Abstract
The head and neck squamous cell carcinoma (HNSCC) population consists mainly of high-risk for recurrence and locally advanced stage patients. Increased knowledge of the HNSCC genomic profile can improve early diagnosis and treatment outcomes. The development of models to identify consistent genomic patterns that distinguish HNSCC patients that will recur and/or develop metastasis after treatment is of utmost importance to decrease mortality and improve survival rates. In this study, we used array comparative genomic hybridization data from HNSCC patients to implement a robust model to predict HNSCC recurrence/metastasis. This predictive model showed a good accuracy (>80%) and was validated in an independent population from TCGA data portal. This predictive genomic model comprises chromosomal regions from 5p, 6p, 8p, 9p, 11q, 12q, 15q and 17p, where several upstream and downstream members of signaling pathways that lead to an increase in cell proliferation and invasion are mapped. The introduction of genomic predictive models in clinical practice might contribute to a more individualized clinical management of the HNSCC patients, reducing recurrences and improving patients’ quality of life. The power of this genomic model to predict the recurrence and metastases development should be evaluated in other HNSCC populations.
Highlights
Head and neck squamous cell carcinoma (HNSCC) is the sixth most common type of cancer worldwide[1]
The identified chromosomal alteration profile of our head and neck squamous cell carcinoma (HNSCC) patients together with their follow up clinical data (6–64 months of clinical follow up) were used to build a predictive model for HNSCC recurrence/metastasis development
Identification of genome-wide high resolution DNA copy number changes through array-CGH has been applied to a wide range of tumors including HNSCC10–12
Summary
Head and neck squamous cell carcinoma (HNSCC) is the sixth most common type of cancer worldwide[1]. Tumor recurrence and metastasis lead to a poor prognosis and quality of life, being the recurrence rate in HNSCC patients of about 50% during the first 2 years after the diagnosis of the primary tumor[4]. Some clinical-pathological parameters have been pointed out to prognosis, recurrence, and survival, namely tumor primary site, nodal involvement, tumor thickness, and the status of the surgical margins[6]. Distant metastases would significantly enhance the choice of personalized treatment modalities and improve survival of patients. This stratification of patients has been difficult to obtain due to the numerous anatomic sites, the unpredictable clinical behavior and heterogeneous molecular features of these tumors[7]. Our predictive model presented an accuracy of more than 80% and it was validated in a TCGA cohort, representing a step further in the identification of clinically significant biomarkers with predictive value for HNSCC management
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