Neuropilin-2 regulates androgen-receptor transcriptional activity in advanced prostate cancer

Aberrant transcriptional activity of androgen receptor (AR) is one of the dominant mechanisms for developing of castration-resistant prostate cancer (CRPC). Analyzing AR-transcriptional complex related to CRPC is therefore important towards understanding the mechanism of therapy-resistance. While studying its mechanism, we observed that a transmembrane protein called neuropilin-2 (NRP2) plays a contributory role in forming a novel AR-transcriptional complex containing nuclear pore proteins. Using immunogold electron microscopy, high-resolution confocal microscopy, chromatin immunoprecipitation, proteomics, and other biochemical techniques, we delineated the molecular mechanism of how a specific splice variant of NRP2 becomes sumoylated upon ligand stimulation and translocates to the inner nuclear membrane. This splice variant of NRP2 then stabilizes the complex between AR and nuclear pore proteins to promote CRPC specific gene expression. Both full-length and splice variants of AR have been identified in this specific transcriptional complex. In vitro cell line-based assays indicated that depletion of NRP2 not only destabilizes the AR-nuclear pore protein interaction but also inhibits the transcriptional activities of AR. Using an in vivo bone metastasis model, we showed that the inhibition of NRP2 led to the sensitization of CRPC cells toward established anti-AR therapies such as enzalutamide. Overall, our finding emphasize the importance of combinatorial inhibition of NRP2 and AR as an effective therapeutic strategy against treatment refractory prostate cancer

The Role of lncRNAs TAPIR-1 and -2 as Diagnostic Markers and Potential Therapeutic Targets in Prostate Cancer

In search of new biomarkers suitable for the diagnosis and treatment of prostate cancer, genome-wide transcriptome sequencing was carried out with tissue specimens from 40 prostate cancer (PCa) and 8 benign prostate hyperplasia patients. We identified two intergenic long non-coding transcripts, located in close genomic proximity, which are highly expressed in PCa. Microarray studies on a larger cohort comprising 155 patients showed a profound diagnostic potential of these transcripts (AUC~0.94), which we designated as tumor associated prostate cancer increased lncRNA (TAPIR-1 and -2). To test their therapeutic potential, knockdown experiments with siRNA were carried out. The knockdown caused an increase in the p53/TP53 tumor suppressor protein level followed by downregulation of a large number of cell cycle- and DNA-damage repair key regulators. Furthermore, in radiation therapy resistant tumor cells, the knockdown leads to a renewed sensitization of these cells to radiation treatment. Accordingly, in a preclinical PCa xenograft model in mice, the systemic application of nanoparticles loaded with siRNA targeting TAPIR-1 significantly reduced tumor growth. These findings point to a crucial role of TAPIR-1 and -2 in PCa

Loss of Heterozygosity and Copy Number Abnormality in Clear Cell Renal Cell Carcinoma Discovered by High-Density Affymetrix 10K Single Nucleotide Polymorphism Mapping Array1

Genetic aberrations are crucial in renal tumor progression. In this study, we describe loss of heterozygosity (LOH) and DNA-copy number abnormalities in clear cell renal cell carcinoma (cc-RCC) discovered by genome-wide single nucleotide polymorphism (SNP) arrays. Genomic DNA from tumor and normal tissue of 22 human cc-RCCs was analyzed on the Affymetrix GeneChip Human Mapping 10K Array. The array data were validated by quantitative polymerase chain reaction and immunohistochemistry. Reduced DNA copy numbers were detected on chromosomal arm 3p in 91%, on chromosome 9 in 32%, and on chromosomal arm 14q in 36% of the tumors. Gains were detected on chromosomal arm 5q in 45% and on chromosome 7 in 32% of the tumors. Copy number abnormalities were found not only in FHIT and VHL loci, known to be involved in renal carcinogenesis, but also in regions containing putative new tumor suppressor genes or oncogenes. In addition, microdeletions were detected on chromosomes 1 and 6 in genes with unknown impact on renal carcinogenesis. In validation experiments, abnormal protein expression of FOXP1 (on 3p) was found in 90% of tumors (concordance with SNP array data in 85%). As assessed by quantitative polymerase chain reaction, PARK2 and PACRG were down-regulated in 57% and 100%, respectively, and CSF1R was up-regulated in 69% of the cc-RCC cases (concordance with SNP array data in 57%, 33%, and 38%). Genome-wide SNP array analysis not only confirmed previously described large chromosomal aberrations but also detected novel microdeletions in genes potentially involved in tumor genesis of cc-RCC

Lack of Ephrin Receptor A1 Is a Favorable Independent Prognostic Factor in Clear Cell Renal Cell Carcinoma

