Baseline CTC Count as a Predictor of Long-Term Outcomes in High-Risk Prostate Cancer.

The aim of the present study was to verify whether the baseline circulating tumor cell (CTC) count might serve as a predictor of overall survival (OS) and metastasis-free survival (MFS) in patients with high-risk prostate cancer (PCa) during a follow-up period of at least 5 years. CTCs were enumerated using three different assay formats in 104 patients: the CellSearch® system, EPISPOT assay and GILUPI CellCollector. A total of 57 (55%) patients survived until the end of the follow-up period, with a 5 year OS of 66% (95% CI: 56-74%). The analysis of univariate Cox proportional hazard models identified a baseline CTC count ≥ 1, which was determined with the CellSearch® system, a Gleason sum ≥ 8, cT ≥ 2c and metastases at initial diagnosis as significant predictors of a worse OS in the entire cohort. The CTC count ≥ 1 was also the only significant predictor of a worse OS in a subset of 85 patients who presented with localized PCa at the baseline. The baseline CTC number did not affect the MFS. In conclusion, the baseline CTC count can be considered a determinant of survival in high-risk PCa and also in patients with a localized disease. However, determining the prognostic value of the CTC count in patients with localized PCa would optimally require longitudinal monitoring of this parameter.

Circulating Tumor Cells as a Marker of Disseminated Disease in Patients with Newly Diagnosed High-Risk Prostate Cancer.

The aim of this study was to investigate whether the enumeration of circulating tumor cells (CTCs) in blood can differentiate between true localized and metastatic prostate cancer. A cross-sectional study of 104 prostate cancer patients with newly diagnosed high-risk prostate cancer was conducted. In total, 19 patients presented metastatic disease and 85 were diagnosed with localized disease. Analyses included intergroup comparison of CTC counts, determined using the CellSearch® system, EPISPOT assay and GILUPI CellCollector®, and ROC analysis verifying the accuracy of CTC count as a maker of disseminated prostate cancer. The vast majority (94.7%) of patients with advanced-stage cancer tested positively for CTCs in at least one of the assays. However, significantly higher CTC counts were determined with the CellSearch® system compared to EPISPOT assay and GILUPI CellCollector®. Identification of ≥4 CTCs with the CellSearch® system was the most accurate predictor of metastatic disease (sensitivity 0.500; specificity 0.900; AUC (95% CI) 0.760 (0.613-0.908). Furthermore, we tried to create a model to enhance the specificity and sensitivity of metastatic prediction with CTC counts by incorporating patient's clinical data, including PSA serum levels, Gleason score and clinical stage. The composite biomarker panel achieved the following performance: sensitivity, 0.611; specificity, 0.971; AUC (95% CI), 0.901 (0.810-0.993). Thus, although the sensitivity of CTC detection needs to be further increased, our findings suggest that high CTC counts might contribute to the identification of high-risk prostate cancer patients with occult metastases at the time of diagnosis.

Analysis of Circulating Tumor Cells in Patients with Non-Metastatic High-Risk Prostate Cancer before and after Radiotherapy Using Three Different Enumeration Assays.

The characterization of circulating tumor cells (CTCs) can lead to a promising strategy for monitoring residual or relapsing prostate cancer (PCa) after local therapy. The aim of this study was to compare three innovative technologies for CTC enumeration in 131 high-risk patients with PCa, before and after radiotherapy, combined with androgen deprivation. The CTC number was tested using the FDA-cleared CellSearch® system, the dual fluoro-EPISPOT assay that only detects functional CTCs, and the in vivo CellCollector® technology. The highest percentage of CTC-positive patients was detected with the CellCollector® (48%) and dual fluoro-EPISPOT (42%) assays, while the CellSearch® system presented the lowest rate (14%). Although the concordance among methods was only 23%, the cumulative positivity rate was 79%. A matched-pair analysis of the samples before, and after, treatment suggested a trend toward a decrease in CTC count after treatment with all methods. CTC tended to be positivity correlated with age for the fluoro-EPISPOT assay and with PSA level from the data of three assays. Combining different CTC assays improved CTC detection rates in patients with non-metastatic high-risk PCa before and after treatment. Our findings do not support the hypothesis that radiotherapy leads to cancer cell release in the circulation.

Genetic characterization of Polish ccRCC patients: somatic mutation analysis of PBRM1, BAP1 and KDMC5, genomic SNP array analysis in tumor biopsy and preliminary results of chromosome aberrations analysis in plasma cell free DNA.

