Biology and Genetics of Prostate Cancer

The cellular mechanisms involved in regulation of prostate cancer growth are poorly understood. Progress in elucidating the cellular pathways involved in nuclear morphology, androgen action and growth factor regulation in prostate cancer cells is being made. The Prostate Cancer Program seeks better understanding of these mechanisms to provide biological endpoints for detection, prognosis and treatment of prostate cancer.

Robert Jenkins, M.D., Ph.D., in collaboration with Angelo D. DeMarzo, M.D., Ph.D., at The Sidney Kimmel Comprehensive Cancer Center at Johns Hopkins, has demonstrated decreased NKX3.1 protein expression in focal prostatic atrophy, prostatic intraepithelial neoplasia, and adenocarcinoma: association with Gleason score and chromosome 8p deletion.

Donald Tindall, Ph.D.; Karla Ballman, Ph.D.; George Vasmatzis, Ph.D.; and Dr. Jenkins characterized the genetic and epigenetic mechanisms for progression of prostate cancer to androgen independence. Their findings suggest that a dynamic and adaptable combination of epigenetic and DNA-change-dependent events can be used by Prostate cancer cells for the acquisition of the androgen-independent phenotype.

Scott Dehm, Ph.D., and Dr. Tindall found that ligand-independent androgen receptor (AR) activity is activation function-2-independent and resistant to antiandrogens in androgen refractory prostate cancer cells. Their data demonstrated that the AR can inappropriately activate transcription in androgen-refractory Prostate cancer cells via mechanisms that are resistant to castration and AR antagonism, the two modes of androgen ablation used to treat advanced Prostate cancer.

Hannelore Heemers, Ph.D.; Thomas Sebo, M.D.; and Dr. Tindall showed that androgen deprivation increases p300 expression in prostate cancer cells. Their findings suggest that increased p300 expression upon androgen starvation is crucial for prostate cancer cell proliferation, as loss of p300 expression severely reduces expression of cyclins governing G(1)-S and G(2)-M cell cycle transition and decreases 5-bromo-2'-deoxyuridine incorporation.

John Cheville, M.D., Wanguo Liu, Ph.D.; and Dr. Tindall identified unique substitution of CHEK2 and TP53 mutations that are implicated in primary prostate tumors and cancer cell lines. Their data suggest that the CHEK2 and TP53 mutations can substitute each other in at least 25% of prostate cancers and that DNA damage-signaling pathway plays an important role in prostate cancer tumorigenesis.

Drs. Ballman, Cheville, and Tindall, along with Michael Lieber, M.D.; and Charles Young, Ph.D.; discovered that PDLIM4 repression by hypermethylation is a potential biomarker for prostate cancer. Their analysis revealed differential expression of 8 down-regulated and 3 up-regulated genes, implicating their role in prostate cancer development and progression. They further showed that the hypermethylation of PDLIM4 gene could be used as a sensitive molecular tool in detection of prostate tumorigenesis.

Krishna Donkena, Ph.D., and Dr. Young found that Sodium selenite inhibits interleukin-6-mediated androgen receptor activation in prostate cancer cells via upregulation of c-Jun. Their results suggest that sodium selenite, as opposed to methylseleninic acid, can inhibit IL-6-mediated AR activation by increased c-Jun in LNCaP cells. Sodium selenite may be a proper selenium form for further testing its potency on intervening IL-6-mediated Prostate cancer progression.

Heyu Zhang, M.D., and Dr. Young identified ZNF185 as an actin-cytoskeleton-associated growth inhibitory LIM protein in prostate cancer. Their data suggest that ZNF185 may function as a tumor-suppressor protein by associating with the actin-cytoskeleton.

Dr. Ballman developed a technique for the calibration and expression for high-density oligonucleotide arrays. A unified algorithm was found that incorporates normalization and class comparison in one analysis using probe level perfect match and mismatch data. This algorithm should facilitate the analysis of gene expression data.