A signature of miRNAs in the blood to help prognosticate prostate cancer at the time of diagnosis.

2017 ◽  
Vol 35 (15_suppl) ◽  
pp. e16558-e16558
Author(s):  
Ailsa Roberg Sita-Lumsden ◽  
Damien Leach ◽  
Andrea Zivi ◽  
Mathias Winkler ◽  
Jonathan Waxman ◽  
...  
Keyword(s):  
Prostate Cancer ◽  
Survival Rates ◽  
Benign Prostatic Hypertrophy ◽  
Serum Levels ◽  
The Cancer Genome Atlas ◽  
Circulating Mirnas ◽  
P Values ◽  
Circulating Micrornas ◽  
Cancer Genome Atlas ◽  
Clinically Significant

e16558 Background: Prostate cancer (PCa) is the most commonly diagnosed cancer in men. Around 80% of PCas are diagnosed as early, localised stage yet a subset of these will metastasise and eventually prove fatal. Management decisions are based on risk stratification systems. However, these systems are not able to clearly distinguish indolent from aggressive PCa’s and as a result many patients with indolent cancers may be over treated. Circulating microRNAs (miRNA) may be an easily accessible, suitable biomarker to distinguish true indolent from clinically significant early PCas thus reducing overtreatments. Methods: Blood samples from 24 men with benign prostatic hypertrophy (BPH, n = 8), localised PCa (n = 8) or metastatic PCa (n = 8) were collected at time of diagnosis. All men had intact prostates and were naïve to any endocrine or other cancer therapy. A platform of circulating miRNAs were analysed in serum using Abcam FireflyTM technology. Data collected were independently verified using real-time qPCR (Exiqon TM ). The miRNAs identified as being significantly different between groups were then analysed in a published dataset. Results: Serum levels of seven of the miRs examined were significantly different in patients with prostate cancer compared to control across both platforms (miR-10b, miR-125b, miR-210, miR-21, miR-378a, miR-483 and miR93 all with P values < 0.005). A further four miRNAs could differentiate between the benign and metastatic cohorts (miR-126 P = 0.008, miR-150 P = 0.05, miR375 P = 0.007). Kaplein-Meier analysis further identified that the serum levels of four miRNAs showed significant association with survival rates (miR-21 P = 0.032, miR-126 P = 0.032, miR-150 P = 0.032, miR-93 P = 0.019). On examination in a cohort of 280 men from The Cancer Genome Atlas (TCGA), four miRs from the cohort had significantly different expression in patients who eventually relapsed (miR-21 P = 0.048, miR-375 P = 0.021, miR-210 P = 0.0003, miR-93 P = 0.008) Conclusions: Our circulating miRNA based signature could be used to stratify men at prostate cancer diagnosis and help identify those who are likely to harbour micro metastases and would benefit more from an early radical treatment. The data is being validated in larger cohorts.

A circulating miRNA signature to help prognosticate at prostate cancer diagnosis.

2017 ◽  
Vol 35 (6_suppl) ◽  
pp. 108-108 ◽  
Author(s):  
Ailsa Roberg Sita-Lumsden ◽  
Damien Leach ◽  
Andrea Zivi ◽  
Jonathan Waxman ◽  
Mathias Winkler ◽  
...  
Keyword(s):  
Prostate Cancer ◽  
Cancer Diagnosis ◽  
Survival Rates ◽  
Benign Prostatic Hypertrophy ◽  
Serum Levels ◽  
The Cancer Genome Atlas ◽  
Prostate Cancer Diagnosis ◽  
Circulating Mirna ◽  
Clinically Significant ◽  
Prostate Cancers