BACKGROUND: Mutation analysis and cytogenetic testing in clear cell renal cell carcinoma (ccRCC) is not yet implemented in a routine diagnostics of ccRCC. MATERIAL AND METHODS: We characterized the chromosomal alterations in 83 ccRCC tumors from Polish patients using whole genome SNP genotyping assay. Moreover, the utility of next generation sequencing of cell free DNA (cfDNA) in patients plasma as a potential tool for non-invasive cytogenetic analysis was tested. Additionally, tumor specific somatic mutations in PBRM1, BAP1 and KDM5C were determined. RESULTS: We confirmed a correlation between deletions at 9p and higher tumor size, and deletion of chromosome 20 and the survival time. In Fuhrman grade 1, only aberrations of 3p and 8p deletion, gain of 5q and 13q and gains of chromosome 7 and 16 were present. The number of aberrations increased with Fuhrman grade, all chromosomes displayed cytogenetic changes in G3 and G4. ccRCC specific chromosome aberrations were observed in cfDNA, although discrepancies were found between cfDNA and tumor samples. In total 12 common and 94 rare variants were detected in PBRM1, BAP1 and KDM5C, with four potentially pathogenic variants. We observed markedly lower mutation load in PBRM1. CONCLUSIONS: Cytogenetic analysis of cfDNA may allow more accurate diagnosis of tumor aberrations and therefore the correlation between the chromosome aberrations in cfDNA and clinical outcome should be studied in larger cohorts. The functional studies on in BAP1, KDM5C, PBRM1 mutations in large, independent sample set would be necessary for the assessment of their prognostic and diagnostic potential.

Expression of pre-selected TMEMs with predicted ER localization as potential classifiers of ccRCC tumors.

BACKGROUND: VHL inactivation is the most established molecular characteristic of clear cell renal cell carcinoma (ccRCC), with only a few additional genes implicated in development of this kidney tumor. In recently published ccRCC gene expression meta-analysis study we identified a number of deregulated genes with limited information available concerning their biological role, represented by gene transcripts belonging to transmembrane proteins family (TMEMs). TMEMs are predicted to be components of cellular membranes, such as mitochondrial membranes, ER, lysosomes and Golgi apparatus. Interestingly, the function of majority of TMEMs remains unclear. Here, we analyzed expression of ten TMEM genes in the context of ccRCC progression and development, and characterized these proteins bioinformatically. METHODS: The expression of ten TMEMs (RTP3, SLC35G2, TMEM30B, TMEM45A, TMEM45B, TMEM61, TMEM72, TMEM116, TMEM207 and TMEM213) was measured by qPCR. T-test, Pearson correlation, univariate and multivariate logistic and Cox regression were used in statistical analysis. The topology of studied proteins was predicted with Metaserver, together with PSORTII, Pfam and Localizome tools. RESULTS: We observed significant deregulation of expression of 10 analyzed TMEMs in ccRCC tumors. Cluster analysis of expression data suggested the down-regulation of all tested TMEMs to be a descriptor of the most advanced tumors. Logistic and Cox regression potentially linked TMEM expression to clinical parameters such as: metastasis, Fuhrman grade and overall survival. Topology predictions classified majority of analyzed TMEMs as type 3 and type 1 transmembrane proteins, with predicted localization mainly in ER. CONCLUSIONS: The massive down-regulation of expression of TMEM family members suggests their importance in the pathogenesis of ccRCC and the bioinformatic analysis of TMEM topology implies a significant involvement of ER proteins in ccRCC pathology.

FUT11 as a potential biomarker of clear cell renal cell carcinoma progression based on meta-analysis of gene expression data.

In this paper, we provide a comprehensive summary of available clear cell renal cell carcinoma (ccRCC) microarray data in the form of meta-analysis of genes differentially regulated in tumors as compared to healthy tissue, using effect size to measure the strength of a relationship between the disease and gene expression. We identified 725 differentially regulated genes, with a number of interesting targets, such as TMEM213, SMIM5, or ATPases: ATP6V0A4 and ATP6V1G3, of which limited or no information is available in terms of their function in ccRCC pathology. Downregulated genes tended to represent pathways related to tissue remodeling, blood clotting, vasodilation, and energy metabolism, while upregulated genes were classified into pathways generally deregulated in cancers: immune system response, inflammatory response, angiogenesis, and apoptosis. One hundred fifteen deregulated genes were included in network analysis, with EGLN3, AP-2, NR3C1, HIF1A, and EPAS1 (gene encoding HIF2-α) as points of functional convergence, but, interestingly, 610 genes failed to join previously identified molecular networks. Furthermore, we validated the expression of 14 top deregulated genes in independent sample set of 32 ccRCC tumors by qPCR and tested if it could serve as a marker of disease progression. We found a correlation of high fucosyltransferase 11 (FUT11) expression with non-symptomatic course of the disease, which suggests that FUT11's expression might be potentially used as a biomarker of disease progression.