Independent evaluation of a FOXM1-based quantitative malignancy diagnostic system (qMIDS) on head and neck squamous cell carcinomas

基于 FOXM1 的定量恶性肿瘤诊断系统 (qMIDS) 对头颈部鳞状细胞癌的独立评估

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作者:Hong Ma, Haiyan Dai, Xiaofeng Duan, Zhenglong Tang, Rui Liu, Kunjun Sun, Ke Zhou, Hao Chen, Hang Xiang, Jinsheng Wang, Qiong Gao, Yuan Zou, Hong Wan, Muy-Teck Teh

Abstract

The forkhead box M1 (FOXM1) transcription factor gene has been implicated in almost all human cancer types. It would be an ideal biomarker for cancer detection but, to date, its translation into a cancer diagnostic tool is yet to materialise. The quantitative Malignancy Index Diagnostic System (qMIDS) was the first FOXM1 oncogene-based diagnostic test developed for quantifying squamous cell carcinoma aggressiveness. The test was originally validated using head and neck squamous cell carcinomas (HNSCC) from European patients. The HNSCC gene expression signature across geographical and ethnic differences is unknown. This is the first study evaluated the FOXM1-based qMIDS test using HNSCC specimens donated by ethnic Chinese patients. We tested 50 Chinese HNSCC patients and 18 healthy subjects donated 68 tissues in total. qMIDS scores from the Chinese cohort were compared with the European datasets (n = 228). The median ± SD scores for the Chinese cohort were 1.13 ± 0.66, 4.02 ± 1.66 and 5.83 ± 3.13 in healthy oral tissues, adjacent tumour margin and HNSCC core tissue, respectively. Diagnostic test efficiency between the Chinese and European datasets was almost identical. Consistent with previous European data, qMIDS scores for HNSCC samples were not influenced by gender or age. The degree of HNSCC differentiation, clinical stage and lymphatic metastasis status were found to be correlated with qMIDS scores. This study provided the first evidence that the pathophysiology of HNSCC was molecularly indistinguishable between the Chinese and European specimens. The qMIDS test robustly quantifies a universal FOXM1-driven oncogenic program, at least in HNSCC, which transcends ethnicity, age, gender and geographic origins.

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