The ability to predict responsiveness to drugs in individual patients is limited. We hypothesized that integrating molecular information from databases would yield predictions that could be experimentally tested to develop transcriptomic signatures for specific drugs. We analyzed lung adenocarcinoma patient data from The Cancer Genome Atlas and identified a subset of patients in which xanthine dehydrogenase (XDH) expression correlated with decreased survival. We tested allopurinol, an FDA-approved drug that inhibits XDH, on human non-small-cell lung cancer (NSCLC) cell lines obtained from the Broad Institute Cancer Cell Line Encyclopedia and identified sensitive and resistant cell lines. We utilized the transcriptomic profiles of these cell lines to identify six-gene signatures for allopurinol-sensitive and allopurinol-resistant cell lines. Transcriptomic networks identified JAK2 as an additional target in allopurinol-resistant lines. Treatment of resistant cell lines with allopurinol and CEP-33779 (a JAK2 inhibitor) resulted in cell death. The effectiveness of allopurinol alone or allopurinol and CEP-33779 was verified in vivo using tumor formation in NCR-nude mice. We utilized the six-gene signatures to predict five additional allopurinol-sensitive NSCLC cell lines and four allopurinol-resistant cell lines susceptible to combination therapy. We searched the transcriptomic data from a library of patient-derived NSCLC tumors from the Jackson Laboratory to identify tumors that would be predicted to be sensitive to allopurinol or allopurinol + CEP-33779 treatment. Patient-derived tumors showed the predicted drug sensitivity in vivo. These data indicate that we can use integrated molecular information from cancer databases to predict drug responsiveness in individual patients and thus enable precision medicine.

中文翻译：

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通过系统治疗分析确定了对别嘌呤醇和肺癌联合治疗的反应性的基因组特征。

预测个别患者对药物反应的能力有限。我们假设整合来自数据库的分子信息将产生预测，可以通过实验测试该预测以开发特定药物的转录组签名。我们分析了《癌症基因组图集》中的肺腺癌患者数据，并确定了黄嘌呤脱氢酶（XDH）表达与存活率降低相关的部分患者。我们对从广泛研究所癌细胞系百科全书获得的人非小细胞肺癌（NSCLC）细胞系测试了FDA批准的抑制XDH的别嘌呤醇，并鉴定了敏感和耐药细胞系。我们利用这些细胞系的转录组概况，为别嘌呤醇敏感性和别嘌呤醇抗性细胞系鉴定了六个基因标记。转录组学网络将JAK2确定为别嘌呤醇抗性系的另一个靶标。用别嘌醇和CEP-33779（JAK2抑制剂）处理耐药细胞系会导致细胞死亡。使用NCR裸鼠中的肿瘤形成，在体内证实了别嘌呤醇或别嘌醇和CEP-33779的有效性。我们利用这六个基因的信号来预测易受联合疗法影响的另外五种别嘌呤醇敏感的NSCLC细胞株和四种别嘌呤醇耐药的细胞株。我们从杰克逊实验室的患者来源的NSCLC肿瘤库中检索了转录组数据，以鉴定预计对别嘌呤醇或别嘌呤醇+ CEP-33779治疗敏感的肿瘤。患者来源的肿瘤在体内显示出预期的药物敏感性。