108 Background: Prostate cancer (PCa) is the most commonly diagnosed cancer in men. Around 80% of PCas are diagnosed as early, localised stage yet a subset of these will metastasise and eventually prove fatal. Management decisions are based on risk stratification systems. However, these systems are not able to clearly distinguish indolent from aggressive PCa’s and as a result many patients with indolent cancers may be over treated. Circulating microRNAs (miRNA) may be an easily accessible, suitable biomarker to distinguish true indolent from clinically significant early prostate cancers (PCa) thus reducing overtreatments. Methods: Blood samples from 24 men with benign prostatic hypertrophy (BPH, n = 8), localised PCa (n = 8) or metastatic PCa (n = 8) were collected at time of diagnosis. All men had intact prostates and were naïve to any endocrine or other cancer therapy. A platform of circulating miRNAs were analysed in serum using Abcam Firefly technology. Data collected were independently verified using real-time qPCR (Exiqon). The miRNAs identified as being significantly different between groups were then analysed in a published dataset. Results: Serum levels of seven of the miRs examined were significantly different in patients with prostate cancer compared to control across both platforms (miR-10b, miR-125b, miR-210, miR-21, miR-378a, miR-483 and miR93 all with P values < 0.005). A further four miRNAs could differentiate between the benign and metastatic cohorts (miR-126 P = 0.008, miR-150 P = 0.05, miR375 P = 0.007). Kaplein-Meier analysis further identified that the serum levels of four miRNAs showed significant association with survival rates (miR-21 P = 0.032, miR-126 P = 0.032, miR-150 P = 0.032, miR-93 P = 0.019). On examination in a cohort of 280 men from The Cancer Genome Atlas (TCGA), four miRs from the cohort had significantly different expression in patients who eventually relapsed (miR-21 P = 0.048, miR-375 P = 0.021, miR-210 P = 0.0003, miR-93 P = 0.008) Conclusions: Our circulating miRNA based signature could be used to stratify men at prostate cancer diagnosis and help identify those who are likely to harbour micro metastases and would benefit more from an early radical treatment. The data is being validated in larger cohorts.

scholarly journals Promoter Methylation of PRKCB, ADAMTS12, and NAALAD2 Is Specific to Prostate Cancer and Predicts Biochemical Disease Recurrence

2021 ◽  
Vol 22 (11) ◽  
pp. 6091
Author(s):  
Kristina Daniunaite ◽  
Arnas Bakavicius ◽  
Kristina Zukauskaite ◽  
Ieva Rauluseviciute ◽  
Juozas Rimantas Lazutka ◽  
...  
Keyword(s):  
Prostate Cancer ◽  
Clinical Practice ◽  
Promoter Methylation ◽  
Disease Recurrence ◽  
The Cancer Genome Atlas ◽  
Cancer Dataset ◽  
Protein Coding ◽  
Diagnosis And Prognosis ◽  
Genome Wide ◽  
Cancer Genome Atlas

The molecular diversity of prostate cancer (PCa) has been demonstrated by recent genome-wide studies, proposing a significant number of different molecular markers. However, only a few of them have been transferred into clinical practice so far. The present study aimed to identify and validate novel DNA methylation biomarkers for PCa diagnosis and prognosis. Microarray-based methylome data of well-characterized cancerous and noncancerous prostate tissue (NPT) pairs was used for the initial screening. Ten protein-coding genes were selected for validation in a set of 151 PCa, 51 NPT, as well as 17 benign prostatic hyperplasia samples. The Prostate Cancer Dataset (PRAD) of The Cancer Genome Atlas (TCGA) was utilized for independent validation of our findings. Methylation frequencies of ADAMTS12, CCDC181, FILIP1L, NAALAD2, PRKCB, and ZMIZ1 were up to 91% in our study. PCa specific methylation of ADAMTS12, CCDC181, NAALAD2, and PRKCB was demonstrated by qualitative and quantitative means (all p < 0.05). In agreement with PRAD, promoter methylation of these four genes was associated with the transcript down-regulation in the Lithuanian cohort (all p < 0.05). Methylation of ADAMTS12, NAALAD2, and PRKCB was independently predictive for biochemical disease recurrence, while NAALAD2 and PRKCB increased the prognostic power of multivariate models (all p < 0.01). The present study identified methylation of ADAMTS12, NAALAD2, and PRKCB as novel diagnostic and prognostic PCa biomarkers that might guide treatment decisions in clinical practice.

scholarly journals Can mean ADC value and ADC ratio of benign prostate tissue to prostate cancer assist in the prediction of clinically significant prostate cancer within the PI-RADSv2 scoring system?

