Exploration of Extracellular Vesicle miRNAs, Targeted mRNAs and Pathways in Prostate Cancer: Relation to Disease Status and Progression.

BACKGROUND: Prostate cancer (PCa) lacks non-invasive specific biomarkers for aggressive disease. We studied the potential of urinary extracellular vesicles (uEV) as a liquid PCa biopsy by focusing on the micro RNA (miRNA) cargo, target messenger RNA (mRNA) and pathway analysis. METHODS: We subjected uEV samples from 31 PCa patients (pre-prostatectomy) to miRNA sequencing and matched uEV and plasma EV (pEV) from three PCa patients to mRNA sequencing. EV quality control was performed by electron microscopy, Western blotting and particle and RNA analysis. We compared miRNA expression based on PCa status (Gleason Score) and progression (post-prostatectomy follow-up) and confirmed selected miRNAs by quantitative PCR. Expression of target mRNAs was mapped in matched EV. RESULTS: Quality control showed typical small uEV, pEV, RNA and EV-protein marker enriched samples. Comparisons between PCa groups revealed mostly unique differentially expressed miRNAs. However, they targeted comprehensive and largely overlapping sets of cancer and progression-associated signalling, resistance, hormonal and immune pathways. Quantitative PCR confirmed changes in miR-892a (Gleason Score 7 vs. ≥8), miR-223-3p (progression vs. no progression) and miR-146a-5p (both comparisons). Their target mRNAs were expressed widely in PCa EV. CONCLUSIONS: PCa status and progression-linked RNAs in uEV are worth exploration in large personalized medicine trials.

Adrenals Contribute to Growth of Castration-Resistant VCaP Prostate Cancer Xenografts.

The role of adrenal androgens as drivers for castration-resistant prostate cancer (CRPC) growth in humans is generally accepted; however, the value of preclinical mouse models of CRPC is debatable, because mouse adrenals do not produce steroids activating the androgen receptor. In this study, we confirmed the expression of enzymes essential for de novo synthesis of androgens in mouse adrenals, with high intratissue concentration of progesterone (P4) and moderate levels of androgens, such as androstenedione, testosterone, and dihydrotestosterone, in the adrenal glands of both intact and orchectomized (ORX) mice. ORX alone had no effect on serum P4 concentration, whereas orchectomized and adrenalectomized (ORX + ADX) resulted in a significant decrease in serum P4 and in a further reduction in the low levels of serum androgens (androstenedione, testosterone, and dihydrotestosterone), measured by mass spectrometry. In line with this, the serum prostate-specific antigen and growth of VCaP xenografts in mice after ORX + ADX were markedly reduced compared with ORX alone, and the growth difference was not abolished by a glucocorticoid treatment. Moreover, ORX + ADX altered the androgen-dependent gene expression in the tumors, similar to that recently shown for the enzalutamide treatment. These data indicate that in contrast to the current view, and similar to humans, mouse adrenals synthesize significant amounts of steroids that contribute to the androgen receptor-dependent growth of CRPC.

Reanalysis of RNA-sequencing data reveals several additional fusion genes with multiple isoforms.

RNA-sequencing and tailored bioinformatic methodologies have paved the way for identification of expressed fusion genes from the chaotic genomes of solid tumors. We have recently successfully exploited RNA-sequencing for the discovery of 24 novel fusion genes in breast cancer. Here, we demonstrate the importance of continuous optimization of the bioinformatic methodology for this purpose, and report the discovery and experimental validation of 13 additional fusion genes from the same samples. Integration of copy number profiling with the RNA-sequencing results revealed that the majority of the gene fusions were promoter-donating events that occurred at copy number transition points or involved high-level DNA-amplifications. Sequencing of genomic fusion break points confirmed that DNA-level rearrangements underlie selected fusion transcripts. Furthermore, a significant portion (>60%) of the fusion genes were alternatively spliced. This illustrates the importance of reanalyzing sequencing data as gene definitions change and bioinformatic methods improve, and highlights the previously unforeseen isoform diversity among fusion transcripts.

