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微阵列分析确定了一种癌症死亡特征,可预测多种癌症患者的治疗失败。

Microarray analysis identifies a death-from-cancer signature predicting therapy failure in patients with multiple types of cancer.

作者信息

Glinsky Gennadi V, Berezovska Olga, Glinskii Anna B

机构信息

Sidney Kimmel Cancer Center, San Diego, California 92121, USA.

出版信息

J Clin Invest. 2005 Jun;115(6):1503-21. doi: 10.1172/JCI23412.

Abstract

Activation in transformed cells of normal stem cells' self-renewal pathways might contribute to the survival life cycle of cancer stem cells and promote tumor progression. The BMI-1 oncogene-driven gene expression pathway is essential for the self-renewal of hematopoietic and neural stem cells. We applied a mouse/human comparative translational genomics approach to identify an 11-gene signature that consistently displays a stem cell-resembling expression profile in distant metastatic lesions as revealed by the analysis of metastases and primary tumors from a transgenic mouse model of prostate cancer and cancer patients. To further validate these results, we examined the prognostic power of the 11-gene signature in several independent therapy-outcome sets of clinical samples obtained from 1,153 cancer patients diagnosed with 11 different types of cancer, including 5 epithelial malignancies (prostate, breast, lung, ovarian, and bladder cancers) and 5 nonepithelial malignancies (lymphoma, mesothelioma, medulloblastoma, glioma, and acute myeloid leukemia). Kaplan-Meier analysis demonstrated that a stem cell-like expression profile of the 11-gene signature in primary tumors is a consistent powerful predictor of a short interval to disease recurrence, distant metastasis, and death after therapy in cancer patients diagnosed with 11 distinct types of cancer. These data suggest the presence of a conserved BMI-1-driven pathway, which is similarly engaged in both normal stem cells and a highly malignant subset of human cancers diagnosed in a wide range of organs and uniformly exhibiting a marked propensity toward metastatic dissemination as well as a high probability of unfavorable therapy outcome.

摘要

正常干细胞自我更新途径在转化细胞中的激活可能有助于癌症干细胞的生存生命周期并促进肿瘤进展。BMI-1致癌基因驱动的基因表达途径对于造血干细胞和神经干细胞的自我更新至关重要。我们应用了一种小鼠/人类比较翻译基因组学方法,以鉴定一个11基因特征,通过对前列腺癌转基因小鼠模型和癌症患者的转移灶及原发肿瘤的分析发现,该特征在远处转移灶中始终显示出类似干细胞的表达谱。为了进一步验证这些结果,我们在从1153名被诊断患有11种不同类型癌症的癌症患者中获得的几个独立的临床样本治疗结果集中,检验了该11基因特征的预后能力,其中包括5种上皮性恶性肿瘤(前列腺癌、乳腺癌、肺癌、卵巢癌和膀胱癌)和5种非上皮性恶性肿瘤(淋巴瘤、间皮瘤、髓母细胞瘤、神经胶质瘤和急性髓细胞白血病)。Kaplan-Meier分析表明,在原发性肿瘤中,11基因特征的类似干细胞的表达谱是诊断为11种不同类型癌症的癌症患者疾病复发、远处转移和治疗后死亡间隔时间短的一致有力预测指标。这些数据表明存在一种保守的BMI-1驱动途径,该途径同样参与正常干细胞以及在广泛器官中诊断出的人类癌症的高度恶性亚群,这些癌症均一致表现出明显的转移扩散倾向以及不良治疗结果的高可能性。

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