POS-03.71: Transcript signatures of tumor-related marker genes for the prediction of prostate cancer on paired prostate tissue samples and artificial biopsies

Urology ◽  
2007 ◽  
Vol 70 (3) ◽  
pp. 295
Author(s):  
S. Unversucht ◽  
A. Lohse ◽  
M. Zenker ◽  
S. Fuessel ◽  
A. Meye ◽  
...  
Keyword(s):  
Prostate Cancer ◽  
Prostate Tissue ◽  
Marker Genes ◽  
Tissue Samples

scholarly journals Epigenetic silencing of MEIS2 in prostate cancer recurrence

2019 ◽  
Vol 11 (1) ◽  
Author(s):  
Maibritt Nørgaard ◽  
Christa Haldrup ◽  
Marianne Trier Bjerre ◽  
Søren Høyer ◽  
Benedicte Ulhøi ◽  
...  
Keyword(s):  
Prostate Cancer ◽  
Dna Methylation ◽  
Prostate Tissue ◽  
Rank Test ◽  
Transcriptional Expression ◽  
Tissue Samples ◽  
Whitney Test ◽  
Log Rank Test ◽  
Mann Whitney Test ◽  
Malignant Prostate

Abstract Background Current diagnostic and prognostic tools for prostate cancer (PC) are suboptimal, resulting in overdiagnosis and overtreatment of clinically insignificant tumors. Thus, to improve the management of PC, novel biomarkers are urgently needed. Results In this study, we integrated genome-wide methylome (Illumina 450K DNA methylation array (450K)) and RNA sequencing (RNAseq) data performed in a discovery set of 27 PC and 15 adjacent normal (AN) prostate tissue samples to identify candidate driver genes involved in PC development and/or progression. We found significant enrichment for homeobox genes among the most aberrantly methylated and transcriptionally dysregulated genes in PC. Specifically, homeobox gene MEIS2 (Myeloid Ecotropic viral Insertion Site 2) was significantly hypermethylated (p < 0.0001, Mann-Whitney test) and transcriptionally downregulated (p < 0.0001, Mann-Whitney test) in PC compared to non-malignant prostate tissue in our discovery sample set, which was also confirmed in an independent validation set including > 500 PC and AN tissue samples in total (TCGA cohort analyzed by 450K and RNAseq). Furthermore, in three independent radical prostatectomy (RP) cohorts (n > 700 patients in total), low MEIS2 transcriptional expression was significantly associated with poor biochemical recurrence (BCR) free survival (p = 0.0084, 0.0001, and 0.0191, respectively; log-rank test). Next, we analyzed another RP cohort consisting of > 200 PC, AN, and benign prostatic hyperplasia (BPH) samples by quantitative methylation-specific PCR (qMSP) and found that MEIS2 was significantly hypermethylated (p < 0.0001, Mann-Whitney test) in PC compared to non-malignant prostate tissue samples (AN and BPH) with an AUC > 0.84. Moreover, in this cohort, aberrant MEIS2 hypermethylation was significantly associated with post-operative BCR (p = 0.0068, log-rank test), which was subsequently confirmed (p = 0.0067; log-rank test) in the independent TCGA validation cohort (497 RP patients; 450K data). Conclusions To the best of our knowledge, this is the first study to investigate, demonstrate, and independently validate a prognostic biomarker potential for MEIS2 at the transcriptional expression level and at the DNA methylation level in PC.

scholarly journals No Evidence of XMRV or MuLV Sequences in Prostate Cancer, Diffuse Large B-Cell Lymphoma, or the UK Blood Donor Population

2011 ◽  
Vol 2011 ◽  
pp. 1-6 ◽  
Author(s):  
Mark James Robinson ◽  
Philip William Tuke ◽  
Otto Erlwein ◽  
Kate I. Tettmar ◽  
Steve Kaye ◽  
...  
Keyword(s):  
Prostate Cancer ◽  
B Cell ◽  
Blood Donors ◽  
Cell Lymphoma ◽  
B Cell Lymphoma ◽  
Chronic Fatigue ◽  
Prostate Tissue ◽  
Tissue Samples ◽  
Leukaemia Virus ◽  
The Uk

Xenotropic murine leukaemia virus-related virus (XMRV) is a recently described retrovirus which has been claimed to infect humans and cause associated pathology. Initially identified in the US in patients with prostate cancer and subsequently in patients with chronic fatigue syndrome, doubt now exists that XMRV is a human pathogen. We studied the prevalence of genetic sequences of XMRV and related MuLV sequences in human prostate cancer, from B cell lymphoma patients and from UK blood donors. Nucleic acid was extracted from fresh prostate tissue biopsies, formalin-fixed paraffin-embedded (FFPE) prostate tissue and FFPE B-cell lymphoma. The presence of XMRV-specific LTR or MuLV genericgag-like sequences was investigated by nested PCR. To control for mouse DNA contamination, a PCR that detected intracisternal A-type particle (IAP) sequences was included. In addition, DNA and RNA were extracted from whole blood taken from UK blood donors and screened for XMRV sequences by real-time PCR. XMRV or MuLV-like sequences were not amplified from tissue samples. Occasionally MuLVgagand XMRV-LTR sequences were amplified from Indian prostate cancer samples, but were always detected in conjunction with contaminating murine genomic DNA. We found no evidence of XMRV or MuLV infection in the UK blood donors.

