Genome-wide DNA methylation measurements in prostate tissues uncovers novel prostate cancer diagnostic biomarkers and transcription factor binding patterns.

BACKGROUND: Current diagnostic tools for prostate cancer lack specificity and sensitivity for detecting very early lesions. DNA methylation is a stable genomic modification that is detectable in peripheral patient fluids such as urine and blood plasma that could serve as a non-invasive diagnostic biomarker for prostate cancer. METHODS: We measured genome-wide DNA methylation patterns in 73 clinically annotated fresh-frozen prostate cancers and 63 benign-adjacent prostate tissues using the Illumina Infinium HumanMethylation450 BeadChip array. We overlaid the most significantly differentially methylated sites in the genome with transcription factor binding sites measured by the Encyclopedia of DNA Elements consortium. We used logistic regression and receiver operating characteristic curves to assess the performance of candidate diagnostic models. RESULTS: We identified methylation patterns that have a high predictive power for distinguishing malignant prostate tissue from benign-adjacent prostate tissue, and these methylation signatures were validated using data from The Cancer Genome Atlas Project. Furthermore, by overlaying ENCODE transcription factor binding data, we observed an enrichment of enhancer of zeste homolog 2 binding in gene regulatory regions with higher DNA methylation in malignant prostate tissues. CONCLUSIONS: DNA methylation patterns are greatly altered in prostate cancer tissue in comparison to benign-adjacent tissue. We have discovered patterns of DNA methylation marks that can distinguish prostate cancers with high specificity and sensitivity in multiple patient tissue cohorts, and we have identified transcription factors binding in these differentially methylated regions that may play important roles in prostate cancer development.

NUSAP1 expression is upregulated by loss of RB1 in prostate cancer cells.

BACKGROUND: Overexpression of NUSAP1 is associated with poor prognosis in prostate cancer, but little is known about what leads to its overexpression. Based on previous observations that NUSAP1 expression is enhanced by E2F1, we hypothesized that NUSAP1 expression is regulated, at least in part, by loss of RB1 via the RB1/E2F1 axis. METHODS: Using Significance Analysis of Microarrays, we examined RB1, E2F1, and NUSAP1 transcript levels in prostate cancer gene expression datasets. We compared NUSAP1 expression levels in DU145, LNCaP, and PC-3 prostate cancer cell lines via use of cDNA microarray data, RT-qPCR, and Western blots. In addition, we used lentiviral expression constructs to knockdown RB1 in prostate cancer cell lines and transient transfections to knockdown E2F1, and investigated RB1, E2F1, and NUSAP1 expression levels with RT-qPCR and Western blots. Finally, in DU145 cells or PC-3 cells that stably underexpress RB1, we used proliferation and invasion assays to assess whether NUSAP1 knockdown affects proliferation or invasion. RESULTS: NUSAP1 transcript levels are positively correlated with E2F1 and negatively correlated with RB1 transcript levels in prostate cancer microarray datasets. NUSAP1 expression is elevated in the RB1-null DU145 prostate cancer cell line, as opposed to LNCaP and PC-3 cell lines. Furthermore, NUSAP1 expression increases upon knockdown of RB1 in prostate cancer cell lines (LNCaP and PC-3) and decreases after knockdown of E2F1. Lastly, knockdown of NUSAP1 in DU145 cells or PC-3 cells with stable knockdown of RB1 decreases proliferation and invasion of these cells. CONCLUSION: Our studies support the notion that NUSAP1 expression is upregulated by loss of RB1 via the RB1/E2F1 axis in prostate cancer cells. Such upregulation may promote prostate cancer progression by increasing proliferation and invasion of prostate cancer cells. NUSAP1 may thus represent a novel therapeutic target.

Novel fusion transcripts associate with progressive prostate cancer.

The mechanisms underlying the potential for aggressive behavior of prostate cancer (PCa) remain elusive. In this study, whole genome and/or transcriptome sequencing was performed on 19 specimens of PCa, matched adjacent benign prostate tissues, matched blood specimens, and organ donor prostates. A set of novel fusion transcripts was discovered in PCa. Eight of these fusion transcripts were validated through multiple approaches. The occurrence of these fusion transcripts was then analyzed in 289 prostate samples from three institutes, with clinical follow-up ranging from 1 to 15 years. The analyses indicated that most patients [69 (91%) of 76] positive for any of these fusion transcripts (TRMT11-GRIK2, SLC45A2-AMACR, MTOR-TP53BP1, LRRC59-FLJ60017, TMEM135-CCDC67, KDM4-AC011523.2, MAN2A1-FER, and CCNH-C5orf30) experienced PCa recurrence, metastases, and/or PCa-specific death after radical prostatectomy. These outcomes occurred in only 37% (58/157) of patients without carrying those fusion transcripts. Three fusion transcripts occurred exclusively in PCa samples from patients who experienced recurrence or PCaerelated death. The formation of these fusion transcripts may be the result of genome recombination. A combination of these fusion transcripts in PCa with Gleason's grading or with nomogram significantly improves the prediction rate of PCa recurrence. Our analyses suggest that formation of these fusion transcripts may underlie the aggressive behavior of PCa.

