Center for Cancer Research and Department of Surgery, Massachusetts General Hospital, Boston, MA 02114, USA.
Cancer. 2013 Aug 15;119(16):3034-42. doi: 10.1002/cncr.28150. Epub 2013 May 20.
Although the presence of genetic heterogeneity within the tumors of individual patients is established, it is unclear whether greater heterogeneity predicts a worse outcome. A quantitative measure of genetic heterogeneity based on next-generation sequencing (NGS) data, mutant-allele tumor heterogeneity (MATH), was previously developed and applied to a data set on head and neck squamous cell carcinoma (HNSCC). Whether this measure correlates with clinical outcome was not previously assessed.
The authors examined the association between MATH and clinical, pathologic, and overall survival data for 74 patients with HNSCC for whom exome sequencing was completed.
High MATH (a MATH value above the median) was found to be significantly associated with shorter overall survival (hazards ratio, 2.5; 95% confidence interval, 1.3-4.8). MATH was similarly found to be associated with adverse outcomes in clinically high-risk patients with an advanced stage of disease, and in those with tumors classified as high risk on the basis of validated biomarkers including those that were negative for human papillomavirus or having disruptive tumor protein p53 mutations. In patients who received chemotherapy, the hazards ratio for high MATH was 4.1 (95% confidence interval, 1.6-10.2).
This novel measure of tumor genetic heterogeneity is significantly associated with tumor progression and adverse treatment outcomes, thereby supporting the hypothesis that higher genetic heterogeneity portends a worse clinical outcome in patients with HNSCC. The prognostic value of some known biomarkers may be the result of their association with high genetic heterogeneity. MATH provides a useful measure of that heterogeneity to be prospectively validated as NGS data from homogeneously treated patient cohorts become available.
尽管已经确定了个体患者肿瘤内存在遗传异质性，但尚不清楚更大的异质性是否预示着更差的预后。先前开发了一种基于下一代测序 (NGS) 数据的遗传异质性定量测量方法，即突变等位基因肿瘤异质性 (MATH)，并将其应用于头颈部鳞状细胞癌 (HNSCC) 的数据集。以前尚未评估该测量方法与临床结果是否相关。
作者研究了 74 名接受过头颈鳞癌外显子组测序的患者的 MATH 与临床、病理和总生存数据之间的关联。
发现高 MATH（中位数以上的 MATH 值）与总生存期较短显著相关（风险比，2.5；95%置信区间，1.3-4.8）。在疾病晚期的临床高危患者和基于验证生物标志物（包括 HPV 阴性或肿瘤蛋白 p53 突变具有破坏性的患者）被归类为高危的患者中，MATH 也与不良结局相关。在接受化疗的患者中，高 MATH 的风险比为 4.1（95%置信区间，1.6-10.2）。
这种肿瘤遗传异质性的新测量方法与肿瘤进展和不良治疗结局显著相关，从而支持了更高遗传异质性预示着 HNSCC 患者临床结局更差的假设。一些已知生物标志物的预后价值可能是其与高遗传异质性相关的结果。随着来自同质治疗患者队列的 NGS 数据的可用性，MATH 提供了一种有用的异质性测量方法，可以进行前瞻性验证。
