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

Simple Summary Prostate cancer lacks non-invasive specific biomarkers for aggressive disease. Urinary extracellular vesicles (uEV) could provide such markers; however, due to technical challenges, little is known regarding the pathogenesis pathways reflected in uEV. We performed a miRNA, target mRNA and pathway study focused on uEV, exploring the differences between cancer (1) status groups (Gleason score) and (2) progression groups. The uEV provided a surprisingly comprehensive presentation of differentially expressed miRNAs, target mRNAs and pathogenesis pathways. The miRNAs associated with prostate cancer status or progression were mostly unique, but still targeted overlapping sets of signalling, resistance, hormonal and immune pathways. Interestingly, mRNA targets of the key miRNAs (miR-892a, miR-223-3p, miR-146a-5p) were widely expressed in both uEV and plasma EV from PCa patients. The study thus suggests that uEV carry a vast presentation of PCa status and progression-linked RNAs that are worth further exploration in large personalized medicine trials. 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.Peer reviewe

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

Simple Summary Prostate cancer lacks non-invasive specific biomarkers for aggressive disease. Urinary extracellular vesicles (uEV) could provide such markers; however, due to technical challenges, little is known regarding the pathogenesis pathways reflected in uEV. We performed a miRNA, target mRNA and pathway study focused on uEV, exploring the differences between cancer (1) status groups (Gleason score) and (2) progression groups. The uEV provided a surprisingly comprehensive presentation of differentially expressed miRNAs, target mRNAs and pathogenesis pathways. The miRNAs associated with prostate cancer status or progression were mostly unique, but still targeted overlapping sets of signalling, resistance, hormonal and immune pathways. Interestingly, mRNA targets of the key miRNAs (miR-892a, miR-223-3p, miR-146a-5p) were widely expressed in both uEV and plasma EV from PCa patients. The study thus suggests that uEV carry a vast presentation of PCa status and progression-linked RNAs that are worth further exploration in large personalized medicine trials. 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.Peer reviewe

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

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

MicroRNA Expression Profiling Reveals MiRNA Families Regulating Specific Biological Pathways in Mouse Frontal Cortex and Hippocampus

Peer reviewe

Gait Characterization in Duchenne Muscular Dystrophy (DMD) Using a Single-Sensor Accelerometer: Classical Machine Learning and Deep Learning Approaches

Differences in gait patterns of children with Duchenne muscular dystrophy (DMD) and typically-developing (TD) peers are visible to the eye, but quantifications of those differences outside of the gait laboratory have been elusive. In this work, we measured vertical, mediolateral, and anteroposterior acceleration using a waist-worn iPhone accelerometer during ambulation across a typical range of velocities. Fifteen TD and fifteen DMD children from 3-16 years of age underwent eight walking/running activities, including five 25 meters walk/run speed-calibration tests at a slow walk to running speeds (SC-L1 to SC-L5), a 6-minute walk test (6MWT), a 100 meters fast-walk/jog/run (100MRW), and a free walk (FW). For clinical anchoring purposes, participants completed a Northstar Ambulatory Assessment (NSAA). We extracted temporospatial gait clinical features (CFs) and applied multiple machine learning (ML) approaches to differentiate between DMD and TD children using extracted temporospatial gait CFs and raw data. Extracted temporospatial gait CFs showed reduced step length and a greater mediolateral component of total power (TP) consistent with shorter strides and Trendelenberg-like gait commonly observed in DMD. ML approaches using temporospatial gait CFs and raw data varied in effectiveness at differentiating between DMD and TD controls at different speeds, with an accuracy of up to 100%. We demonstrate that by using ML with accelerometer data from a consumer-grade smartphone, we can capture DMD-associated gait characteristics in toddlers to teens

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 (P-4) 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 P-4 concentration, whereas orchectomized and adrenalectomized (ORX + ADX) resulted in a significant decrease in serum P-4 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.Peer reviewe

Segmentation of DNA into Coding and Noncoding Regions Based on Recursive Entropic Segmentation and Stop-Codon Statistics

Heterogeneous DNA sequences can be partitioned into homogeneous domains that are comprised of the four nucleotides A, C, G, and T and the stop-codons. Recursively, we apply a new entropic segmentation method on DNA sequences using Jensen-Shannon and Jensen-Rényi divergences in order to find the borders between coding and noncoding DNA regions. We have chosen 12- and 18-symbol alphabets that capture (i) the differential nucleotide composition in codons, and (ii) the differential stop-codon composition along all the three phases in both strands of the DNA. The new segmentation method is based on the Jensen-Rényi divergence measure, nucleotide statistics, and stop-codon statistics in both DNA strands. The recursive segmentation process requires no prior training on known datasets. Consequently, for three entire genomes of bacteria, we find that the use of nucleotide composition, stop-codon composition, and Jensen-Rényi divergence improve the accuracy of finding the borders between coding and noncoding regions in DNA sequences

Novel fusion genes in U87MG glioblastoma-astrocytoma cell line

<p>Novel fusion genes in U87MG (or U87) glioblastoma-astrocytoma cell line found using using FusionCatcher and RNA-seq data. Novel fusion genes TAF5L-C1ORF95, PPP1R13L-ZNF541 found in U87 cell lines.</p> <p> </p

Novel FGFR2 fusion genes in SNU-16 gastric cancer cell line

<p>Fusion genes in SNU-16 gastric cancer cell line found using using FusionCatcher and RNA-seq data. The novel FGFR2 fusion genes (i.e.FGFR2-PPAPDC1A, FGFR2-MYC, FGFR2-MUC, FGFR2-PDHX, CD44-FGFR2) were found in SNU-16 cell line. Other novel fusion genes found are: PVT1-SLC1A2, CMIP-DYNLRB2, CD44-PDHX, PVT1-MYC, and CD44-SLC1A2.</p