Delineation of prognostic biomarkers in prostate cancer
Delineation of prognostic biomarkers in prostate cancer
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DOI：
10.1038/35090585
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发表时间：
2001-08-23
期刊：
影响因子：
64.8
通讯作者：
Chinnaiyan, AM
中科院分区：
文献类型：
--
作者：
Dhanasekaran, SM;Barrette, TR;Chinnaiyan, AM
前列腺癌是美国男性中最常见的癌症（1，2）。前列腺特异性抗原（PSA）筛查可以更早发现前列腺癌（3），但血清PSA水平升高可能存在于良性前列腺增生（BPH）等非恶性疾病中。从分子水平区分前列腺肿瘤的基因表达谱的表征可以鉴定参与前列腺癌发生的基因，阐明临床生物标志物，并导致前列腺癌分类的改进（4-6）。利用互补DNA微阵列，我们研究了50多个正常和肿瘤前列腺标本和三个常见的前列腺癌细胞系的基因表达谱。测定了正常相邻前列腺（NAP）、BPH、局限性前列腺癌和转移性、难治性前列腺癌的特征表达谱。在这里，我们建立了基因和前列腺癌之间的许多关联。我们评估了其中两个基因hepsin（一种跨膜丝氨酸蛋白酶）和pim-1（一种丝氨酸/苏氨酸激酶）在蛋白质水平上使用由700多个临床分层的前列腺癌标本组成的组织微阵列。hepsin和pim-1蛋白的表达与临床结果显著相关。因此，整合cDNA微阵列、高密度组织微阵列以及相关的临床和病理学数据是人类癌症分子谱分析的有力方法。
Prostate cancer is the most frequently diagnosed cancer in American men(1,2). Screening for prostate-specific antigen (PSA) has led to earlier detection of prostate cancer(3), but elevated serum PSA levels may be present in non-malignant conditions such as benign prostatic hyperlasia (BPH). Characterization of gene-expression profiles that molecularly distinguish prostatic neoplasms may identify genes involved in prostate carcinogenesis, elucidate clinical biomarkers, and lead to an improved classification of prostate cancer(4-6). Using microarrays of complementary DNA, we examined gene-expression profiles of more than 50 normal and neoplastic prostate specimens and three common prostate-cancer cell lines. Signature expression profiles of normal adjacent prostate (NAP), BPH, localized prostate cancer, and metastatic, hormone-refractory prostate cancer were determined. Here we establish many associations between genes and prostate cancer. We assessed two of these genes-hepsin, a transmembrane serine protease, and pim-1, a serine/threonine kinase-at the protein level using tissue microarrays consisting of over 700 clinically stratified prostate-cancer specimens. Expression of hepsin and pim-1 proteins was significantly correlated with measures of clinical outcome. Thus, the integration of cDNA microarray, high-density tissue microarray, and linked clinical and pathology data is a powerful approach to molecular profiling of human cancer.