Association of a gene-expression subtype to outcome and treatment response in patients with recurrent/metastatic head and neck squamous cell carcinoma treated with nivolumab.

Background: Immune checkpoint inhibitors have been approved and currently used in the clinical management of recurrent and metastatic head and neck squamous cell carcinoma (R/M HNSCC) patients. The reported benefit in clinical trials is variable and heterogeneous. Our study aims at exploring and comparing the predictive role of gene-expression signatures with classical biomarkers for immunotherapy-treated R/M HNSCC patients in a multicentric phase IIIb trial.

Dietary intervention for tertiary prevention in head and neck squamous cell carcinoma survivors: clinical and translational results of a randomized phase II trial.

Background: There is a strong need for preventive approaches to reduce the incidence of recurrence, second cancers, and late toxicities in head and neck squamous cell carcinoma (HNSCC) survivors. We conducted a randomized controlled trial (RCT) to assess a dietary intervention as a non-expensive and non-toxic method of tertiary prevention in HNSCC survivors.

Methods: Eligible participants were disease-free patients with HNSCC in follow-up after curative treatments.

Tumor molecular landscape of Epstein-Barr virus (EBV) related nasopharyngeal carcinoma in EBV-endemic and non-endemic areas: Implications for improving treatment modalities.

Epstein-Barr virus (EBV) related- nasopharyngeal carcinoma (NPC) is a squamous carcinoma of the nasopharyngeal mucosal lining. Endemic areas (EA) are east and Southeast Asia, were NPC was recorded with higher incidence and longer estimated survival than in non-endemic area (NEA) such as Europe, We analyzed the gene expression and microenvironment properties of NPC in both areas to identify molecular subtypes and assess biological and clinical correlates that might explain the differences in incidence and outcome between EA- and NEA-NPCs. Six EA-NPC transcriptomic datasets, including tumor and normal samples, were integrated in a meta-analysis to identify molecular subtypes using a ConsensusClusterPlus bioinformatic approach.