Schwaederle Maria, Daniels Gregory A, Piccioni David E, Kesari Santosh, Fanta Paul T, Schwab Richard B, Shimabukuro Kelly A, Parker Barbara A, Kurzrock Razelle
a Center for Personalized Cancer Therapy, and Division of Hematology and Oncology; UCSD Moores Cancer Center ; La Jolla , CA , USA.
Cell Cycle. 2015;14(11):1730-7. doi: 10.1080/15384101.2015.1033596.
Next generation sequencing is transforming patient care by allowing physicians to customize and match treatment to their patients' tumor alterations. Our goal was to study the association between key molecular alterations and outcome parameters. We evaluated the characteristics and outcomes (overall survival (OS), time to metastasis/recurrence, and best progression-free survival (PFS)) of 392 patients for whom next generation sequencing (182 or 236 genes) had been performed. The Kaplan-Meier method and Cox regression models were used for our analysis, and results were subjected to internal validation using a resampling method (bootstrap analysis). In a multivariable analysis (Cox regression model), the parameters that were statistically associated with a poorer overall survival were the presence of metastases at diagnosis (P = 0.014), gastrointestinal histology (P < 0.0001), PTEN (P < 0.0001), and CDKN2A alterations (P = 0.0001). The variables associated with a shorter time to metastases/recurrence were gastrointestinal histology (P = 0.004), APC (P = 0.008), PTEN (P = 0.026) and TP53 (P = 0.044) alterations. TP53 (P = 0.003) and PTEN (P = 0.034) alterations were independent predictors of a shorter best PFS. A personalized treatment approach (matching the molecular aberration with a cognate targeted drug) also correlated with a longer best PFS (P = 0.046). Our study demonstrated that, across diverse cancers, anomalies in specific tumor suppressor genes (PTEN, CDKN2A, APC, and/or TP53) were independently associated with a worse outcome, as reflected by time to metastases/recurrence, best PFS on treatment, and/or overall survival. These observations suggest that molecular diagnostic tests may provide important prognostic information in patients with cancer.
下一代测序技术正在改变患者护理方式，它使医生能够根据患者肿瘤的改变来定制并匹配治疗方案。我们的目标是研究关键分子改变与预后参数之间的关联。我们评估了392例接受下一代测序（182个或236个基因）的患者的特征和预后（总生存期（OS）、转移/复发时间以及最佳无进展生存期（PFS））。采用Kaplan-Meier方法和Cox回归模型进行分析，并使用重采样方法（自助法分析）对结果进行内部验证。在多变量分析（Cox回归模型）中，与较差总生存期具有统计学关联的参数包括诊断时存在转移（P = 0.014）、胃肠道组织学类型（P < 0.0001）、PTEN（P < 0.0001）和CDKN2A改变（P = 0.0001）。与转移/复发时间较短相关的变量包括胃肠道组织学类型（P = 0.004）、APC（P = 0.008）、PTEN（P = 0.026）和TP53（P = 0.044）改变。TP53（P = 0.003）和PTEN（P = 0.034）改变是较短最佳PFS的独立预测因素。个性化治疗方法（将分子异常与相关靶向药物相匹配）也与较长的最佳PFS相关（P = 0.046）。我们的研究表明，在多种癌症中，特定肿瘤抑制基因（PTEN、CDKN2A、APC和/或TP53）的异常与较差的预后独立相关，这通过转移/复发时间、治疗期间的最佳PFS和/或总生存期得以体现。这些观察结果表明，分子诊断测试可能为癌症患者提供重要的预后信息。