scholarly journals 656: Comparative Expression Study of Selected Marker Genes on Paired Prostate Tissue Samples

2007 ◽  
Vol 177 (4S) ◽  
pp. 220-220
Author(s):  
Susanne Fuessel ◽  
Susanne Unversucht ◽  
Rainer Koch ◽  
Gustavo B. Baretton ◽  
Michael Froehner ◽  
...  
Keyword(s):  
Prostate Tissue ◽  
Marker Genes ◽  
Expression Study ◽  
Tissue Samples

The silent presence of Mycoplasma hominis in patients with prostate cancer

2020 ◽  
Vol 78 (7) ◽  
Author(s):  
Saman Saadat ◽  
Pezhman Karami ◽  
Mohammad Jafari ◽  
Mahdi Kholoujini ◽  
Zahra Rikhtegaran Tehrani ◽  
...  
Keyword(s):  
Prostate Cancer ◽  
Mycoplasma Hominis ◽  
Opportunistic Pathogen ◽  
Host Cells ◽  
Prostate Tissue ◽  
Control Group ◽  
P Value ◽  
Retrospective Case ◽  
Formalin Fixed Paraffin Embedded ◽  
Pcr Targeting

ABSTRACT Background Mycoplasma hominis, an opportunistic pathogen in human genitourinary tract, can cause chronic infection in the prostate. Intracellular survival of M. hominis leads to a prolonged presence in the host cells that can affect the cell's biological cycle. In the present study, we aimed to evaluate the frequency of M. hominis DNA in prostate tissue of Iranian patients with prostate cancer (PCa) in comparison to a control group with benign prostatic hyperplasia (BPH). Methods This research was a retrospective case-control study using 61 archived formalin-fixed paraffin-embedded (FFPE) blocks of prostate tissue from patients with PCa and 70 FFPE blocks of patients with BPH. Real-time PCR, targeting two different genes, 16S rRNA and yidC, in the M. hominis genome was performed for all specimens. Results Out of 61 blocks of prostate biopsy from patients with PCa, eight samples (13%) were positive for M. hominis, while the bacterium was not detected in any of the 70 blocks of patients with BPH (P value, 0.002). Conclusions The high frequency of M. hominis in patients with PCa likely shows a hidden role of the organism in prostate cancer during its chronic, apparently silent and asymptomatic colonization in prostate.

scholarly journals HERV-K Gag RNA and Protein Levels Are Elevated in Malignant Regions of the Prostate in Males with Prostate Cancer

Viruses ◽  
2021 ◽  
Vol 13 (3) ◽  
pp. 449
Author(s):  
Simin D. Rezaei ◽  
Joshua A. Hayward ◽  
Sam Norden ◽  
John Pedersen ◽  
John Mills ◽  
...  
Keyword(s):  
Prostate Cancer ◽  
Cell Lines ◽  
Endogenous Retrovirus ◽  
Human Endogenous Retrovirus ◽  
Normal Prostate ◽  
Tissue Samples ◽  
Gag Protein ◽  
Protein Levels ◽  
Prostate Epithelial Cells ◽  
Prostate Cancers

Heightened expression of human endogenous retrovirus (HERV) sequences has been associated with a range of malignancies, including prostate cancer, suggesting that they may serve as useful diagnostic or prognostic cancer biomarkers. We analysed the expression of HERV-K (Gag and Env/Np9 regions), HERV-E 4.1 (Pol and Env regions), HERV-H (Pol) and HERV-W (Gag) sequences in prostate cancer cells lines and normal prostate epithelial cells using qRT-PCR. HERV expression was also analysed in matched malignant and benign prostate tissue samples from men with prostate cancer (n = 27, median age 65.2 years (range 47–70)) and compared to prostate cancer-free male controls (n = 11). Prostate cancer epithelial cell lines exhibited a signature of HERV RNA overexpression, with all HERVs analysed, except HERV-E Pol, showing heightened expression in at least two, but more commonly all, cell lines analysed. Analysis of primary prostate material indicated increased expression of HERV-E Pol but decreased expression of HERV-E Env in both malignant and benign regions of the prostate in men with prostate cancer as compared to those without. Expression of HERV-K Gag was significantly higher in malignant regions of the prostate in men with prostate cancer as compared to matched benign regions and prostate cancer-free men (p < 0.001 for both), with 85.2% of prostate cancers donors showing malignancy-associated upregulation of HERV-K Gag RNA. HERV-K Gag protein was detected in 12/18 (66.7%) malignant tissues using immunohistochemistry, but only 1/18 (5.6%) benign tissue sections. Heightened expression of HERV-K Gag RNA and protein appears to be a sensitive and specific biomarker of prostate malignancy in this cohort of men with prostate carcinoma, supporting its potential utility as a non-invasive, adjunct clinical biomarker.

