Browse
Submit Data
Databases
API
Help

Dataset Information

0 Views

0 Connections

0 Citations

0 Reanalyses

0 Downloads

Omics score: 0

Imaging Studies of Local Responses of Prostate Cancer to Radiation Therapy

ABSTRACT: Patients receiving radiation therapy for prostate cancer received a multiparametric MRI and MRI/ultrasound-fusion targeted biopsy. Patients received a second mpMRI six months after radiation therapy. The goal of this study was to generate gene expression profiles of prostate cancer tumor tissue prior to treatment, and compare the gene expression profiles of those patients based on imaging response or time to biochemical recurrence.

ORGANISM(S): Homo sapiens

PROVIDER: GSE129274 | GEO | 2025/08/25

REPOSITORIES: GEO

ACCESS DATA

Json Xml

Dataset's files

Source:

			Action	DRS
		Other

Items per page:

1 - 1 of 1

Similar Datasets

Association of Multiparametric MRI Quantitative Imaging Features with Prostate Cancer Gene Expression in MRI-targeted Prostate Biopsies

Project description:Standard clinicopathological variables are inadequate for optimal management of prostate cancer patients. While genomic classifiers have improved patient risk classification, the multifocality and heterogeneity of prostate cancer can confound pre-treatment assessment. The objective is to investigate the association of multiparametric (mp)MRI quantitative features with prostate cancer risk gene expression profiles in mpMRI-guided biopsies tissues.

2016-06-07 | GSE80683 | GEO

RNA sequencing of prostate cancers reveal insights on the prognostic significance of visibility on multi-parametric MRI

Project description:Not all prostate cancers are visible on multiparametric MRI. The biologic basis and clinical implication of MRI visibility are unknown. We sought to identify genes associated with prognosis and MRI visibility.

2018-02-22 | GSE95369 | GEO

Imaging Studies of Local Responses of Prostate Cancer to Radiation Therapy

Project description:Imaging Studies of Local Responses of Prostate Cancer to Radiation Therapy

| PRJNA530751 | ENA

Imaging Studies of Local Responses of Prostate Cancer to Radiation Therapy

Project description:Imaging Studies of Local Responses of Prostate Cancer to Radiation Therapy

| PRJNA540876 | ENA

Imaging Studies of Local Responses of Prostate Cancer to Radiation Therapy

Project description:Imaging Studies of Local Responses of Prostate Cancer to Radiation Therapy

| PRJNA540877 | ENA

Prostate cancer multiparametric magnetic resonance imaging visibility is a tumor-intrinsic phenomena

Project description:Proteomics analysis of matched tumor and normal adjacent tumor regions of 40 patients with multiparametric magnetic resonance imaging (mpMRI) visible or invisible tumors. All patients have clinically significant intermediate-risk (pathological ISUP Grade Group 2), localized prostate cancer.

2021-08-18 | MSV000088000 | MassIVE

Homo sapiens

Project description:Association of Multiparametric MRI Quantitative Imaging Features with Prostate Cancer Gene Expression in MRI-targeted Prostate Biopsies

| PRJNA324676 | ENA

Assessing Radiation Therapy induced changes in Androgen Receptor Pathway activity using hK2-targeted PET imaging

Project description:To investigate the effects of external beam radiation therapy on androgen receptor pathway transcriptomic expression in prostate cancer, we performed RNAseq on EBRT-treated LNCAP xenograft tumors.

2022-06-27 | GSE206847 | GEO

Prediction of response to bevacizumab

Project description:The patients who underwent surgery for primary lesions were examined. All patients had metastatic or recurrent CRC and received bevacizumab therapy as first line or second line treatment. Responders and nonresponders were determined based on RECIST and confirmed by CT or MRI. Gene-expression profiles of primary CRC were determined using Human Genome GeneChip arrays U133.

2013-01-03 | GSE19862 | GEO

Radiomic subtyping improves disease stratification beyond key molecular, clinical and standard imaging characteristics in patients with glioblastoma.

Project description:Background: To analyze the potential of radiomics for disease stratification beyond key molecular, clinical and standard imaging features in patients with glioblastoma. Methods: Quantitative imaging features (n=1043) were extracted from the multiparametric MRI of 181 patients with newly-diagnosed glioblastoma prior to standard-of-care treatment (allocated to a discovery and validation set, 2:1 ratio). A subset of 386/1043 features were identified as reproducible (in an independent MRI-test-retest cohort) and selected for analysis. A penalized Cox-model with 10-fold cross-validation (Coxnet) was fitted on the discovery set to construct a radiomic signature for predicting progression-free and overall survival (PFS, OS). The incremental value of a radiomic signature beyond molecular (MGMT-promoter methylation, DNA-methylation subgroups), clinical (patients age, KPS, extent-of-resection, adjuvant treatment) and standard imaging parameters (tumor volumes) for stratifying PFS and OS was assessed with multivariate Cox-models (performance quantified with prediction error curves). Results: The radiomic signature (constructed from 8/386 features identified through Coxnet) increased the prediction accuracy for PFS and OS (in both discovery and validation set) beyond the assessed molecular, clinical and standard imaging parameters (p≤0.01). Prediction errors decreased by 36% for PFS and 37% for OS when adding the radiomic signature (as compared to 29% and 27% with molecular + clinical features alone). The radiomic signature was - along with MGMT-status - the only parameter with independent significance on multivariate analysis (p≤0.01). Conclusions: Our study stresses the role of integrating radiomics into a multi-layer decision framework with key molecular and clinical features to improve disease stratification and to potentially advance personalized treatment of patients with glioblastoma.

2018-01-05 | GSE103659 | GEO

OmicsDI is part of the ELIXIR infrastructure

OmicsDI is an Elixir interoperability service. Learn more ›

Tweets

OmicsDI Databases

PRIDE
PeptideAtlas
MassIVE
JPOST Repository
Physiome Model Repository

EGA
EVA
ENA
LINCS
PAXDB
Cell Collective

MetaboLights
Metabolomics Workbench
MetabolomeExpress
GNPS
BioModels
FAIRDOMHub

ArrayExpress
dbGaP
ExpressionAtlas
GEO
NODE

Information

Databases
Help
API
Contact us
Code on GitHub
Terms of use
Submit Data