<div><p>The EPH receptor tyrosine kinases and their cell-bound ligands, the ephrins, have been shown to be associated with cancer development and progression. In this study, mRNA and protein expression of the receptors EPHA1 and EPHA2 as well as of their ligand EFNA1 and their prognostic relevance in clear cell renal cell carcinoma was evaluated. Gene expression was measured in 75 cryo-preserved primary tumors and matched non-malignant renal specimens by quantitative PCR. Protein expression was analyzed by immunohistochemistry on tissue microarrays comprising non-malignant, primary tumors and metastatic renal tissues of 241 patients. Gene and protein expression of all three factors was altered in tumor specimens with EPHA1 and EPHA2 being generally diminished in tumors compared to normal renal tissue, whereas EFNA1 was commonly elevated. A positive EPHA1 and EPHA2 protein staining as well as a low EFNA1 protein level were significantly linked to more aggressive tumor features, but only a positive EPHA1 immunoreactivity was significantly associated with poor survival. In subgroup analyses, EPHA1 and EPHA2 protein levels were significantly higher in metastatic than in primary lesions. Patients with EPHA1/EPHA2-positive tumors or with tumors with positive EPHA1 and low EFNA1 immunoreactivity had the shortest survival rates compared to the respective other combinations. In a multivariate model, EPHA1 was an independent prognostic marker for different survival endpoints. In conclusion, an impaired EPH-ephrin signaling could contribute to the pathogenesis and progression of clear cell renal cell carcinoma.</p></div

CD103+ Tissue Resident T-Lymphocytes Accumulate in Lung Metastases and Are Correlated with Poor Prognosis in ccRCC

Clear cell renal cell carcinoma (ccRCC) is a highly immunogenic tumor with variable responses to immune checkpoint therapy. The significance of the immune cell infiltrate in distant metastases, their association with the immune infiltrate in the primary tumors and their impact on prognosis are poorly described. We hypothesized that specific subtypes of immune cells may be involved in the control of metastases and may have an impact on the prognosis of ccRCC. We analyzed the immune microenvironment in ccRCC primary tumors with distant metastases, paired distant metastases and non-metastasized ccRCC (n = 25 each group) by immunohistochemistry. Confirmatory analyses for CD8+ and CD103+ cells were performed in a large ccRCC cohort (n = 241) using a TCGA-KIRC data set (ITGAE/CD103). High immune cell infiltration in primary ccRCC tumors was significantly correlated with the development of distant tumor metastasis (p &lt; 0.05). A high density of CD103+ cells in ccRCC was more frequent in poorly differentiated tumors (p &lt; 0.001). ccRCCs showed high levels of ITGAE/CD103 compared with adjacent non-neoplastic tissue. A higher density of CD103+ cells and a higher ITGAE/CD103 expression were significantly correlated with poor overall survival in ccRCC (log rank p &lt; 0.05). Our results show a major prognostic value of the immune pattern, in particular CD103+ cell infiltration in ccRCC, and highlight the importance of the tumor immune microenvironment

Differential protein expression of EPHA1, EPHA2 and EFNA1 in primary tumors and subgroups of metastases.

<p>The table beneath each image includes the number of patients and the median staining intensity for each group as well as the p values retrieved by the Mann–Whitney <i>U</i> test. P values highlighted in bold indicate statistically significant differences following corrections for multiple comparisons (n = 5 for each protein) by using the method of Benjamini and Hochberg.</p

Univariate Cox regression analyses for PFS, TSS and OS dependent on clinicopathological parameters and molecular markers.

<p>P values highlighted in bold indicate statistically significant prognostic markers following correction for multiple comparisons (n = 20) by using the method of Benjamini and Hochberg.</p><p>Abbreviations: CI: confidence interval; HR: hazard ratio; n.d.: not determined.</p

Demographic and clinicopathological characteristics of patients included in the study.

1<p>When no clinical (N0) or pathological (pN0) lymph node metastases were noticed the lymph node status was considered as pN0/N0.</p>2<p>Patients with a time to progression of ≤3 months, distant metastases (M1) or unknown M stage at nephrectomy have been excluded from analysis of progression-free survival.</p

Kaplan-Meier analysis of PFS, TSS and OS of ccRCC patients dependent on protein expression.

<p>The table beneath each Kaplan-Meier curve includes the legend, the number of patients and events in each category as well as the respective median survival times, 5- and 10-year survival rates. P values were calculated by logrank test and then corrected for multiple comparisons (n = 29) by using the method of Benjamini and Hochberg. P values highlighted in bold indicate statistically significant differences. Abbreviations: cum.: cumulative; mo.: months; n.r.: not reached.</p

Kaplan-Meier analysis of PFS, TSS and OS of ccRCC patients dependent on pairwise-combined protein expression.

<p>The table beneath each Kaplan-Meier curve includes the legend, the number of patients and events in each category as well as the respective median survival times, 5- and 10-year survival rates. P values were calculated by logrank test and then corrected for multiple comparisons (n = 29) by using the method of Benjamini and Hochberg. P values highlighted in bold indicate statistically significant differences. Abbreviations: cum.: cumulative; mo.: months; neg.: negative; n.r.: not reached; pos.: positive.</p