This technology identifies a list of genes that are potential diagnostic markers and therapeutic targets for aggressive prostate cancers.
Unmet need: Strategies for early intervention against prostate cancer
Prostate cancer is the second most common cancer in American men. While some types of prostate cancer grow slowly and may need minimal treatment, other types are aggressive and can be fatal. It remains challenging to determine which patients will develop the aggressive forms of prostate cancer. Once these patients are identified, treatments are also needed to prevent and manage advanced cases of prostate cancer.
The Technology: Molecular biomarkers and therapeutic targets for aggressive prostate tumors
This technology identifies two genes, FOXM1 and CENPF, as robust indicators of advanced prostate cancer. In vivo studies have shown that the protein products of these two genes synergistically promote tumor growth by coordinated regulation of target gene expression and activation of key signaling pathways associated with prostate cancer malignancy. Thus, in addition to diagnostic markers, these genes could also serve as potential therapeutic targets to treat these cancers.
This technology has been published in a research article in Cell
Applications:
- Diagnostic markers for advanced prostate cancer
- Therapeutic targets for aggressive prostate cancer
- Use in combination with other determinants, such as risk factors and Gleason score to increase diagnosis accuracy
Advantages:
- Robust biomarkers for advanced prostate cancer
- The functions of these genes in prostate cancer are verified in vivo
- Allows for feasible immunostaining assay
Lead Inventors:
Patent Information:
Related Publications:
Paull EO, Aytes A, Jones SJ, Subramaniam PS, Giorgi FM, Douglass EF, Tagore S, Chu B, Vasciaveo A, Zheng S, Verhaak R, Abate-Shen C, Alvarez MJ, Califano A. “A modular master regulator landscape controls cancer transcriptional identity” Cell. 2021 Jan 21; 184(2): 334-351.
Mitrofanova A, Aytes A, Zou M, Shen MM, Abate-Shen C, Califano A. “Predicting Drug Response in Human Prostate Cancer from Preclinical Analysis of In Vivo Mouse Models” Cell Rep. 2015 Sep 29; 12(12): 2060-71.
Aytes A, Mitrofanova A, Lefebvre C, Alvarez MJ, Castillo-Martin M, Zheng T, Eastham JA, Gopalan A, Pienta KJ, Shen MM, Califano A, Abate-Shen C. “Cross-species regulatory network analysis identifies a synergistic interaction between FOXM1 and CENPF that drives prostate cancer malignancy” Cancer Cell. 2014 May 12;25(5): 638-51.
Irshad S, Bansal M, Castillo-Martin M, Aytes A, Zheng T, Wenske S, Guarnieri P, Sumazin P, Le Magnen C, Benson MC, Shen MM, Califano A, Abate-Shen C. “A molecular signature predictive of indolent prostate cancer” Sci Transl Med. 2013 Sep 11; 5(202): 202ra122.
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