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The dual pathway inhibitor rigosertib inhibits phosphoinositide 3-kinase (PI3K) pathway activation as well as polo-like kinase 1 (PLK1) activity across a broad spectrum of cancer cell lines. The importance of PIK3CA alterations in squamous cell carcinoma of the head and neck (HNSCC) has raised interest in exploring agents targeting PI3K, the product of PIK3CA. The genetic and molecular basis of rigosertib treatment response was investigated in a panel of 16 HNSCC cell lines, and direct patient tumor xenografts from eight patients with HNSCC [four HPV-serotype16 (HPV16)–positive]. HNSCC cell lines and xenografts were characterized by pathway enrichment gene expression analysis, exon sequencing, gene copy number, Western blotting, and immunohistochemistry (IHC). Rigosertib had potent antiproliferative effects on 11 of 16 HPV− HNSCC cell lines. Treatment sensitivity was confirmed in two cell lines using an orthotopic in vivo xenograft model. Growth reduction after rigosertib treatment was observed in three of eight HNSCC direct patient tumor lines. The responsive tumor lines carried a combination of a PI3KCA-activating event (amplification or mutation) and a p53-inactivating event (either HPV16- or mutation-mediated TP53 inactivation). In this study, we evaluated the in vitro and in vivo efficacy of rigosertib in both HPV+ and HPV− HNSCCs, focusing on inhibition of the PI3K pathway. Although consistent inhibition of the PI3K pathway was not evident in HNSCC, we identified a combination of PI3K/TP53 events necessary, but not sufficient, for rigosertib sensitivity. Mol Cancer Ther; 12(10); 1994–2005. ©2013 AACR.

Supplemental Methods. Description of additional methods and procedures used in the study.

Supplemental Tables S1-S2. Hirsch Score was calculated from tumors and their respective stroma from Figure 5 (S1); All potential flank implanted stromal:tumor and tumor:tumor combinations were measured bi-weekly to chart growth kinetics (S2).

Supplemental Figures S1-S6. Comparison of HN11 and TU167 by RNA-Seq Expression (S1); Suppression of Radiation-induced GLI1 using shRNA Model (S2); Cyst Formation Following Radiation Treatment in Orthotopic TU167-implanted Tumors (S3); Radiation-induced Gli1 Expression and the Effect of Rapamycin Inhibition in HN11 Cells (S4); Effect of siRNA inhibition on Head Neck Cancer Cells and Gli1 Nuclear Translocation (S5); Schema and Histology Detailing Radiation-induced Tumor Repopulation (S6).

Supplemental Table and Figure Legends. Legends for Supplemental Figures S1-S6 and Supplemental Tables S1-S2.

Massively parallel sequencing (MPS) of human mitochondrial control region or whole genome is now faster, easier and more informative than was possible with Sanger sequencing and capillary electrophoresis. This study focuses on the aspects of mtDNA data that are important to consider when implementing MPS-based mtDNA typing into casework operations. This includes evaluation of data from the ForenSeq mtDNA typing system that indicate how interpretation concepts integral to Sanger sequencing of mtDNA apply directly to MPS-based mtDNA typing. In addition, there are new interpretation considerations that may be helpful when determining standard operating procedures and casework interpretation guidelines. Sequencing data are presented that may assist with SOP determination relative to sensitivity assessments that may help inform interpretation criteria, including thresholds, relative to input DNA template concentration ranges, number of pooled samples for MiSeq FGx sequencing runs and downstream bioinformatic demultiplexing. Given the quantitative nature of digital MPS data, these limit of detection studies may also assist when laboratories wish to set criteria for heteroplasmy detection (within an individual) or for mixed DNA sample interpretation. Assessment of variables will be provided across sample types such as hairs and PCR/sequencing inhibition when typing skeletal and dental remains to assist with fundamental understanding of ForenSeq mtDNA typing system limitations as well as metrics that may assist when making data quality determinations.