Genomic, pathological, and clinical heterogeneity as drivers of personalized medicine in prostate cancer

Abstract Prostate cancer (CaP) is the most commonly diagnosed malignancy in men in the Western world. In North America, more than 275,000 men are diagnosed annually, whereby approximately 1 in 6 men will be diagnosed with CaP in their lifetime, and 1 in 34 men will die from castration-resistant meta...

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Veröffentlicht in:Urologic oncology 2015-02, Vol.33 (2), p.85-94
Hauptverfasser: Fraser, Michael, Ph.D, Berlin, Alejandro, M.D, Bristow, Robert G., M.D., Ph.D., F.R.C.P.C, van der Kwast, Theodorus, M.D., Ph.D., F.R.C.P.C
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Sprache:eng
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Zusammenfassung:Abstract Prostate cancer (CaP) is the most commonly diagnosed malignancy in men in the Western world. In North America, more than 275,000 men are diagnosed annually, whereby approximately 1 in 6 men will be diagnosed with CaP in their lifetime, and 1 in 34 men will die from castration-resistant metastatic disease. Unfortunately, current clinical prognostic factors explain only a proportion of the observed variation in clinical outcome from patient to patient. Furthermore, overtreatment of indolent and low-risk cancers leads to inappropriate morbidity following radiotherapy or surgery. As such, better predictors of individualized prognosis and treatment response are urgently needed to triage patients to customized and intensified CaP treatment. Recent developments in next-generation sequencing have made it possible to identify prognostic and predictive signatures based on genomic profiles. We discuss the genetic basis of CaP progression from localized to systemic disease (e.g., point mutations, copy-number alterations, and structural variants) in relation with unique features of CaP biology, including intraprostatic and interprostatic heterogeneity, multifocality and multiclonality, TMPRSS2:ERG, and other ETS-family gene fusions. Finally, we focus on the use of genomic markers as prognostic factors for local failure and for systemic disease, as novel risk-stratification tools, in triaging patients to existing treatment options, and ultimately the potential of genomics for the identification of molecular targets for therapy of CaP.
ISSN:1078-1439
1873-2496
DOI:10.1016/j.urolonc.2013.10.020