Prostate cancer invasion and metastasis: Insights from mining genomic data

Hudson, Bryan D.; Kulp, Kristen S.; Loots, Gabriela G.

doi:10.1093/bfgp/elt021

Title: Prostate cancer invasion and metastasis: Insights from mining genomic data

Journal Article · Mon Jul 22 00:00:00 EDT 2013 · Briefings in Functional Genomics

DOI:https://doi.org/10.1093/bfgp/elt021· OSTI ID:1343829

Hudson, Bryan D. ^[1]; Kulp, Kristen S. ^[1]; Loots, Gabriela G. ^[1]

Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States)

Prostate cancer (PCa) is the second most commonly diagnosed malignancy in men in the Western world and the second leading cause of cancer-related deaths among men worldwide. Although most cancers have the potential to metastasize under appropriate conditions, PCa favors the skeleton as a primary site of metastasis, suggesting that the bone microenvironment is conducive to its growth. PCa metastasis proceeds through a complex series of molecular events that include angiogenesis at the site of the original tumor, local migration within the primary site, intravasation into the blood stream, survival within the circulation, extravasation of the tumor cells to the target organ and colonization of those cells within the new site. In turn, each one of these steps involves a complicated chain of events that utilize multiple protein–protein interactions, protein signaling cascades and transcriptional changes. Despite the urgent need to improve current biomarkers for diagnosis, prognosis and drug resistance, advances have been slow. Global gene expression methods such as gene microarrays and RNA sequencing enable the study of thousands of genes simultaneously and allow scientists to examine molecular pathways of cancer pathogenesis. In this review, we summarize the current literature that explored high-throughput transcriptome analysis toward the advancement of biomarker discovery for PCa. Novel biomarkers are strongly needed to enable more accurate detection of PCa, improve prediction of tumor aggressiveness and facilitate the discovery of new therapeutic targets for tailored medicine. Furthermore, promising molecular markers identified from gene expression profiling studies include HPN, CLU1, WT1, WNT5A, AURKA and SPARC.

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Research Organization:: Lawrence Livermore National Laboratory (LLNL), Livermore, CA (United States)

Sponsoring Organization:: USDOE

Grant/Contract Number:: AC52-07NA27344

OSTI ID:: 1343829

Report Number(s):: LLNL-JRNL-615633

Journal Information:: Briefings in Functional Genomics, Vol. 12, Issue 5; ISSN 2041-2649

Publisher:: Oxford University PressCopyright Statement

Country of Publication:: United States

Language:: English

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Cited by: 27 works

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