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首页> 外文期刊>American Journal of Pathology: Official Publication of the American Association of Pathologists >Transcriptomic Analysis Predicts Survival and Sensitivity to Anticancer Drugs of Patients with a Pancreatic Adenocarcinoma
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Transcriptomic Analysis Predicts Survival and Sensitivity to Anticancer Drugs of Patients with a Pancreatic Adenocarcinoma

机译:转录组分析预测胰腺癌患者的生存率和对抗癌药物的敏感性

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摘要

A major impediment to the effective treatment of patients with pancreatic ductal adenocarcinoma (PDAC) is the molecular heterogeneity of this disease, which is reflected in an equally diverse pattern of clinical outcome and in responses to therapies. We developed an efficient strategy in which PDAC samples from 17 consecutive patients were collected by endoscopic ultrasound guided fine-needle aspiration or surgery and were preserved as breathing tumors by xenografting and as a primary culture of epithelial cells. Transcriptomic analysis was performed from breathing tumors by an Affymetrix approach. We observed significant heterogeneity in the RNA expression profile of tumors. However, the bioinformatic analysis of these data was able to discriminate between patients with long- and short-term survival corresponding to patients with moderately or poorly differentiated PDAC tumors, respectively. Primary culture of cells allowed us to analyze their relative sensitivity to anticancer drugs in vitro using a chemogram, similar to the antibiogram for microorganisms, establishing an individual profile of drug sensitivity. As expected, the response was patient dependent. We also found that transcriptomic analysis predicts the sensitivity of cells to the five anticancer drugs most frequently used to treat patients with PDAC. In conclusion, using this approach, we found that transcriptomic analysis could predict the sensitivity to anticancer drugs and the clinical outcome of patients with PDAC.
机译:有效治疗胰腺导管腺癌(PDAC)的主要障碍是该疾病的分子异质性,这反映在临床结果的同等模式和对治疗的反应中。我们制定了一种有效的策略,其中通过内镜超声引导下细针穿刺抽吸或手术收集了连续17例患者的PDAC样本,并通过异种移植和上皮细胞原代培养保存为呼吸道肿瘤。通过Affymetrix方法从呼吸的肿瘤中进行转录组分析。我们在肿瘤的RNA表达谱中观察到明显的异质性。但是,这些数据的生物信息学分析能够区分分别具有中度或低分化PDAC肿瘤的长期和短期生存患者。细胞的原代培养使我们能够使用化学图谱(类似于微生物的抗菌谱图)分析其对体外抗癌药的相对敏感性,从而建立了药物敏感性的个人资料。如预期的那样,反应取决于患者。我们还发现,转录组分析可预测细胞对最常用于治疗PDAC患者的五种抗癌药物的敏感性。总之,使用这种方法,我们发现转录组学分析可以预测抗癌药物的敏感性以及PDAC患者的临床结局。

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