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  • Title: [Literature-mining and bioinformatic analysis of androgen-independent prostate cancer-specific genes].
    Author: Li TQ, Feng CQ, Zou YG, Shi R, Liang S, Mao XM.
    Journal: Zhonghua Nan Ke Xue; 2009 Dec; 15(12):1102-7. PubMed ID: 20180422.
    Abstract:
    OBJECTIVE: To compare the differences of the gene expressions in androgen-independent and androgen-dependent prostate cancer (ADPC), gain a deeper insight into the molecular mechanism of androgen-independent prostate cancer (AIPC), and find effective means for its clinical diagnosis and treatment. METHODS: Eats of genes highly-associated with prostate cancer were obtained by mining PubMed with the FACTA tool, and the specifically expressed genes in AIPC were analyzed with a set of bioinformatic tools including GATHER, PANTHER, STRING and ToppGene. RESULTS: A total of 128 genes specifically expressed in AIPC were identified, as compared with 23 that were specific to ADPC. Bioinformatic analysis showed the essential roles of AIPC-specific genes in such important biological processes as cell signal transduction, cell adhesion, apoptosis, oncogenesis, cell proliferation and cell differentiation. CONCLUSION: Such genes as MMPJ, EGFR, MMP2, ADM, MIF, IGFBP3, 112, MET, BAD, RHOA, SPP1, EP300, SMAD3, RAE1, PTK2, and TGFB2 may play important roles in transforming ADPC into AIPC.
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