2020 ◽  
Vol 51 (1) ◽  
Author(s):  
Samar Ramzy Ragheb ◽  
Reem Hassan Bassiouny
Keyword(s):  
Prostate Cancer ◽  
Sensitivity And Specificity ◽  
Gleason Score ◽  
Treatment Strategies ◽  
Serum Levels ◽  
Prostatic Tissue ◽  
Histopathological Analysis ◽  
Adc Value ◽  
The Mean ◽  
Clinically Significant

Abstract Background The aim of this study is to investigate whether quantitative DW metrics can provide additive value to the reliable categorization of lesions within existing PI-RADSv2 guidelines. Fifty-eight patients with clinically suspicious prostate cancer who underwent PR examination, PSA serum levels, sextant TRUS-guided biopsies, and bi-parametric MR imaging were included in the study. Results Sixty-six lesions were detected by histopathological analysis of surgical specimens. The mean ADC values were significantly lower in tumor than non-tumor tissue. The mean ADC value inversely correlated with Gleason score of tumors with a significant p value < 0.001.Conversely, a positive relationship was found between the ADC ratio (ADC of benign prostatic tissue to prostate cancer) and the pathologic Gleason score with a significant elevation of the ADC ratio along with an increase of the pathologic Gleason score (p < 0.001). ROC curves constructed for the tumor ADC and ADC ratio helped to distinguish pathologically aggressive (Gleason score ≥ 7) from non-aggressive (Gleason score ≤ 6) tumors and to correlate it with PIRADSv2 scoring to predict the presence of clinically significant PCA (PIRADSv2 DW ≥ 4). The ability of the tumor ADC and ADC ratio to predict highly aggressive tumors (GS> 7) was high (AUC for ADC and ADC ratio, 0.946 and 0.897; p = 0.014 and 0.039, respectively). The ADC cut-off value for GS ≥ 7 was < 0.7725 and for GS ≤ 6 was > 0.8620 with sensitivity and specificity 97 and 94%. The cutoff ADC ratio for predicting (GS > 7) was 1.42 and for GS ≤ 6 was > 1.320 with sensitivity and specificity 97 and 92%. By applying this ADC ratio cut-off value the sensitivity and specificity of reader 1 for correct categorization of PIRADSv2 DW > 4 increased from 90 and 68% to 95 and 90% and that of reader 2 increased from 94 and 88% to 97 and 92%, respectively. Conclusion Estimation of DW metrics (ADC and ADC ratio between benign prostatic tissue and prostate cancer) allow the non-invasive assessment of biological aggressiveness of prostate cancer and allow reliable application of the PIRADSv2 scoring to determine clinically significant cancer (DW score > 4) which may contribute in planning initial treatment strategies.

scholarly journals Interfocal heterogeneity challenges the clinical usefulness of molecular classification of primary prostate cancer

2019 ◽  
Vol 9 (1) ◽  
Author(s):  
Kristina Totland Carm ◽  
Andreas M. Hoff ◽  
Anne Cathrine Bakken ◽  
Ulrika Axcrona ◽  
Karol Axcrona ◽  
...  
Keyword(s):  
Prostate Cancer ◽  
Molecular Classification ◽  
Primary Diagnosis ◽  
The Cancer Genome Atlas ◽  
Clinical Usefulness ◽  
Whole Exome ◽  
Primary Prostate Cancer ◽  
Cancer Genome Atlas ◽  
Prostate Cancers

Abstract Prostate cancer is a highly heterogeneous disease and typically multiple distinct cancer foci are present at primary diagnosis. Molecular classification of prostate cancer can potentially aid the precision of diagnosis and treatment. A promising genomic classifier was published by The Cancer Genome Atlas (TCGA), successfully classifying 74% of primary prostate cancers into seven groups based on one cancer sample per patient. Here, we explore the clinical usefulness of this classification by testing the classifier’s performance in a multifocal context. We analyzed 106 cancer samples from 85 distinct cancer foci within 39 patients. By somatic mutation data from whole-exome sequencing and targeted qualitative and quantitative gene expression assays, 31% of the patients were uniquely classified into one of the seven TCGA classes. Further, different samples from the same focus had conflicting classification in 12% of the foci. In conclusion, the level of both intra- and interfocal heterogeneity is extensive and must be taken into consideration in the development of clinically useful molecular classification of primary prostate cancer.

