Pharmacogenomic modeling of circulating tumor and invasive cells for prediction of chemotherapy response and resistance in pancreatic cancer.
Pharmacogenomic modeling of circulating tumor and invasive cells for prediction of chemotherapy response and resistance in pancreatic cancer.
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DOI：
10.1158/1078-0432.ccr-14-0531
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发表时间：
2014-10-15
期刊：
影响因子：
--
通讯作者：
O'Reilly EM
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文献类型：
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作者：
Yu KH;Ricigliano M;Hidalgo M;Abou-Alfa GK;Lowery MA;Saltz LB;Crotty JF;Gary K;Cooper B;Lapidus R;Sadowska M;O'Reilly EM
尽管预后具有挑战性，但现代细胞毒治疗可以诱导肿瘤反应并延长胰腺腺癌（PDAC）的生命。肿瘤组织的药物基因组学（PGx）模型可以预测化疗药物在临床前癌症模型中的疗效。我们假设从外周血中分离的循环肿瘤和侵袭细胞（CTICs）的PGx谱分析可以预测肿瘤的反应、进展和耐药性。建立了PGx模型并在临床前模型中进行了验证。进行前瞻性临床试验。50例晚期PDAC患者入组。治疗前，采集外周抽血10ml。从该血液样本中分离的CTICs表达谱和PGx模型用于预测有效和无效的化疗药物。治疗医生对PGx预测不知情。我们发现可以可靠地分离CTICs，从化疗前和疾病进展时不可切除的PDAC患者的10ml外周血中提取总RNA并进行分析。使用先前创建的PGx模型来预测化疗敏感性，我们发现，在无进展（10.4个月vs 3.6个月，p < 0.0001, HR = 0.14）和总生存期（17.2个月vs 8.3个月，p < 0.0249, HR = 0.29）方面，化疗方案预测有效而化疗方案预测无效的研究参与者的临床获益。这些发现表明，ctic的PGx谱分析可以预测治疗反应。
Despite a challenging prognosis, modern cytotoxic therapy can induce tumor responses and extend life in pancreatic adenocarcinoma (PDAC). Pharmacogenomic (PGx) modeling of tumor tissue can predict efficacy of chemotherapeutic agents in preclinical cancer models. We hypothesized that PGx profiling of circulating tumor and invasive cells (CTICs) isolated from peripheral blood could predict tumor response, progression and resistance. A PGx model was created and validated in preclinical models. A prospective clinical trial was conducted. 50 patients with advanced PDAC were enrolled. Prior to treatment, 10 mL of peripherally drawn blood was collected. CTICs isolated from this blood sample were expression profiled and the PGx model was used to predict effective and ineffective chemotherapeutic agents. Treating physicians were blinded to PGx prediction. We found that CTICs could be reliably isolated, total RNA extracted and profiled from 10 mL of peripheral blood from patients with unresectable PDAC prior to chemotherapy treatment and at disease progression. Using previously created PGx models to predict chemotherapy sensitivity, we found that clinical benefit was seen for study participants treated with chemotherapy regimens predicted to be effective versus chemotherapy regimens predicted to be ineffective with regards to progression-free (10.4 mo v 3.6 mo, p < 0.0001, HR = 0.14) and overall survival (17.2 mo v 8.3 mo, p < 0.0249, HR = 0.29). These findings suggest that PGx profiling of CTICs can predict treatment response.