refine.bio
  • Search
      • Normalized Compendia
      • RNA-seq Sample Compendia
  • Docs
  • About
  • My Dataset
github link
Showing
of 97 results
Sort by

Filters

Technology

Platform

accession-icon GSE93338
Feasibility of Developing Reliable Gene Expression Modules from FFPE Derived RNA Profiled on Affymetrix Arrays
  • organism-icon Homo sapiens
  • sample-icon 38 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)

Description

This SuperSeries is composed of the SubSeries listed below.

Publication Title

Feasibility of developing reliable gene expression modules from FFPE derived RNA profiled on Affymetrix arrays.

Sample Metadata Fields

Specimen part

View Samples
accession-icon GSE93334
FFPE samples profiled on HG-U133plus2 array with Affymetrix's GeneChip 3' IVT Express kit
  • organism-icon Homo sapiens
  • sample-icon 6 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)

Description

The reliability of differential expression analysis on FFPE expression profiles from Affymetrix arrays is questionable, due to the wide range of percent-present values reported in studies which profiled FFPE samples on Affymetrix arrays. Moreover the validity of externally defined gene-modules in FFPE microarray expression profiles is unknown. Using eight breast cancer tumors with available frozen and FFPE samples, five sample-matched data sets were generated from different combination of Affymetrix arrays, amplification-and-labeling kit and sample preservation method. The reliability of differential expression analysis was investigated by developing de novo ER/HER2 pathway gene-modules from matched data sets and validating it on external data set using ROC analysis. Spearman's rank correlation coefficient of module scores between matched FFPE-frozen expression profiles was used to measure reliability of externally defined gene-modules in FFPE expression profiles. Independent of array/amplification-kit/sample preservation method used, de novo ER/HER2 gene-modules derived from all matching data sets showed similar prediction performance during independent validation (AUC range; ER: 0.92-0.95, HER2: 0.88-0.91), except for de novo HER2 gene-module derived from FFPE data set with 3'IVT kit (AUC: 0.67-0.72). Further not all gene-module based biological signals present in frozen expression profiles can be recovered from matching FFPE microarray expression profiles using the currently available FFPE specific sample preparation kits. The gene-module based biological signal extracted from FFPE RNA, using microarrays, may not be as reliable as that from their frozen counterpart, if the sample preparation protocol used with FFPE RNA failed to recover relevant genes involved in the biological signal.

Publication Title

Feasibility of developing reliable gene expression modules from FFPE derived RNA profiled on Affymetrix arrays.

Sample Metadata Fields

Specimen part

View Samples
accession-icon GSE93332
Fresh-Frozen samples profiled on HG-U133plus2 array with Affymetrix's GeneChip 3' IVT Express kit
  • organism-icon Homo sapiens
  • sample-icon 8 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)

Description

The reliability of differential expression analysis on FFPE expression profiles from Affymetrix arrays is questionable, due to the wide range of percent-present values reported in studies which profiled FFPE samples on Affymetrix arrays. Moreover the validity of externally defined gene-modules in FFPE microarray expression profiles is unknown. Using eight breast cancer tumors with available frozen and FFPE samples, five sample-matched data sets were generated from different combination of Affymetrix arrays, amplification-and-labeling kit and sample preservation method. The reliability of differential expression analysis was investigated by developing de novo ER/HER2 pathway gene-modules from matched data sets and validating it on external data set using ROC analysis. Spearman's rank correlation coefficient of module scores between matched FFPE-frozen expression profiles was used to measure reliability of externally defined gene-modules in FFPE expression profiles. Independent of array/amplification-kit/sample preservation method used, de novo ER/HER2 gene-modules derived from all matching data sets showed similar prediction performance during independent validation (AUC range; ER: 0.92-0.95, HER2: 0.88-0.91), except for de novo HER2 gene-module derived from FFPE data set with 3'IVT kit (AUC: 0.67-0.72). Further not all gene-module based biological signals present in frozen expression profiles can be recovered from matching FFPE microarray expression profiles using the currently available FFPE specific sample preparation kits. The gene-module based biological signal extracted from FFPE RNA, using microarrays, may not be as reliable as that from their frozen counterpart, if the sample preparation protocol used with FFPE RNA failed to recover relevant genes involved in the biological signal.

Publication Title

Feasibility of developing reliable gene expression modules from FFPE derived RNA profiled on Affymetrix arrays.