MicroRNA expression profiling reveals miRNA families regulating specific biological pathways in mouse frontal cortex and hippocampus.

MicroRNAs (miRNAs) are small regulatory molecules that cause post-transcriptional gene silencing. Although some miRNAs are known to have region-specific expression patterns in the adult brain, the functional consequences of the region-specificity to the gene regulatory networks of the brain nuclei are not clear. Therefore, we studied miRNA expression patterns by miRNA-Seq and microarrays in two brain regions, frontal cortex (FCx) and hippocampus (HP), which have separate biological functions. We identified 354 miRNAs from FCx and 408 from HP using miRNA-Seq, and 245 from FCx and 238 from HP with microarrays. Several miRNA families and clusters were differentially expressed between FCx and HP, including the miR-8 family, miR-182|miR-96|miR-183 cluster, and miR-212|miR-312 cluster overexpressed in FCx and miR-34 family overexpressed in HP. To visualize the clusters, we developed support for viewing genomic alignments of miRNA-Seq reads in the Chipster genome browser. We carried out pathway analysis of the predicted target genes of differentially expressed miRNA families and clusters to assess their putative biological functions. Interestingly, several miRNAs from the same family/cluster were predicted to regulate specific biological pathways. We have developed a miRNA-Seq approach with a bioinformatic analysis workflow that is suitable for studying miRNA expression patterns from specific brain nuclei. FCx and HP were shown to have distinct miRNA expression patterns which were reflected in the predicted gene regulatory pathways. This methodology can be applied for the identification of brain region-specific and phenotype-specific miRNA-mRNA-regulatory networks from the adult and developing rodent brain.

Systematic analysis of microRNAs targeting the androgen receptor in prostate cancer cells.

Androgen receptor (AR) is expressed in all stages of prostate cancer progression, including in castration-resistant tumors. Eliminating AR function continues to represent a focus of therapeutic investigation, but AR regulatory mechanisms remain poorly understood. To systematically characterize mechanisms involving microRNAs (miRNAs), we conducted a gain-of function screen of 1129 miRNA molecules in a panel of human prostate cancer cell lines and quantified changes in AR protein content using protein lysate microarrays. In this way, we defined 71 unique miRNAs that influenced the level of AR in human prostate cancer cells. RNA sequencing data revealed that the 3'UTR of AR (and other genes) is much longer than currently used in miRNA target prediction programs. Our own analyses predicted that most of the miRNA regulation of AR would target an extended 6 kb 3'UTR. 3'UTR-binding assays validated 13 miRNAs that are able to regulate this long AR 3'UTR (miR-135b, miR-185, miR-297, miR-299-3p, miR-34a, miR-34c, miR-371-3p, miR-421, miR-449a, miR-449b, miR-634, miR-654-5p, and miR-9). Fifteen AR downregulating miRNAs decreased androgen-induced proliferation of prostate cancer cells. In particular, analysis of clinical prostate cancers confirmed a negative correlation of miR-34a and miR-34c expression with AR levels. Our findings establish that miRNAs interacting with the long 3'UTR of the AR gene are important regulators of AR protein levels, with implications for developing new therapeutic strategies to inhibit AR function and androgen-dependent cell growth.

Identification of fusion genes in breast cancer by paired-end RNA-sequencing.

