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Myeloid differentiation factor-2/LY96, a new predictive biomarker of metastasis in prostate cancer: Clinical implications as a potential therapeutic target.
Ferrari, Marina; Wang, Li; Hoeppner, Luke; Hahm, Eunsil; Yu, Jindan; Kuzel, Timothy; Mansini, Adrian.
Afiliação
  • Hoeppner L; University of Minnesota.
  • Yu J; Emory University.
  • Mansini A; Rush University Medical Center.
Res Sq ; 2023 Jun 09.
Article em En | MEDLINE | ID: mdl-37333086
ABSTRACT
Relapsed prostate cancer (CaP), usually treated with androgen deprivation therapy, acquires resistance to develop into lethal metastatic castration-resistant CaP. The cause of resistance remains elusive, and the lack of biomarkers predictive of castration-resistance emergence is a stumbling block in managing the disease. We provide strong evidence that Myeloid differentiation factor-2 (MD2) plays a critical role in metastasis and CaP progression. Analysis of tumor genomic data and IHC of tumors showed a high frequency of MD2 amplification and association with poor overall survival in patients. The Decipher-genomic test validated the potential of MD2 in predicting metastasis. In vitro studies demonstrated that MD2 confers invasiveness by activating MAPK and NF-kB signaling pathways. Furthermore, we show that metastatic cells release MD2 (sMD2). We measured serum-sMD2 in patients and found that the level is correlated to disease extent. We determined the significance of MD2 as a therapeutic target and found that targeting MD2 significantly inhibited metastasis in a murine model. We conclude that MD2 predicts metastatic behavior and serum-MD2 is a non-invasive biomarker for tumor burden, whereas MD2 presence on prostate biopsy predicts adverse disease outcome. We suggest MD2-targeted therapies could be developed as potential treatments for aggressive metastatic disease.
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Tipo de estudo: Prognostic_studies / Risk_factors_studies Idioma: En Ano de publicação: 2023 Tipo de documento: Article

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Tipo de estudo: Prognostic_studies / Risk_factors_studies Idioma: En Ano de publicação: 2023 Tipo de documento: Article