The role of molecular methods in the diagnosis of head and neck cancer is rapidly evolving and holds great potential for improving outcomes for all patients who suffer from this diverse group of malignancies . However, there is considerable debate as to the best clinical approaches, particularly for Next Generation Sequencing (NGS). The choices of NGS methods such as whole exome, whole genome, whole transcriptomes (RNA-Seq) or multiple gene resequencing panels, each have strengths and weakness based on data quality, the size of the data, the turnaround time for data analysis, and clinical actionability. There have also been a variety of gene expression signatures established from microarray studies that correlate with relapse and response to treatment, but none of these methods have been implemented as standard of care for oropharyngeal squamous cell carcinoma (OPSCC). Because many genomic methodologies are still far from the capabilities of most clinical laboratories, we chose to explore the use of a combination of off the shelf targeted mutation analysis and gene expression analysis methods to complement standard anatomical pathology methods. Specifically, we have used the Ion Torrent AmpliSeq cancer panel in combination with the NanoString nCounter Human Cancer Reference Kit on 8 formalin-fixed paraffin embedded (FFPE) OPSCC tumor specimens, (4) HPV-positive and (4) HPV-negative. Differential expression analysis between HPV-positive and negative groups showed that expression of several genes was highly likely to correlate with HPV status. For example, WNT1, PDGFA and OGG1 were all over-expressed in the positive group. Our results show the utility of these methods with routine FFPE clinical specimens to identify potential therapeutic targets which could be readily applied in a clinical trial setting for clinical laboratories lacking the instrumentation or bioinformatics infrastructure to support comprehensive genomics workflows. To the best of our knowledge, these preliminary experiments are among the earliest to combine both mutational and gene expression profiles using Ion Torrent and NanoString technologies. This reports serves as a proof of principle methodology in OPSCC.