Prostate cancer heterogeneity: Discovering novel molecular targets for therapy
•Prostate cancer (PCa) shows a broad spectrum of biological and clinical behavior, which represents the epiphenomenon of an extreme genetic heterogeneity.•The AR and PI3K/Akt/mTOR signaling pathways are the two most frequently altered, representing therefore interestingly targets for therapy.•Germli...
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| Veröffentlicht in: | Cancer treatment reviews Jg. 54; S. 68 - 73 |
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| Hauptverfasser: | , , , , , , , , |
| Format: | Journal Article |
| Sprache: | Englisch |
| Veröffentlicht: |
Netherlands
Elsevier Ltd
01.03.2017
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| Schlagworte: | |
| ISSN: | 0305-7372, 1532-1967, 1532-1967 |
| Online-Zugang: | Volltext |
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| Zusammenfassung: | •Prostate cancer (PCa) shows a broad spectrum of biological and clinical behavior, which represents the epiphenomenon of an extreme genetic heterogeneity.•The AR and PI3K/Akt/mTOR signaling pathways are the two most frequently altered, representing therefore interestingly targets for therapy.•Germline mutations in DNA repair genes (BRCA2, BRCA1, MSH2, HOXB13) have been related to an increased risk of developing PCa.•The PI3K/Akt pathway is the second most commonly genomic aberration hyperactivated in advanced PCa, after AR alterations.
Prostate cancer (PCa) shows a broad spectrum of biological and clinical behavior, which represents the epiphenomenon of an extreme genetic heterogeneity. Recent genomic profiling studies have deeply improved the knowledge of the genomic landscape of localized and metastatic PCa. The AR and PI3K/Akt/mTOR signaling pathways are the two most frequently altered, representing therefore interestingly targets for therapy. Moreover, somatic or germline aberrations of DNA repair genes (DRGs) have been observed at high frequency, supporting the potential role of platinum derivatives and PARP inhibitors as effective therapeutic strategies.
In the future, the identification of driver mutations present at a specific stage of the disease, the classification PCa based on specific molecular alterations, and the selection of the most appropriate therapy based on biomarkers predictors of response represent the foundations for an increasingly more accurate personalized medicine. |
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| Bibliographie: | ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 ObjectType-Review-3 content type line 23 |
| ISSN: | 0305-7372 1532-1967 1532-1967 |
| DOI: | 10.1016/j.ctrv.2017.02.001 |