Delineation of prognostic biomarkers in prostate cancer

前列腺癌 PCA3系列 组织微阵列 前列腺 癌症 TMPRS2型 癌症研究 医学 微阵列 癌变 基因表达谱 肿瘤科 病理 生物 内科学 基因表达 基因 疾病 2019年冠状病毒病(COVID-19) 传染病(医学专业) 生物化学
作者
Saravana M. Dhanasekaran,Terrence R. Barrette,Debashis Ghosh,Rajal B. Shah,Sooryanarayana Varambally,Kotoku Kurachi,Kenneth J. Pienta,Mark A. Rubin,Arul M. Chinnaiyan
出处
期刊:Nature [Nature Portfolio]
卷期号:412 (6849): 822-826 被引量:1703
标识
DOI:10.1038/35090585
摘要

Prostate cancer is the most frequently diagnosed cancer in American men1,2. Screening for prostate-specific antigen (PSA) has led to earlier detection of prostate cancer3, 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 cancer4,5,6. 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.
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