Sample Metadata Fields

Specimen part

View Samples
accession-icon GSE93336
FFPE samples profiled on HG-U219 array with Nugen's Ovation FFPE WTA System and EncoreTM Biotin Module
  • organism-icon Homo sapiens
  • sample-icon 8 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)

Description

The reliability of differential expression analysis on FFPE expression profiles from Affymetrix arrays is questionable, due to the wide range of percent-present values reported in studies which profiled FFPE samples on Affymetrix arrays. Moreover the validity of externally defined gene-modules in FFPE microarray expression profiles is unknown. Using eight breast cancer tumors with available frozen and FFPE samples, five sample-matched data sets were generated from different combination of Affymetrix arrays, amplification-and-labeling kit and sample preservation method. The reliability of differential expression analysis was investigated by developing de novo ER/HER2 pathway gene-modules from matched data sets and validating it on external data set using ROC analysis. Spearman's rank correlation coefficient of module scores between matched FFPE-frozen expression profiles was used to measure reliability of externally defined gene-modules in FFPE expression profiles. Independent of array/amplification-kit/sample preservation method used, de novo ER/HER2 gene-modules derived from all matching data sets showed similar prediction performance during independent validation (AUC range; ER: 0.92-0.95, HER2: 0.88-0.91), except for de novo HER2 gene-module derived from FFPE data set with 3'IVT kit (AUC: 0.67-0.72). Further not all gene-module based biological signals present in frozen expression profiles can be recovered from matching FFPE microarray expression profiles using the currently available FFPE specific sample preparation kits. The gene-module based biological signal extracted from FFPE RNA, using microarrays, may not be as reliable as that from their frozen counterpart, if the sample preparation protocol used with FFPE RNA failed to recover relevant genes involved in the biological signal.

Publication Title

Feasibility of developing reliable gene expression modules from FFPE derived RNA profiled on Affymetrix arrays.

Sample Metadata Fields

Specimen part

View Samples
accession-icon GSE93335
Fresh-Frozen samples profiled on HG-U219 array with Nugen's Ovation FFPE WTA System and EncoreTM Biotin Module [dataset 3]
  • organism-icon Homo sapiens
  • sample-icon 8 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)

Description

The reliability of differential expression analysis on FFPE expression profiles from Affymetrix arrays is questionable, due to the wide range of percent-present values reported in studies which profiled FFPE samples on Affymetrix arrays. Moreover the validity of externally defined gene-modules in FFPE microarray expression profiles is unknown. Using eight breast cancer tumors with available frozen and FFPE samples, five sample-matched data sets were generated from different combination of Affymetrix arrays, amplification-and-labeling kit and sample preservation method. The reliability of differential expression analysis was investigated by developing de novo ER/HER2 pathway gene-modules from matched data sets and validating it on external data set using ROC analysis. Spearman's rank correlation coefficient of module scores between matched FFPE-frozen expression profiles was used to measure reliability of externally defined gene-modules in FFPE expression profiles. Independent of array/amplification-kit/sample preservation method used, de novo ER/HER2 gene-modules derived from all matching data sets showed similar prediction performance during independent validation (AUC range; ER: 0.92-0.95, HER2: 0.88-0.91), except for de novo HER2 gene-module derived from FFPE data set with 3'IVT kit (AUC: 0.67-0.72). Further not all gene-module based biological signals present in frozen expression profiles can be recovered from matching FFPE microarray expression profiles using the currently available FFPE specific sample preparation kits. The gene-module based biological signal extracted from FFPE RNA, using microarrays, may not be as reliable as that from their frozen counterpart, if the sample preparation protocol used with FFPE RNA failed to recover relevant genes involved in the biological signal.

Publication Title

Feasibility of developing reliable gene expression modules from FFPE derived RNA profiled on Affymetrix arrays.

Sample Metadata Fields

Specimen part

View Samples
accession-icon GSE93337
FFPE samples profiled on HG-U219 array with Affymetrix's SensationPlusTM FFPE Amplification and 3'IVT Labeling kit
  • organism-icon Homo sapiens
  • sample-icon 8 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)

Description

The reliability of differential expression analysis on FFPE expression profiles from Affymetrix arrays is questionable, due to the wide range of percent-present values reported in studies which profiled FFPE samples on Affymetrix arrays. Moreover the validity of externally defined gene-modules in FFPE microarray expression profiles is unknown. Using eight breast cancer tumors with available frozen and FFPE samples, five sample-matched data sets were generated from different combination of Affymetrix arrays, amplification-and-labeling kit and sample preservation method. The reliability of differential expression analysis was investigated by developing de novo ER/HER2 pathway gene-modules from matched data sets and validating it on external data set using ROC analysis. Spearman's rank correlation coefficient of module scores between matched FFPE-frozen expression profiles was used to measure reliability of externally defined gene-modules in FFPE expression profiles. Independent of array/amplification-kit/sample preservation method used, de novo ER/HER2 gene-modules derived from all matching data sets showed similar prediction performance during independent validation (AUC range; ER: 0.92-0.95, HER2: 0.88-0.91), except for de novo HER2 gene-module derived from FFPE data set with 3'IVT kit (AUC: 0.67-0.72). Further not all gene-module based biological signals present in frozen expression profiles can be recovered from matching FFPE microarray expression profiles using the currently available FFPE specific sample preparation kits. The gene-module based biological signal extracted from FFPE RNA, using microarrays, may not be as reliable as that from their frozen counterpart, if the sample preparation protocol used with FFPE RNA failed to recover relevant genes involved in the biological signal.

