Department of Gastroenterology, Hospital Clínic, Centro de Investigación Biomédica en Red de Enfermedades Hepáticas y Digestivas, IDIBAPS*, University of Barcelona, Barcelona, Catalonia, Spain.
Int J Cancer. 2013 Mar 1;132(5):1090-7. doi: 10.1002/ijc.27747. Epub 2012 Aug 12.
Although receiving adjuvant chemotherapy after radical surgery, a disappointing proportion of patients with colorectal cancer will develop tumor recurrence. Probability of relapse is currently predicted from pathological staging, there being a need for additional markers to further select high-risk patients. This study was aimed to identify a gene-expression signature to predict tumor recurrence in patients with Stages II and III colon cancer treated with 5'fluoruracil (5FU)-based adjuvant chemotherapy. Two-hundred and twenty-eight patients diagnosed with Stages II-III colon cancer and treated with surgical resection and 5FU-based adjuvant chemotherapy were included. RNA was extracted from formalin-fixed, paraffin-embedded tissue samples and expression of 27 selected candidate genes was analyzed by RT-qPCR. A tumor recurrence predicting model, including clinico-pathological variables and gene-expression profiling, was developed by Cox regression analysis and validated by bootstrapping. The regression analysis identified tumor stage and S100A2 and S100A10 gene expression as independently associated with tumor recurrence. The risk score derived from this model was able to discriminate two groups with a highly significant different probability of tumor recurrence (HR, 2.75; 95%CI, 1.71-4.39; p = 0.0001), which it was maintained when patients were stratified according to tumor stage. The algorithm was also able to distinguish two groups with different overall survival (HR, 2.68; 95%CI, 1.12-6.42; p = 0.03). Identification of a new gene-expression signature associated with a high probability of tumor recurrence in patients with Stages II and III colon cancer receiving adjuvant 5FU-based chemotherapy, and its combination in a robust, easy-to-use and reliable algorithm may contribute to tailor treatment and surveillance strategies.
尽管在根治性手术后接受辅助化疗,但相当一部分结直肠癌患者仍会出现肿瘤复发。目前,复发的概率是根据病理分期来预测的,需要额外的标志物来进一步选择高危患者。本研究旨在确定一个基因表达谱,以预测接受 5-氟尿嘧啶(5FU)为基础的辅助化疗的 II 期和 III 期结肠癌患者的肿瘤复发。
纳入了 228 名诊断为 II-III 期结肠癌并接受手术切除和 5FU 为基础的辅助化疗的患者。从福尔马林固定、石蜡包埋的组织样本中提取 RNA,并通过 RT-qPCR 分析 27 个选定候选基因的表达。通过 Cox 回归分析和 bootstrap 验证,建立了一个包括临床病理变量和基因表达谱的肿瘤复发预测模型。
回归分析确定肿瘤分期和 S100A2 和 S100A10 基因表达与肿瘤复发独立相关。该模型得出的风险评分能够区分两组肿瘤复发概率具有显著差异(HR,2.75;95%CI,1.71-4.39;p=0.0001),当根据肿瘤分期对患者进行分层时,该差异仍然存在。该算法还能够区分两组总生存率不同的患者(HR,2.68;95%CI,1.12-6.42;p=0.03)。
鉴定出一种与接受 5FU 为基础的辅助化疗的 II 期和 III 期结肠癌患者肿瘤复发高概率相关的新基因表达谱,以及将其组合成一种强大、易于使用且可靠的算法,可能有助于制定个体化的治疗和监测策略。