BACKGROUND: Until recently, chromosomal translocations and fusion genes have been an underappreciated class of mutations in solid tumors. Next-generation sequencing technologies provide an opportunity for systematic characterization of cancer cell transcriptomes, including the discovery of expressed fusion genes resulting from underlying genomic rearrangements. RESULTS: We applied paired-end RNA-seq to identify 24 novel and 3 previously known fusion genes in breast cancer cells. Supported by an improved bioinformatic approach, we had a 95% success rate of validating gene fusions initially detected by RNA-seq. Fusion partner genes were found to contribute promoters (5' UTR), coding sequences and 3' UTRs. Most fusion genes were associated with copy number transitions and were particularly common in high-level DNA amplifications. This suggests that fusion events may contribute to the selective advantage provided by DNA amplifications and deletions. Some of the fusion partner genes, such as GSDMB in the TATDN1-GSDMB fusion and IKZF3 in the VAPB-IKZF3 fusion, were only detected as a fusion transcript, indicating activation of a dormant gene by the fusion event. A number of fusion gene partners have either been previously observed in oncogenic gene fusions, mostly in leukemias, or otherwise reported to be oncogenic. RNA interference-mediated knock-down of the VAPB-IKZF3 fusion gene indicated that it may be necessary for cancer cell growth and survival. CONCLUSIONS: In summary, using RNA-sequencing and improved bioinformatic stratification, we have discovered a number of novel fusion genes in breast cancer, and identified VAPB-IKZF3 as a potential fusion gene with importance for the growth and survival of breast cancer cells.

The gene expression signature of genomic instability in breast cancer is an independent predictor of clinical outcome.

Recently, expression profiling of breast carcinomas has revealed gene signatures that predict clinical outcome, and discerned prognostically relevant breast cancer subtypes. Measurement of the degree of genomic instability provides a very similar stratification of prognostic groups. We therefore hypothesized that these features are linked. We used gene expression profiling of 48 breast cancer specimens that profoundly differed in their degree of genomic instability and identified a set of 12 genes that defines the 2 groups. The biological and prognostic significance of this gene set was established through survival prediction in published datasets from patients with breast cancer. Of note, the gene expression signatures that define specific prognostic subtypes in other breast cancer datasets, such as luminal A and B, basal, normal-like, and ERBB2+, and prognostic signatures including MammaPrint and Oncotype DX, predicted genomic instability in our samples. This remarkable congruence suggests a biological interdependence of poor-prognosis gene signatures, breast cancer subtypes, genomic instability, and clinical outcome.

Analysis of signaling pathways in 90 cancer cell lines by protein lysate array.

UNLABELLED: Multiple signal transduction pathways play a crucial role in cancer development, progression, and response to different therapies. An important issue is whether common signal transduction pathways are ubiquitously altered in all cancer types and some unique pathways are involved in different cancer types. Another important issue is whether and how transduction signaling molecules are heterogeneously expressed and activated in different cancer cells within and between cancer cell types. METHODS: To gain insight into these issues, we assembled a protein lysate array with 90 different cell lines of 12 different cell types. Each sample is diluted 2-fold six times, and samples from the dilution series were printed three times on the array. We then measured the expression levels and phosphorylation status of 52 different signaling proteins with specific antibodies and carried out statistical hierarchical clustering analysis. RESULTS: The most significant finding based on the cluster analysis was that the cell lines did not group based on tumor types, suggesting that the signaling pathways studied were commonly activated in most of the tumor types cultured in vitro. As expected, related proteins associated with specific signaling pathways clustered together, and analysis of the 30 most differentially expressed proteins revealed the PI3-K signaling pathway was upregulated in several different tumor types and the VEGF-angiogenesis pathway was downregulated in hematopoetic cancers. Another important observation, with clinical implications was that EGFR was the most heterogeneous among all the cell lines. We also observed signaling pathways unique to specific types of cancers such as the inverse relationship between p16ink and Rb, and the EGFR mediated pathway activation characteristic of pancreatic cancers. CONCLUSIONS: Using reverse phase lysate array analysis in this study, we were able to determine potential relationships and signaling pathways, both common and unique, to different types of cancer using cell lines in vitro. This data could be utilized for mining information related to an individual cancer of interest and combined with morphological and genomic profiles would help in creating a combination of expression markers and/or functional signaling maps for specific cancer diagnosis and therapy.

Global gene expression profile of human cord blood-derived CD133+ cells.

