Secreted protein, acidic and rich in cysteine-like 1 (SPARCL1) is down regulated in aggressive prostate cancers and is prognostic for poor clinical outcome

Prostate cancer is the second leading cause of cancer death among United States men. However, disease aggressiveness is varied, with low-grade disease often being indolent and high-grade cancer accounting for the greatest density of deaths. Outcomes are also disparate among men with high-grade prostate cancer, with upwards of 65% having disease recurrence even after primary treatment. Identification of men at risk for recurrence and elucidation of the molecular processes that drive their disease is paramount, as these men are the most likely to benefit from multimodal therapy. We previously showed that androgen-induced expression profiles in prostate development are reactivated in aggressive prostate cancers. Herein, we report the down-regulation of one such gene, Sparcl1, a secreted protein, acidic and rich in cysteine (SPARC) family matricellular protein, during invasive phases of prostate development and regeneration. We further demonstrate a parallel process in prostate cancer, with decreased expression of SPARCL1 in high-grade/metastatic prostate cancer. Mechanistically, we demonstrate that SPARCL1 loss increases the migratory and invasive properties of prostate cancer cells through Ras homolog gene family, member C (RHOC), a known mediator of metastatic progression. By using models incorporating clinicopathologic parameters to predict prostate cancer recurrence after treatment, we show that SPARCL1 loss is a significant, independent prognostic marker of disease progression. Thus, SPARCL1 is a potent regulator of cell migration/invasion and its loss is independently associated with prostate cancer recurrence.     

Identification of a PAX-FKHR gene expression signature that defines molecular classes and determines the prognosis of alveolar rhabdomyosarcomas

Alveolar rhabdomyosarcomas (ARMS) are aggressive soft-tissue sarcomas affecting children and young adults. Most ARMS tumors express the PAX3-FKHR or PAX7-FKHR (PAX-FKHR) fusion genes resulting from the t(2;13) or t(1;13) chromosomal translocations, respectively. However, up to 25% of ARMS tumors are fusion negative, making it unclear whether ARMS represent a single disease or multiple clinical and biological entities with a common phenotype. To test to what extent PAX-FKHR determine class and behavior of ARMS, we used oligonucleotide microarray expression profiling on 139 primary rhabdomyosarcoma tumors and an in vitro model. We found that ARMS tumors expressing either PAX-FKHR gene share a common expression profile distinct from fusion-negative ARMS and from the other rhabdomyosarcoma variants. We also observed that PAX-FKHR expression above a minimum level is necessary for the detection of this expression profile. Using an ectopic PAX3-FKHR and PAX7-FKHR expression model, we identified an expression signature regulated by PAX-FKHR that is specific to PAX-FKHR-positive ARMS tumors. Data mining for functional annotations of signature genes suggested a role for PAX-FKHR in regulating ARMS proliferation and differentiation. Cox regression modeling identified a subset of genes within the PAX-FKHR expression signature that segregated ARMS patients into three risk groups with 5-year overall survival estimates of 7%, 48%, and 93%. These prognostic classes were independent of conventional clinical risk factors. Our results show that PAX-FKHR dictate a specific expression signature that helps define the molecular phenotype of PAX-FKHR-positive ARMS tumors and, because it is linked with disease outcome in ARMS patients, determine tumor behavior.     

The lncRNAs PCGEM1 and PRNCR1 are not implicated in castration resistant prostate cancer

Long noncoding RNAs (lncRNAs) are increasingly implicated in cancer biology, contributing to essential cancer cell functions such as proliferation, invasion, and metastasis. In prostate cancer, several lncRNAs have been nominated as critical actors in disease pathogenesis. Among these, expression of PCGEM1 and PRNCR1 has been identified as a possible component in disease progression through the coordination of androgen receptor (AR) signaling (Yang et al., Nature 2013, see ref. [1]). However, concerns regarding the robustness of these findings have been suggested. Here, we sought to evaluate whether PCGEM1 and PRNCR1 are associated with prostate cancer. Through a comprehensive analysis of RNA-sequencing data (RNA-seq), we find evidence that PCGEM1 but not PRNCR1 is associated with prostate cancer. We employ a large cohort of >230 high-risk prostate cancer patients with long-term outcomes data to show that, in contrast to prior reports, neither gene is associated with poor patient outcomes. We further observe no evidence that PCGEM1 nor PRNCR1 interact with AR, and neither gene is a component of AR signaling. Thus, we conclusively demonstrate that PCGEM1 and PRNCR1 are not prognostic lncRNAs in prostate cancer and we refute suggestions that these lncRNAs interact in AR signaling.     

Impact of a genomic classifier of metastatic risk on postoperative treatment recommendations for prostate cancer patients: a report from the DECIDE study group

Background

Only a minority of prostate cancer patients with adverse pathology and biochemical recurrence (BCR) post radical prostatectomy (RP) experience metastasis and die from prostate cancer. Improved risk prediction models using genomic information may enable clinicians to better weigh the risk of metastasis and the morbidity and costs of treatment in a clinically heterogeneous population.

Purpose

We present a clinical utility study that evaluates the influence on urologist treatment recommendations for patients at risk of metastasis using a genomic-based prediction model (Decipher^TM).

Methods

A prospective, pre-post design was used to assess urologist treatment recommendations following RP in both the adjuvant (without any evidence of PSA rise) and salvage (BCR) settings. Urologists were presented de-identified pathology reports and genomic classifier (GC) test results for 24 patients from a previously conducted GC validation study in high-risk post-RP men. Participants were fellowship trained, high-volume urologic oncologists (n=21) from 18 US institutions. Treatment recommendations for secondary therapy were made based solely on clinical information (pre-GC) and then with genomic biomarker information (post-GC). This study was approved by an independent IRB.

Results

Treatment recommendations changed from pre-GC to post-GC in 43% of adjuvant, and in 53% of salvage setting case evaluations. In the adjuvant setting, urologists changed their treatment recommendations from treatment (i.e. radiation and/or hormones) to close observation post-GC in 27% of cases. For cases with low GC risk (<3% risk of metastasis), observation was recommended for 79% of the case evaluations post-GC. Consistent trends were observed in the salvage setting.

Conclusion

These results indicate that urologists across a range of practice settings are likely to change treatment decisions when presented with genomic biomarker information following RP. Implementation of genomic risk stratification into routine clinical practice may better direct treatment decision-making post-RP.