alpha-Methylacyl-CoA racemase (AMACR) has previously been shown to be a highly sensitive marker for colorectal and clinically localized prostate cancer (PCa). However, AMACR expression was down-regulated at the transcript and protein level in hormone-refractory metastatic PCa, suggesting a hormone-dependent expression of AMACR. To further explore the hypothesis that AMACR is hormone regulated and plays a role in PCa progression AMACR protein expression was characterized in a broad range of PCa samples treated with variable amounts and lengths of exogenous anti-androgens. Analysis included standard slides and high-density tissue microarrays. AMACR protein expression was significantly increased in localized hormone-naive PCa as compared to benign (P < 0.001). Mean AMACR expression was lower in tissue samples from patients who had received neoadjuvant hormone treatment but still higher compared to hormone-refractory metastases. The hormone-sensitive tumor cell line, LNCaP, demonstrated stronger AMACR expression by Western blot analysis than the poorly differentiated cell lines DU-145 and PC-3. AMACR protein expression in cells after exposure to anti-androgen treatment was unchanged, whereas prostate-specific antigen, known to be androgen-regulated, demonstrated decreased protein expression. Surprisingly, this data suggests that AMACR expression is not regulated by androgens. Examination of colorectal cancer, which is not hormone regulated, demonstrated high levels of AMACR expression in well to moderately differentiated tumors and weak expression in anaplastic colorectal cancers. Taken together, these data suggest that AMACR expression is not hormone-dependent but may in fact be a marker of tumor differentiation.

Although, we found a high rate of osteolysis after rotator cuff repair with bioabsorbable anchors, these results did not change the clinical outcomes after rotator cuff repair. Recurrent tears were not significantly different in both groups and are comparable to rerupture rates in prior studies. More studies are needed to verify the effect of osteolysis over the long term.

Comparative genomic hybridization (CGH) is a modern genetic method which enables a genome‐wide survey of chromosomal imbalances. For each chromosome region, one obtains the information whether there is a loss or gain of genetic material, or whether there is no change at that region. Usually it is not possible to evaluate all 46 chromosomes of a metaphase, therefore several (up to 20 or more) metaphases are analyzed per individual, and expressed as average. Mostly one does not study one individual alone but groups of 20–30 individuals. Therefore, large amounts of data quickly accumulate which must be put into a logical order. In this paper we present the application of a self‐organizing map (Genecluster) as a tool for cluster analysis of data from pT2N0 prostate cancer cases studied by CGH. Self‐organizing maps are artificial neural networks with the capability to form clusters on the basis of an unsupervised learning rule, i.e., in our examples it gets the CGH data as only information (no clinical data). We studied a group of 40 recent cases without follow‐up, an older group of 20 cases with follow‐up, and the data set obtained by pooling both groups. In all groups good clusterings were found in the sense that clinically similar cases were placed into the same clusters on the basis of the genetic information only. The data indicate that losses on chromosome arms 6q, 8p and 13q are all frequent in pT2N0 prostatic cancer, but the loss on 8p has probably the largest prognostic importance.

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