Prediction of future metastasis and molecular characterization of head and neck squamous-cell carcinoma based on transcriptome and genome analysis by microarrays

Propensity for subsequent distant metastasis in head and neck squamous-cell carcinoma (HNSCC) was analysed using 186 primary tumours from patients initially treated by surgery that developed ( M) or did not develop (NM) metastases as the first recurrent event. Transcriptome (Affymetrix HGU133_ Plus2, QRT-PCR) and array-comparative genomic hybridization data were collected. Non-supervised hierarchical clustering based on Affymetrix data distinguished tumours differing in pathological differentiation, and identified associated functional changes. Propensity for metastasis was not associated with these subgroups. Using QRT-PCR data we identified a four-gene model (PSMD10, HSD17B12, FLOT2 and KRT17) that predicts M/NM status with 77% success in a separate 79-sample validation group of HNSCC samples. This prediction is independent of clinical criteria ( age, lymph node status, stage, differentiation and localization). The most significantlyalte red transcripts in M versus NM were significantly associated to metastasis-related functions, including adhesion, mobility and cell survival. Several genomic modi. cations were significantly associated with M/NM status ( most notably gains at 4q11-22 and Xq12-28; losses at 11q14-24 and 17q11 losses) and partly linked to transcription modi. cations. This work yields a basis for the development of prognostic molecular signatures, markers and therapeutic targets for HNSCC metastasis.