scholarly journals Expression profiling of RNA based markers of prostate cancer in urine and tissue samples

2012 ◽  
Vol 10 (8) ◽  
pp. S101
Author(s):  
Eva Bolton ◽  
Diarmaid Moran ◽  
Armelle Meunier ◽  
Laure Marignol ◽  
Donal Hollywood ◽  
...  
Keyword(s):  
Prostate Cancer ◽  
Expression Profiling ◽  
Tissue Samples

scholarly journals Downregulation and Prognostic Performance of MicroRNA 224 Expression in Prostate Cancer

2013 ◽  
Vol 59 (1) ◽  
pp. 261-269 ◽  
Author(s):  
Konstantinos Mavridis ◽  
Konstantinos Stravodimos ◽  
Andreas Scorilas
Keyword(s):  
Prostate Cancer ◽  
Cox Regression ◽  
Specific Antigen ◽  
Progression Free Survival ◽  
Prognostic Indicator ◽  
Disease Stage ◽  
Clinical Value ◽  
Prostate Tumors ◽  
Tissue Samples ◽  
Total Rna

INTRODUCTION The extensive use of prostate-specific antigen as a general prostate cancer biomarker has introduced the hazards of overdiagnosis and overtreatment. Recent studies have revealed the immense biomarker capacity of microRNAs (miRNAs) in prostate cancer. The aim of this study was to analyze the expression pattern of miR-224, a cancer-related miRNA, in prostate tumors and investigate its clinical utility. METHODS Total RNA was isolated from 139 prostate tissue samples. After the polyadenylation of total RNA by poly(A) polymerase, cDNA was synthesized with a suitable poly(T) adapter. miR-224 expression was assessed by quantitative real-time PCR and analyzed with the comparative quantification cycle method, Cq(2−ΔΔCq). We performed comprehensive biostatistical analyses to explore the clinical value of miR-224 in prostate cancer. RESULTS miR-224 expression was significantly downregulated in malignant samples compared with benign samples (P &lt; 0.001). Higher miR-224 expression levels were found in prostate tumors that were less aggressive (P = 0.017) and in an earlier disease stage (P = 0.018). Patients with prostate cancer who were positive for miR-224 had significantly enhanced progression-free survival intervals compared with miR-224–negative patients (P = 0.021). Univariate bootstrap Cox regression confirmed that miR-224 was associated with favorable prognosis (hazard ratio 0.314, P = 0.013); nonetheless, multivariate analysis, adjusted for conventional markers, did not identify miR-224 as an independent prognostic indicator. CONCLUSIONS miR-224 is aberrantly expressed in prostate cancer. Its assessment by cost-effective quantitative molecular methodologies could provide a useful biomarker for prostate cancer.

scholarly journals Identification of cell-type-specific marker genes from co-expression patterns in tissue samples

2021 ◽  
Author(s):  
Yixuan Qiu ◽  
Jiebiao Wang ◽  
Jing Lei ◽  
Kathryn Roeder
Keyword(s):  
Single Cell ◽  
Expression Patterns ◽  
R Package ◽  
Supplementary Information ◽  
Marker Genes ◽  
Specific Marker ◽  
Cell Type ◽  
Correlation Pattern ◽  
Tissue Samples ◽  
Bulk Data

Abstract Motivation Marker genes, defined as genes that are expressed primarily in a single cell type, can be identified from the single cell transcriptome; however, such data are not always available for the many uses of marker genes, such as deconvolution of bulk tissue. Marker genes for a cell type, however, are highly correlated in bulk data, because their expression levels depend primarily on the proportion of that cell type in the samples. Therefore, when many tissue samples are analyzed, it is possible to identify these marker genes from the correlation pattern. Results To capitalize on this pattern, we develop a new algorithm to detect marker genes by combining published information about likely marker genes with bulk transcriptome data in the form of a semi-supervised algorithm. The algorithm then exploits the correlation structure of the bulk data to refine the published marker genes by adding or removing genes from the list. Availability and implementation We implement this method as an R package markerpen, hosted on CRAN (https://CRAN.R-project.org/package=markerpen). Supplementary information Supplementary data are available at Bioinformatics online.

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