Publication Title

Feasibility of developing reliable gene expression modules from FFPE derived RNA profiled on Affymetrix arrays.

Sample Metadata Fields

Specimen part

View Samples
accession-icon GSE12079
Molecular profiling of CD3- CD4+ T-cells from patients with the lymphocytic variant of hypereosinophilic syndrome
  • organism-icon Homo sapiens
  • sample-icon 24 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)

Description

The clonal CD3- CD4+ Th2 cell population characterizing some hypereosinophilic syndrome patients stably endures for years provoking a chronic inflammatory skin disease, with a subgroup of patients ultimately progressing to T-cell lymphoma. The aim of this study is the identification of the molecular changes (1) associated with the persistence of the pre-malignant clone (2) associated with the activation of co-stimulatory receptors and (3) associated with the emergence of malignant T-cell subclones.

Publication Title

Molecular profiling of CD3-CD4+ T cells from patients with the lymphocytic variant of hypereosinophilic syndrome reveals targeting of growth control pathways.

Sample Metadata Fields

Specimen part, Disease, Disease stage, Time

View Samples
accession-icon GSE19615
Integrated genomic and function characterization of the 8q22 gain
  • organism-icon Homo sapiens
  • sample-icon 113 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)

Description

Integrated DNA and expression array analysis in primary human breast tumors identified chromosome 8q22 copy number gain and a suite of over-expressed genes in this region highly relevant to subsequent recurrence.

Publication Title

Amplification of LAPTM4B and YWHAZ contributes to chemotherapy resistance and recurrence of breast cancer.

Sample Metadata Fields

Age, Specimen part, Subject

View Samples
accession-icon GSE45255
Expression Profiles of Breast Tumors from Singapore and Europe
  • organism-icon Homo sapiens
  • sample-icon 123 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133A Array (hgu133a)

Description

To facilitate a better understanding of the molecular heterogeneity of breast cancer and to uncover gene-survival associations that segregate with distinct molecular subtypes, we recently compiled a meta-analytical database of over 2,000 human breast tumor expression profiles variously annotated for clinical and pathological variables and derived from various institutions worldwide. This database was utilized for the breast tumor study cited below: Nagalla, et. al., Genome Biology, 2013. While the majority of the tumor expression profiles included in this database derived from publicly accessible microarray repositories, a number of the samples had not been previously published. Here, we describe the origin of these samples and provide their associated clinical and pathological annotations with the hope that other investigators will be able to utilize these data in their own research.

Publication Title

Interactions between immunity, proliferation and molecular subtype in breast cancer prognosis.

Sample Metadata Fields

Age, Disease stage

View Samples
accession-icon GSE16391
GGI: a potential predictor of relapse for endocrine-treated breast cancer patients in the BIG 1-98 trial
  • organism-icon Homo sapiens
  • sample-icon 53 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)

Description

Background: We have previously shown that the Gene expression Grade Index (GGI) was able to identify two subtypes of estrogen receptor (ER)-positive tumors that were associated with statistically distinct clinical outcomes in both untreated and tamoxifen-treated patients. Here, we aim to investigate the ability of the GGI to predict relapses in postmenopausal women who were treated with tamoxifen (T) or letrozole (L) within the BIG 1-98 trial.

Publication Title

The Gene expression Grade Index: a potential predictor of relapse for endocrine-treated breast cancer patients in the BIG 1-98 trial.

Sample Metadata Fields

Age, Specimen part, Disease stage, Treatment

View Samples
...

refine.bio is a repository of uniformly processed and normalized, ready-to-use transcriptome data from publicly available sources. refine.bio is a project of the Childhood Cancer Data Lab (CCDL)

fund-icon Fund the CCDL

Developed by the Childhood Cancer Data Lab

Powered by Alex's Lemonade Stand Foundation

Cite refine.bio

Casey S. Greene, Dongbo Hu, Richard W. W. Jones, Stephanie Liu, David S. Mejia, Rob Patro, Stephen R. Piccolo, Ariel Rodriguez Romero, Hirak Sarkar, Candace L. Savonen, Jaclyn N. Taroni, William E. Vauclain, Deepashree Venkatesh Prasad, Kurt G. Wheeler. refine.bio: a resource of uniformly processed publicly available gene expression datasets.
URL: https://www.refine.bio

Note that the contributor list is in alphabetical order as we prepare a manuscript for submission.

BSD 3-Clause LicensePrivacyTerms of UseContact