Human cord blood (CB)-derived CD133+ cells carry characteristics of primitive hematopoietic cells and proffer an alternative for CD34+ cells in hematopoietic stem cell (HSC) transplantation. To characterize the CD133+ cell population on a genetic level, a global expression analysis of CD133+ cells was performed using oligonucleotide microarrays. CD133+ cells were purified from four fresh CB units by immunomagnetic selection. All four CD133+ samples showed significant similarity in their gene expression pattern, whereas they differed clearly from the CD133- control samples. In all, 690 transcripts were differentially expressed between CD133+ and CD133- cells. Of these, 393 were increased and 297 were decreased in CD133+ cells. The highest overexpression was noted in genes associated with metabolism, cellular physiological processes, cell communication, and development. A set of 257 transcripts expressed solely in the CD133+ cell population was identified. Colony-forming unit (CFU) assay was used to detect the clonal progeny of precursors present in the studied cell populations. The results demonstrate that CD133+ cells express primitive markers and possess clonogenic progenitor capacity. This study provides a gene expression profile for human CD133+ cells. It presents a set of genes that may be used to unravel the properties of the CD133+ cell population, assumed to be highly enriched in HSCs.

Transcriptional profiling reflects shared and unique characters for CD34+ and CD133+ cells.

CD34 and CD133 are the most commonly used markers to enrich hematopoietic stem cells (HSCs). Positively selected HSCs are increasingly used for autologous and allogeneic transplantation, yet the biological properties of CD34(+) and CD133(+) cells are largely unknown. In the present study, a genome-wide gene expression analysis of human cord blood (CB)-derived CD34(+) cells was performed. The CD34(+) gene expression profile was compared to an identically constructed CD133(+) gene expression profile to reveal the specific expression patterns and major differences of CD34(+) and CD133(+) cells. As expected, many genes were similarly expressed in the two cell populations, but cell-type-specific gene expression was also demonstrated. Self-organizing map analysis was used to identify transcripts having similar expression patterns, and the results were compared between CD34(+) and CD133(+) cells. Also, a prioritization algorithm was used to rank the genes best separating CD34(+) and CD133(+) cells from their CD34() and CD133() counterparts in CB. Our results show that CD133(+) cells have higher numbers of up-regulated genes than CD34(+) cells. Furthermore, the uniquely expressed genes in CD34(+) or CD133(+) cell populations were associated with different biological processes. CD34(+) cells overexpressed many transcripts associated with development and response to stress or external stimuli. In CD133(+) cells, the most significantly represented biological processes were establishment and maintenance of chromatin architecture, DNA metabolism, and cell cycle. The differences between the gene expression profiles of CD34(+) and CD133(+) cells indicate the more primitive nature of CD133(+) cells. These profiles suggest that CD34(+) and CD133(+) cells may have different roles in hematopoietic regeneration.

Gene-expression profiling predicts recurrence in Dukes' C colorectal cancer.

BACKGROUND & AIMS: Although approximately 50% of Dukes' C colorectal cancer patients are surgically cured, it is currently not possible to distinguish these patients from those at high risk of recurrence. The recent advent of routine adjuvant chemotherapy for these patients has greatly complicated the identification of new markers predicting the response to surgery, which is now reliant on archived materials. Microarray analysis allows fine tumor classification but cannot be used with paraffin-embedded archival samples. METHODS: We used microarray analysis of a unique set of fresh-frozen tumor samples from Dukes' C patients who had surgery as the only form of treatment to identify molecular signatures that characterize tumors from patients with good and bad prognosis. RESULTS: Unsupervised hierarchical clustering and a K-nearest neighbors-based classifier identified groups of patients with significantly different survival (P = .019 and P = .0001). Expression profiling outperformed previously reported genetic markers of prognosis such as TP53 and K-RAS mutational status and allelic imbalance in chromosome 18q, which were of limited prognostic power in this study. Functional categories significantly enriched in gene-expression differences included protein transport and folding. The prognostic potential of the RAS homologue RHOA, one of the most differentially expressed genes, was further investigated using immunohistochemistry and a tissue microarray containing 137 independent Dukes' C tumor samples. Reduced RHOA expression was associated with significantly shorter survival (P = .01). CONCLUSIONS: This study shows that gene-expression profiling of surgical tumor samples can predict recurrence in Dukes' C patients. Therefore, this approach could be used to guide decisions concerning the clinical management of these patients.