Browse
Submit Data
Databases
API
Help

Dataset Information

0 Views

0 Connections

0 Citations

0 Reanalyses

0 Downloads

Omics score: 0

Prostate Cancer (PRC) training cohort for small RNA characterization

ABSTRACT: Prostate Cancer (PRC) training cohort for small RNA characterization

PROVIDER: PRJEB38300 | ENA |

REPOSITORIES: ENA

ACCESS DATA

Json Xml

Dataset's files

Source:

			Action	DRS
	ERR4143820.fastq.gz	Fastqsanger.gz
	ERR4143830.fastq.gz	Fastqsanger.gz
	ERR4143840.fastq.gz	Fastqsanger.gz
	ERR4143850.fastq.gz	Fastqsanger.gz
	ERR4143821.fastq.gz	Fastqsanger.gz

Items per page:

1 - 5 of 41

Similar Datasets

Prostate Cancer (PRC) training cohort for small RNA characterization

Project description:RNA sequencing study on prostate cancer (PRC) cohort for small RNA characterization across biofluids, tissue types and isolation techniques.

2022-06-01 | E-MTAB-8529 | biostudies-arrayexpress

Urine miRNA transcriptome of prostate cancer patients [Training cohort]

Project description:Intra-individual stability of the urine miRNA transcriptome was examined by investigating longitudinal changes over time in a cohort of patients with localized prostate cancer. Using training and validation cohorts, urinary miRNA biomarkers are characterized and validated their utility to identify aggressive prostate cancer.

2019-10-24 | GSE104429 | GEO

Urine miRNA transcriptome of prostate cancer patients [Training cohort]

Project description:Urine miRNA transcriptome of prostate cancer patients [Training cohort]

| PRJNA412693 | ENA

Urine miRNA transcriptome of prostate cancer patients [Validation cohort]

2019-10-24 | GSE104430 | GEO

Urine miRNA transcriptome of prostate cancer patients [Discovery cohort]

2019-10-24 | GSE104431 | GEO

Detection of mutant NPM1 mRNA in acute myeloid leukemia (AML) using custom gene expression arrays [Training cohort]

Project description:Abstract Mutations in the gene encoding nucleophosmin (NPM1) carry prognostic value for patients with acute myeloid leukemia (AML). Various techniques are currently being used to detect these mutations in routine molecular diagnostics. Incorporation of accurate NPM1 mutation detection on a gene expression platform would enable simultaneous detection with various other expression biomarkers. Here we present an array based mutation detection using custom probes for NPM1 WT mRNA and NPM1 type A, B, and D mutant mRNA. This method was 100% accurate on a training cohort of 505 newly diagnosed unselected AML cases. Validation on an independent cohort of 143 normal karyotype AML cases revealed no false negative results, and one false positive (sensitivity 100.0%, and specificity 98.7%). Based on this, we conclude that this method provides a reliable method for NPM1 mutation detection. The method can be applied to other genes/mutations as long as the mutant alleles are sufficiently high expressed. Training cohort of 505 AML cases analyzed using the AMLprofiler

2013-01-01 | E-GEOD-42194 | biostudies-arrayexpress

Proteomic characterization of Prostate cancer cell lines

Project description:Proteomic characterization of prostate cancer cell lines after drug treatment.

2022-10-13 | PXD029525 | Pride

Training and validation of a novel 4-miRNA ratio model (MiCaP) for prediction of post-operative outcome in prostate cancer patients

Project description:Background: New molecular biomarkers for prostate cancer (PC) prognosis are urgently needed. Ratio-based models are attractive, as they require no additional normalization. Here, we train and independently validate a novel 4-miRNA prognostic ratio model for PC. Patients and methods: By genome-wide miRNA expression profiling of PC tissue samples from 123 men who underwent radical prostatectomy (RP) (PCA123, training cohort), we identified six top candidate prognostic miRNAs and systematically tested their ability to predict post-operative biochemical recurrence (BCR). The best miRNA-based prognostic ratio model (MiCaP) was validated in two independent cohorts (PCA352 and PCA476) including >800 RP patients in total. Clinical endpoints were BCR and prostate cancer-specific survival (CSS). The prognostic potential of MiCaP was assessed by univariate and multivariate Cox-regression analyses and Kaplan-Meier analyses. Results: We identified a 4-miRNA ratio model, MiCaP (miR-23a-3p×miR-10b-5p)/(miR-133a×miR-374b-5p), that predicted time to BCR independently of routine clinicopathological variables in the training cohort (PCA123) and was successfully validated in two independent RP cohorts. In addition, MiCaP was a significant predictor of CSS in univariate analysis (HR 3·35 [95% CI 1·34 – 8·35], P=0·0096) and in multivariate analysis (HR 2·43 [95% CI 1·45 – 4·07], P=0·0210). Limitations include low mortality rates (CSS: 5.4%). Conclusions: We identified a novel 4-miRNA ratio model (MiCaP) with significant independent prognostic value in three RP cohorts, indicating promising potential to improve PC risk stratification.

2018-08-14 | GSE115402 | GEO

Urine miRNA transcriptome of prostate cancer patients [Validation cohort]

Project description:Urine miRNA transcriptome of prostate cancer patients [Validation cohort]

| PRJNA412692 | ENA

Urine miRNA transcriptome of prostate cancer patients [Discovery cohort]

Project description:Urine miRNA transcriptome of prostate cancer patients [Discovery cohort]

| PRJNA412691 | ENA