A surprising cross-species conservation in the genomic landscape of mouse and human oral cancer identifies a transcriptional signature predicting metastatic disease
Authors
Michael D. Onken, Ashley E. Winkler, Krishna-Latha Kanchi, Varun Chalivendra, Jonathan H. Law, Charles G. Rickert, Dorina Kallogjeri, Nancy P. Judd, Gavin P. Dunn, Jay F. Piccirillo, James S. Lewis, Jr., Elaine R. Mardis, and Ravindra Uppaluri
Institution
Washington Uni
Country
United States
Year
2014
Journal
Clinical Cancer Research
Abstract
Purpose: Improved understanding of the molecular basis underlying oral squamous cell carcinoma (OSCC) aggressive growth has significant clinical implications. Herein, cross species genomic comparison of carcinogen-induced murine and human OSCCs with indolent or metastatic growth yielded results with surprising translational relevance.
Experimental Design: Murine OSCC cell lines were subjected to next-generation sequencing (NGS) to define their mutational landscape, to define novel candidate cancer genes and to assess for parallels with known drivers in human OSCC. Expression arrays identified a mouse metastasis signature and we assessed its representation in 4 independent human datasets comprising 324 patients using weighted voting and Gene Set Enrichment Analysis (GSEA). Kaplan-Meier analysis and multivariate Cox proportional hazards modeling were used to stratify outcomes. A qRT-PCR assay based on the mouse signature coupled to a machine-learning algorithm was developed and used to stratify an independent set of 31 patients with respect to metastatic lymphadenopathy.
Results: NGS revealed conservation of human driver pathway mutations in mouse OSCC including in Trp53, MAPK, PI3K, NOTCH, JAK/STAT and FAT1-4. Moreover, comparative analysis between The Cancer Genome Atlas (TCGA) and mouse samples defined AKAP9, MED12L and MYH6 as novel putative cancer genes. Expression analysis identified a transcriptional signature predicting aggressiveness and clinical outcomes, which were validated in 4 independent human OSCC datasets. Finally, we harnessed the translational potential of this signature by creating a clinically feasible assay that stratified OSCC patients with a 93.5% accuracy.
Conclusions: These data demonstrate surprising cross-species genomic conservation that has
translational relevance for human oral squamous cell cancer.