The gene ratios c-MYC:cyclin-dependent kinase (CDK)N2A and CCND1:CDKN2A correlate with poor prognosis in squamous cell carcinoma of the head and neck.

Purpose: Tumor-Node-Metastasis classification does not fully predict outcome of treatment and prognosis in patients with squamous cell carcinoma of the head and neck. Different biomarkers have been suggested to yield additional prognostic information, but no single marker has thus far been introduced in the clinic. The objective of the present study was to analyze the copy number of the frequently amplified oncogenes CCND1 and c-MYC in relation to the commonly deleted tumor suppressor gene cyclin-dependent kinase (CDK)N2A (p16) to enhance the clinical significance.

Experimental Design: Extracted DNA from diagnostic biopsies of 78 untreated patients were analyzed by real-time PCR with specific primers for c-MYC, CCND1, and CDKN2A. Gene copy number ratios were calculated by dividing the copy number of c-MYC or CCND1 with CDKN2A. Ratios > 2 were defined as enhanced. These data were related to disease-free interval and disease-specific survival.

Results: Enhanced gene ratio of c-MYC:CDKN2A was detected in 35 of 78 (45%) and enhanced ratio of CCND1:CDKN2A in 36 of 78 (46%) of the cases. The c-MYC:CDKN2A and CCND1:CDKN2A ratios correlated with disease-specific survival with respect to death (P = 0.042 and 0.049, respectively; Log-rank test). Furthermore, enhancement of c-MYC:CDKN2A was associated with a shorter disease-free interval as marked by the development of recurrences or metastases (P = 0.014; Log-rank test).

Conclusions: We conclude that CCND1 and/or c-MYC amplification, when combined with CDKN2A deletion, yield additional prognostic information as compared with analysis of single genetic aberrations. These gene ratios, as analyzed by a sensitive method like real-time PCR on diagnostic biopsies, might help clinicians to individualize the treatment of squamous cell carcinoma of the head and neck as they reflect the biological properties of the tumors. This could be used as an adjunct to the Tumor-Node-Metastasis classification system.