scholarly journals Identification of a Ubiquitin Related Genes Signature for Predicting Prognosis of Prostate Cancer

2022 ◽  
Vol 12 ◽  
Author(s):  
Guoda Song ◽  
Yucong Zhang ◽  
Hao Li ◽  
Zhuo Liu ◽  
Wen Song ◽  
...  
Keyword(s):  
Prostate Cancer ◽  
Roc Curve ◽  
Cox Regression ◽  
R Package ◽  
The Cancer Genome Atlas ◽  
Prognostic Signature ◽  
Post Translational Modifications ◽  
Training Cohort ◽  
Kaplan Meier ◽  
Cancer Genome Atlas

Background: Ubiquitin and ubiquitin-like (UB/UBL) conjugations are one of the most important post-translational modifications and involve in the occurrence of cancers. However, the biological function and clinical significance of ubiquitin related genes (URGs) in prostate cancer (PCa) are still unclear.Methods: The transcriptome data and clinicopathological data were downloaded from The Cancer Genome Atlas (TCGA), which was served as training cohort. The GSE21034 dataset was used to validate. The two datasets were removed batch effects and normalized using the “sva” R package. Univariate Cox, LASSO Cox, and multivariate Cox regression were performed to identify a URGs prognostic signature. Then Kaplan-Meier curve and receiver operating characteristic (ROC) curve analyses were used to evaluate the performance of the URGs signature. Thereafter, a nomogram was constructed and evaluated.Results: A six-URGs signature was established to predict biochemical recurrence (BCR) of PCa, which included ARIH2, FBXO6, GNB4, HECW2, LZTR1 and RNF185. Kaplan-Meier curve and ROC curve analyses revealed good performance of the prognostic signature in both training cohort and validation cohort. Univariate and multivariate Cox analyses showed the signature was an independent prognostic factor for BCR of PCa in training cohort. Then a nomogram based on the URGs signature and clinicopathological factors was established and showed an accurate prediction for prognosis in PCa.Conclusion: Our study established a URGs prognostic signature and constructed a nomogram to predict the BCR of PCa. This study could help with individualized treatment and identify PCa patients with high BCR risks.

scholarly journals A risk prediction model of DNA methylation improves prognosis evaluation and indicates gene targets in prostate cancer

Epigenomics ◽  
2020 ◽  
Vol 12 (4) ◽  
pp. 333-352 ◽  
Author(s):  
Enchong Zhang ◽  
Xueying Hou ◽  
Baoxian Hou ◽  
Mo Zhang ◽  
Yongsheng Song
Keyword(s):  
Prostate Cancer ◽  
Dna Methylation ◽  
Training Group ◽  
The Cancer Genome Atlas ◽  
Cell Counting ◽  
Migration And Invasion ◽  
Transwell Invasion Assay ◽  
Cancer Genome Atlas ◽  
Selection Operator ◽  
Therapy Target

Aim: Prostate cancer (PCa) is the most common malignancy found in males worldwide. Although it is mostly indolent, PCa still poses a serious threat to long-term health. Materials & methods: The Cancer Genome Atlas data were randomly divided into training and validation groups. Least absolute shrinkage and selection operator regression on DNA methylation data in the training group was conducted to build the model, which was validated in the validation group. Weighted correlation network analysis was conducted on RNA-seq data to identify the therapy target. Functional validation (western blot, quantitative real-time PCR, cell transfection, Cell Counting Kit-8 assay, colony formation assay, wound healing assay and transwell invasion assay) for the target was conducted. Results: The model is an independent predictor of prognosis. The knockdown of FOXD1 inhibits cell proliferation, migration and invasion of PCa. Conclusion: The risk of patients could be evaluated by the model, which revealed that FOXD1 might promote poor prognosis.

scholarly journals MTA2 as a Potential Biomarker and Its Involvement in Metastatic Progression of Human Renal Cancer by miR-133b Targeting MMP-9

