the top single-omic predictor of DS. A parsimonious model learning only 589 multi-omic features demonstrated similar predictive performance as the full multi-omic model. Our platform enables discovery of parsimonious biomarker panels and performance assessment of outcome prediction models learning from resource-intensive panels. This approach has considerable potential to impact clinical care and democratize precision cancer medicine worldwide.

Head and neck squamous cell carcinoma (HNSCC) is an aggressive disease marked by frequent recurrence and metastasis and stagnant survival rates. To enhance molecular knowledge of HNSCC and define a non-coding RNA (ncRNA) landscape of the disease, we profiled the transcriptome-wide dysregulation of long non-coding RNA (lncRNA), microRNA (miRNA), and PIWI-interacting RNA (piRNA) using RNA-sequencing data from 422 HNSCC patients in The Cancer Genome Atlas (TCGA). 307 non-coding transcripts differentially expressed in HNSCC were significantly correlated with patient survival, and associated with mutations in TP53, CDKN2A, CASP8, PRDM9, and FBXW7 and copy number variations in chromosomes 3, 5, 7, and 18. We also observed widespread ncRNA correlation to concurrent TP53 and chromosome 3p loss, a compelling predictor of poor prognosis in HNSCCs. Three selected ncRNAs were additionally associated with tumor stage, HPV status, and other clinical characteristics, and modulation of their expression in vitro reveals differential regulation of genes involved in epithelial-mesenchymal transition and apoptotic response. This comprehensive characterization of the HNSCC non-coding transcriptome introduces new layers of understanding for the disease, and nominates a novel panel of transcripts with potential utility as prognostic markers or therapeutic targets.