Stromal features are predictive of disease mortality in oral cancer patients.

Worldwide, approximately 405 000 cases of oral cancer (OSCC) are diagnosed each year, with a rising incidence in many countries. Despite advances in surgery and radiotherapy, which remain the standard treatment options, the mortality rate has remained largely unchanged for decades, with a 5-year survival rate of around 50%. OSCC is a heterogeneous disease, staged currently using the TNM classification, supplemented with pathological information from the primary tumour and loco-regional lymph nodes. Although patients with advanced disease show reduced survival, there is no single pathological or molecular feature that identifies aggressive, early-stage tumours. We retrospectively analysed 282 OSCC patients for disease mortality, related to clinical, pathological, and molecular features based on our previous functional studies [EGFR, αvβ6 integrin, smooth muscle actin (SMA), p53, p16, EP4]. We found that the strongest independent risk factor of early OSCC death was a feature of stroma rather than tumour cells. After adjusting for all factors, high stromal SMA expression, indicating myofibroblast transdifferentiation, produced the highest hazard ratio (3.06, 95% CI 1.65-5.66) and likelihood ratio (3.6; detection rate: false positive rate) of any feature examined, and was strongly associated with mortality, regardless of disease stage. Functional assays showed that OSCC cells can modulate myofibroblast transdifferentiation through αvβ6-dependent TGF-β1 activation and that myofibroblasts promote OSCC invasion. Finally, we developed a prognostic model using Cox regression with backward elimination; only SMA expression, metastasis, cohesion, and age were significant. This model was independently validated on a patient subset (detection rate 70%; false positive rate 20%; ROC analysis 77%, p < 0.001). Our study highlights the limited prognostic value of TNM staging and suggests that an SMA-positive, myofibroblastic stroma is the strongest predictor of OSCC mortality. Whether used independently or as part of a prognostic model, SMA identifies a significant group of patients with aggressive tumours, regardless of disease stage.