Background: Oral squamous cell carcinoma (OSCC) is a capricious cancer with poor survival rates, even for early-stage patients. There is a pressing need to develop more precise risk assessment methods to appropriately tailor clinical treatment. Genome-wide association studies have not produced a viable biomarker. However, these studies are limited by using heterogeneous cohorts, not focusing on methylation although OSCC is a heavily epigenetically-regulated cancer, and not combining molecular data with clinicopathologic data for risk prediction. In this study we focused on early-stage (I/II) OSCC and created a risk score called the REASON score, which combines clinicopathologic characteristics with a 12-gene methylation signature, to predict the risk of 5-year mortality. Methods: We combined data from an internal cohort (n = 515) and The Cancer Genome Atlas (TCGA) cohort (n = 58). We collected clinicopathologic data from both cohorts to derive the non-molecular portion of the REASON score. We then analyzed the TCGA cohort DNA methylation data to derive the molecular portion of the risk score. Results: 5-year disease specific survival was 63% for the internal cohort and 86% for the TCGA cohort. The clinicopathologic features with the highest predictive ability among the two the cohorts were age, race, sex, tobacco use, alcohol use, histologic grade, stage, perineural invasion (PNI), lymphovascular invasion (LVI), and margin status. This panel of 10 non-molecular features predicted 5-year mortality risk with a concordance (c)-index = 0.67. Our molecular panel consisted of a 12-gene methylation signature (i.e., HORMAD2, MYLK, GPR133, SOX8, TRPA1, ABCA2, HGFAC, MCPH1, WDR86, CACNA1H, RNF216, CCNJL), which had the most significant differential methylation between patients who survived vs. died by 5 years. All 12 genes have already been linked to survival in other cancers. Of the genes, only SOX8 was previously associated with OSCC; our study was the first to link the remaining 11 genes to OSCC survival. The combined molecular and non-molecular panel formed the REASON score, which predicted risk of death with a c-index = 0.915. Conclusions: The REASON score is a promising biomarker to predict risk of mortality in early-stage OSCC patients. Validation of the REASON score in a larger independent cohort is warranted.

Oral squamous cell carcinoma (OSCC) patients suffer from poor survival due to metastasis or locoregional recurrence, processes that are both facilitated by perineural invasion (PNI). OSCC has higher rates of PNI than other cancer subtypes, with PNI present in 80% of tumors. Despite the impact of PNI on oral cancer prognosis and pain, little is known about the genes that drive PNI, which in turn drive pain, invasion, and metastasis. In this study, clinical data, preclinical, and in vitro models are leveraged to elucidate the role of neurotrophins in OSCC metastasis, PNI, and pain. The expression data in OSCC patients with metastasis, PNI, or pain demonstrate dysregulation of neurotrophin genes. TrkA and nerve growth factor receptor (NGFR) are focused, two receptors that are activated by NGF, a neurotrophin expressed at high levels in OSCC. It is demonstrated that targeted knockdown of these two receptors inhibits proliferation and invasion in an in vitro and preclinical model of OSCC, and metastasis, PNI, and pain. It is further determined that TrkA knockdown alone inhibits thermal hyperalgesia, whereas NGFR knockdown alone inhibits mechanical allodynia. Collectively the results highlight the ability of OSCC to co‐opt different components of the neurotrophin pathway in metastasis, PNI, and pain.