Cancers ◽  
2019 ◽  
Vol 11 (12) ◽  
pp. 1851 ◽  
Author(s):  
Yong-Syuan Chen ◽  
Tung-Wei Hung ◽  
Shih-Chi Su ◽  
Chia-Liang Lin ◽  
Shun-Fa Yang ◽  
...  
Keyword(s):  
Molecular Mechanisms ◽  
Survival Rates ◽  
The Cancer Genome Atlas ◽  
Metastatic Progression ◽  
Tumour Grade ◽  
Potential Biomarker ◽  
Cancer Genome Atlas ◽  
Metalloproteinase 9

Metastasis-associated protein 2 (MTA2) was previously known as a requirement to maintain malignant potentials in several human cancers. However, the role of MTA2 in the progression of renal cell carcinoma (RCC) has not yet been delineated. In this study, MTA2 expression was significantly increased in RCC tissues and cell lines. Increased MTA2 expression was significantly associated with tumour grade (p = 0.002) and was an independent prognostic factor for overall survival with a high RCC tumour grade. MTA2 knockdown inhibited the migration, invasion, and in vivo metastasis of RCC cells without effects on cell proliferation. Regarding molecular mechanisms, MTA2 knockdown reduced the activity, protein level, and mRNA expression of matrix metalloproteinase-9 (MMP-9) in RCC cells. Further analyses demonstrated that patients with lower miR-133b expression had poorer survival rates than those with higher expression from The Cancer Genome Atlas database. Moreover, miR-133b modulated the 3′untranslated region (UTR) of MMP-9 promoter activities and subsequently the migratory and invasive abilities of these dysregulated expressions of MTA2 in RCC cells. The inhibition of MTA2 could contribute to human RCC metastasis by regulating the expression of miR-133b targeting MMP-9 expression.

scholarly journals MicroRNA-Related Prognosis Biomarkers from High-Throughput Sequencing Data of Colorectal Cancer

2020 ◽  
Vol 2020 ◽  
pp. 1-12
Author(s):  
Xiao-Liang Xing ◽  
Zhi-Yong Yao ◽  
Ti Zhang ◽  
Ning Zhu ◽  
Yuan-Wu Liu ◽  
...  
Keyword(s):  
Colorectal Cancer ◽  
Differential Expression ◽  
High Throughput Sequencing ◽  
Survival Rates ◽  
Colon Adenocarcinoma ◽  
The Cancer Genome Atlas ◽  
Sequencing Data ◽  
High Throughput Sequencing Data ◽  
Differential Expression Genes ◽  
Cancer Genome Atlas

Background. Colorectal cancer (CRC) is the third most common cancer in the world, and most of them are adenocarcinomas. CRC could be classified as colon adenocarcinoma (COAD) and rectum adenocarcinoma (READ) according to the original tumorigenesis position. Increasing evidences indicated that microRNAs (miRNAs) play an important role in the occurrence of multiple tumors. Methods. In this study, we firstly downloaded miRNA (COAD, 8 controls vs. 455 tumors; READ, 3 controls vs. 161 tumors) and mRNA (COAD, 41 controls vs. 478 tumors; READ, 10 controls vs. 166 tumors) data from The Cancer Genome Atlas (TCGA) database and then used DESeq2, RegParallel, miRDB, TargetScanHuman 7.2, DAVID 6.8, STRING, and Cytoscape software to identify the potential prognosis biomarkers. Results. We identified 175 differential expression miRNAs (DEMs) and 3747 differential expression genes (DEGs) in COAD and 184 DEMs and 3928 DEGs in READ. And then, we obtained 21 (13 in COAD and 8 in READ) DEMs associated with the survival rates, which correlated with 440 (217 in COAD and 223 in READ) overlapping DEGs. Through survival analysis for those overlapping DEGs, we found 11 (8 in COAD and 3 in READ) overlapping DGEs associated with survival rates of patients, which were correlated with 9 (7 in COAD and 2 in READ) DEMs significantly. Conclusion. In this study, we found several candidate prognostic biomarkers which have been identified in various cancers and also found several new prognosis biomarkers of COAD and READ. In conclusion, this analysis based on theoretical knowledge and clinical outcomes we have done needs further confirmation by more researches.

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