The link between HPV infection and neoplasia

The link between HPV infection and neoplasia has been well established. HPV encodes two oncogenes (E6 and E7) that drive Caffeine synthesis progression by controlling the functions of tumor suppressor proteins p53 and Rb [7]. HPV is associated with more than 99% of cervical CESC cases [8]. CESC remains a major problem, with more than 500,000 new cases diagnosed worldwide annually [1]. In addition to cervical and oropharyngeal cancers, high-risk HPV subtypes have also been associated with anal and vulvar cancers [9]. To address the unmet need of biomarker-driven, effective, targeted therapy for HPV-associated HNSCC and CESCs, we conducted a high-throughput drug screen (HTDS) with use of a library of 1122 compounds in all readily available HPV-positive HNSCC and CESC cell lines as well as in matched HPV-negative lines. We identified Aurora kinase inhibitors as a class of compounds that has not been well-studied in CESC and HNSCC but one that has a potent, global effect on cancer cell survival. Focusing on the pan-Aurora kinase inhibitor danusertib because of its advanced clinical development, we investigated its effects in vitro and in vivo. In addition, we identified robust correlations between sensitivity to Aurora kinase inhibitors and mutations in the Histone-lysine N-methyltransferase 2D (KMT2D, MLL2) gene. To validate our findings in an independent dataset, we queried the Genomics of Drug Sensitivity in Cancer (GDSC) database, which included results from 983 tested cancer cell lines. The findings of our study suggest potential biomarkers of response to a clinically relevant class of drugs.
Materials and methods
Results
Discussion In this study, we tested 865 unique drugs in all readily available HPV-driven cancer cell lines that grew consistently in culture and included a panel of HPV-negative cell lines. Quality control measures demonstrated that our data were reproducible between two biological replicates and that there was little plate-to-plate variability. Drugs with similar targets tended to be effective or ineffective in the same cell lines and thus clustered together. CDK4/6 inhibitors were more effective in HPV-negative models, but no other drug class showed a consistent differential effect based on HPV status. We focused on the relatively understudied Aurora kinase inhibitors. Treatment with relevant concentrations of danusertib induced G2/M arrest and apoptosis in all cell lines tested. Mutations in KMT2D correlated with response to Aurora kinase inhibitors in our 24 cell lines and in an independent dataset of 983 cancer cell lines. Further validation of this result was that knockdown of KMT2D led to increased Aurora kinase inhibition–induced apoptosis. To the best of our knowledge, our study is the only one to compare drug sensitivity in HPV-positive and -negative cell lines or to examine HPV-positive cancer on this scale. Although other cancer cell line drug screens have been published, few HNSCC and CESC and even fewer HPV-positive cell lines have been tested. The GDSC database included 131 drugs in 22 HPV-negative HNSCC, 4 HPV-negative CESC, and 6 HPV-positive CESC cell lines [27]. The cancer cell line encyclopedia (CCLE) included 24 compounds in 31 HPV-negative HNSCC cell lines and no CESC cell lines [28]. Analysis of drug efficacy in HNSCC cell lines from the CCLE and GDSC database identified 4 drugs that were more effective in HNSCC cell lines than in other cancer types (bosutinib, docetaxel, BIBW2992, and gefitinib), all of which were highly effective drugs in our screen [29]. The Cancer Therapeutic Response Portal tested 481 compounds in 860 genetically characterized cell lines that included 30 HPV-negative HNSCC cell lines and one HPV-positive CESC cell line [30]. The NCI60 did not include HNSCC or CESC. We were surprised to discover that few drugs had a differential effect based on HPV status because patients with HPV-positive HNSCC have a much better outcome than do those with HPV-negative disease [5]. The finding that CDK4/6 inhibitors were less effective in the HPV-positive cell lines and our recent characterization of these cell lines [10] suggests that Chi structure are appropriate models for drug discovery. We speculate that despite the molecular differences between HPV-negative and -positive tumors, these tumors share attributes, including loss of p53 and Rb function that may result in similar drug sensitivity spectrum. Differential outcomes in HPV-positive patients may be due to a distinct microenvironment [31] or to differential effects of radiotherapy [32], which most patients receive.