Metastasis reduces survival in oral cancer patients and pain is their greatest complaint. We have shown previously that oral cancer metastasis and pain are controlled by the endothelin axis, which is a pathway comprised of the endothelin A and B receptors (ET_AR and ET_BR). In this study we focus on individual genes of the pathway, demonstrating that the endothelin axis genes are methylated and dysregulated in cancer tissue. Based on these findings in patients, we hypothesize that ET_AR and ET_BR play dichotomous roles in oral carcinogenesis and pain, such that ET_AR activation and silenced ET_BR expression result in increased carcinogenesis and pain. We test a treatment strategy that targets the dichotomous functions of the two receptors by inhibiting ET_AR with macitentan, an ET_AR antagonist approved for treatment of pulmonary hypertension, and re-expressing the ET_BR gene with adenovirus transduction, and determine the treatment effect on cancer invasion (i.e., metastasis), proliferation and pain in vitro and in vivo. We demonstrate that combination treatment of macitentan and ET_BR gene therapy inhibits invasion, but not proliferation, in cell culture and in a mouse model of tongue cancer. Furthermore, the treatment combination produces an antinociceptive effect through inhibition of endothelin-1 mediated neuronal activation, revealing the analgesic potential of macitentan. Our treatment approach targets a pathway shown to be dysregulated in oral cancer patients, using gene therapy and repurposing an available drug to effectively treat both oral cancer metastasis and pain in a preclinical model.

Oral squamous cell carcinoma (OSCC) biomarker studies rarely employ multi-omic biomarker strategies and pertinent clinicopathologic characteristics to predict mortality. In this study we determine for the first time a combined epigenetic, gene expression, and histology signature that differentiates between patients with different tobacco use history (heavy tobacco use with ≥10 pack years vs. no tobacco use). Using The Cancer Genome Atlas (TCGA) cohort (n = 257) and an internal cohort (n = 40), we identify 3 epigenetic markers (GPR15, GNG12, GDNF) and 13 expression markers (IGHA2, SCG5, RPL3L, NTRK1, CD96, BMP6, TFPI2, EFEMP2, RYR3, DMTN, GPD2, BAALC, and FMO3), which are dysregulated in OSCC patients who were never smokers vs. those who have a ≥ 10 pack year history. While mortality risk prediction based on smoking status and clinicopathologic covariates alone is inaccurate (c-statistic = 0.57), the combined epigenetic/expression and histologic signature has a c-statistic = 0.9409 in predicting 5-year mortality in OSCC patients.

Background: Oral squamous cell carcinoma (OSCC) has poor survival rates. There is a pressing need to develop more precise risk assessment methods to tailor clinical treatment. Epigenome-wide association studies in OSCC have not produced a viable biomarker. These studies have relied on methylation array platforms, which are limited in their ability to profile the methylome. In this study, we use MethylCap-Seq (MC-Seq), a comprehensive methylation quantification technique, and brush swab samples, to develop a noninvasive, readily translatable approach to profile the methylome in OSCC patients. Methods: Three OSCC patients underwent collection of cancer and contralateral normal tissue and brush swab biopsies, totaling 4 samples for each patient. Epigenome-wide DNA methylation quantification was performed using the SureSelectXT Methyl-Seq platform. DNA quality and methylation site resolution were compared between brush swab and tissue samples. Correlation and methylation value difference were determined for brush swabs vs. tissues for each respective patient and site (i.e., cancer or normal). Correlations were calculated between cancer and normal tissues and brush swab samples for each patient to determine the robustness of DNA methylation marks using brush swabs in clinical biomarker studies. Results: There were no significant differences in DNA yield between tissue and brush swab samples. Mapping efficiency exceeded 90% across all samples, with no differences between tissue and brush swabs. The average number of CpG sites with at least 10x depth of coverage was 2,716,674 for brush swabs and 2,903,261 for tissues. Matched tissue and brush swabs had excellent correlation (r = 0.913 for cancer samples and r = 0.951 for normal samples). The methylation profile of the top 1000 CpGs was significantly different between cancer and normal samples (mean p-value = 0.00021) but not different between tissues and brush swabs (mean p-value = 0.11). Conclusions: Our results demonstrate that MC-Seq is an efficient platform for epigenome profiling in cancer biomarker studies, with broader methylome coverage than array-based platforms. Brush swab biopsy provides adequate DNA yield for MC-Seq, and taken together, our findings set the stage for development of a non-invasive methylome quantification technique for oral cancer with high translational potential.