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E2F signature is predictive for the pancreatic adenocarcinoma clinical outcome and sensitivity to E2F inhibitors but not for the response to cytotoxic-based treatments

机译:E2F信号可预测胰腺腺癌的临床结果和对E2F抑制剂的敏感性但不能预测对基于细胞毒性的治疗的反应

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摘要

The main goal of this study was to find out strategies of clinical relevance to classify patients with a pancreatic ductal adenocarcinoma (PDAC) for individualized treatments. In the present study a set of 55 patient-derived xenografts (PDX) were obtained and their transcriptome were analyzed by using an Affymetrix approach. A supervised bioinformatics-based analysis let us to classify these PDX in two main groups named E2F-highly dependent and E2F-lowly dependent. Afterwards their characterization by using a Kaplan-Meier analysis demonstrated that E2F high patients survived significantly less than E2F low patients (9.5 months vs. 16.8 months; p = 0.0066). Then we tried to establish if E2F transcriptional target levels were associated to the response to cytotoxic treatments by comparing the IC50 values of E2F high and E2F low cells after gemcitabine, 5-fluorouracil, oxaliplatin, docetaxel or irinotecan treatment, and no association was found. Then we identified an E2F inhibitor compound, named ly101-4B, and we observed that E2F-higly dependent cells were more sensitive to its treatment (IC50 of 19.4 ± 1.8 µM vs. 44.1 ± 4.4 µM; p = 0.0061). In conclusion, in this work we describe an E2F target expression-based classification that could be predictive for patient outcome, but more important, for the sensitivity of tumors to the E2F inhibitors as a treatment. Finally, we can assume that phenotypic characterization, essentially by an RNA expression analysis of the PDAC, can help to predict their clinical outcome and their response to some treatments when are rationally selected.
机译:这项研究的主要目的是找出临床相关策略,以对胰腺导管腺癌(PDAC)的患者进行个体化治疗。在本研究中,获得了55例患者来源的异种移植物(PDX),并使用Affymetrix方法分析了它们的转录组。基于监督的生物信息学分析使我们可以将这些PDX分为两个主要类别,分别为E2F高依赖性和E2F低依赖性。之后通过使用Kaplan-Meier分析对其进行表征,结果表明,E2F高患者的存活率明显低于E2F低患者(9.5个月比16.8个月; p = 0.0066)。然后我们试图通过比较吉西他滨,5-氟尿嘧啶,奥沙利铂,多西紫杉醇或伊立替康治疗后E2F高细胞和E2F低细胞的IC50值来确定E2F转录靶水平是否与对细胞毒性治疗的反应相关,但未发现相关性。然后,我们鉴定出一种名为ly101-4B的E2F抑制剂化合物,并观察到E2F高依赖性细胞对其治疗更为敏感(IC50为19.4±±1.8μm对44.1±±4.4μm; p = 0.0061)。总之,在这项工作中,我们描述了基于E2F目标表达的分类,该分类可以预测患者的预后,但更重要的是,对于肿瘤对E2F抑制剂作为治疗的敏感性。最后,我们可以假设,通过合理地选择PDAC,通过对PDAC的RNA表达分析,表型特征可以帮助预测它们的临床结果和对某些治疗的反应。

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