Increased expression of GCNT1 is associated with altered O-glycosylation of PSA, PAP, and MUC1 in human prostate cancers.

BACKGROUND: Protein glycosylation is a common posttranslational modification and glycan structural changes have been observed in several malignancies including prostate cancer. We hypothesized that altered glycosylation could be related to differences in gene expression levels of glycoprotein synthetic enzymes between normal and malignant prostate tissues. METHODS: We interrogated prostate cancer gene expression data for reproducible changes in expression of glycoprotein synthetic enzymes. Over-expression of GCNT1 was validated in prostate samples using RT-PCR. ELISA was used to measure core 2 O-linked glycan sialyl Lewis X (sLe(x) ) of prostate specific antigen (PSA), Mucin1 (MUC1), and prostatic acidic phosphatase (PAP) proteins. RESULTS: A key glycosyltransferase, GCNT1, was consistently over-expressed in several prostate cancer gene expression datasets. RT-PCR confirmed increased transcript levels in cancer samples compared to normal prostate tissue in fresh-frozen prostate tissue samples. ELISA using PSA, PAP, and MUC1 capture antibodies and a specific core 2 O-linked sLe(x) detection antibody demonstrated elevation of this glycan structure in cancer compared to normal tissues for MUC1 (P = 0.01), PSA (P = 0.03) and near significant differences in PAP sLe(x) levels (P = 0.06). MUC1, PSA and PAP protein levels alone were not significantly different between paired normal and malignant prostate samples. CONCLUSIONS: GCNT1 is over-expressed in prostate cancer and is associated with higher levels of core 2 O-sLe(x) in PSA, PAP and MUC1 proteins. Alterations of O-linked glycosylation could be important in prostate cancer biology and could provide a new avenue for development of prostate cancer specific glycoprotein biomarkers.

mRNA-Seq of single prostate cancer circulating tumor cells reveals recapitulation of gene expression and pathways found in prostate cancer.

Circulating tumor cells (CTC) mediate metastatic spread of many solid tumors and enumeration of CTCs is currently used as a prognostic indicator of survival in metastatic prostate cancer patients. Some evidence suggests that it is possible to derive additional information about tumors from expression analysis of CTCs, but the technical difficulty of isolating and analyzing individual CTCs has limited progress in this area. To assess the ability of a new generation of MagSweeper to isolate intact CTCs for downstream analysis, we performed mRNA-Seq on single CTCs isolated from the blood of patients with metastatic prostate cancer and on single prostate cancer cell line LNCaP cells spiked into the blood of healthy donors. We found that the MagSweeper effectively isolated CTCs with a capture efficiency that matched the CellSearch platform. However, unlike CellSearch, the MagSweeper facilitates isolation of individual live CTCs without contaminating leukocytes. Importantly, mRNA-Seq analysis showed that the MagSweeper isolation process did not have a discernible impact on the transcriptional profile of single LNCaPs isolated from spiked human blood, suggesting that any perturbations caused by the MagSweeper process on the transcriptional signature of isolated cells are modest. Although the RNA from patient CTCs showed signs of significant degradation, consistent with reports of short half-lives and apoptosis amongst CTCs, transcriptional signatures of prostate tissue and of cancer were readily detectable with single CTC mRNA-Seq. These results demonstrate that the MagSweeper provides access to intact CTCs and that these CTCs can potentially supply clinically relevant information.

DNA methylation profiling reveals novel biomarkers and important roles for DNA methyltransferases in prostate cancer.

Candidate gene-based studies have identified a handful of aberrant CpG DNA methylation events in prostate cancer. However, DNA methylation profiles have not been compared on a large scale between prostate tumor and normal prostate, and the mechanisms behind these alterations are unknown. In this study, we quantitatively profiled 95 primary prostate tumors and 86 benign adjacent prostate tissue samples for their DNA methylation levels at 26,333 CpGs representing 14,104 gene promoters by using the Illumina HumanMethylation27 platform. A 2-class Significance Analysis of this data set revealed 5912 CpG sites with increased DNA methylation and 2151 CpG sites with decreased DNA methylation in tumors (FDR < 0.8%). Prediction Analysis of this data set identified 87 CpGs that are the most predictive diagnostic methylation biomarkers of prostate cancer. By integrating available clinical follow-up data, we also identified 69 prognostic DNA methylation alterations that correlate with biochemical recurrence of the tumor. To identify the mechanisms responsible for these genome-wide DNA methylation alterations, we measured the gene expression levels of several DNA methyltransferases (DNMTs) and their interacting proteins by TaqMan qPCR and observed increased expression of DNMT3A2, DNMT3B, and EZH2 in tumors. Subsequent transient transfection assays in cultured primary prostate cells revealed that DNMT3B1 and DNMT3B2 overexpression resulted in increased methylation of a substantial subset of CpG sites that showed tumor-specific increased methylation.