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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

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accession-icon GSE74079
Expression data from GSS/101LL brain regions
  • organism-icon Mus musculus
  • sample-icon 23 Downloadable Samples
  • Technology Badge Icon Affymetrix Mouse Gene 2.1 ST Array (mogene21st)

Description

Gerstmann Strausller Scheinker (GSS) human prion disease homogenate is i.c. inoculated into mice exhibiting a proline to leucine alteration at codon 101 of the murine prion protein gene (101LL). This results in a disease with an incubation period of approximately 291 days. Normal brain homogenate i.c. inoculated into 101LL mice which are aged matched are used as controls.

Publication Title

Distribution of Misfolded Prion Protein Seeding Activity Alone Does Not Predict Regions of Neurodegeneration.

Sample Metadata Fields

Sex, Specimen part

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accession-icon GSE53031
Gene expression profiling of human breast cancer during pregnancy
  • organism-icon Homo sapiens
  • sample-icon 167 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U219 Array (hgu219)

Description

Using a dataset of 54 pregnant and 113 age/stage-matched non-pregnant breast cancer patients with complete clinical and survival data; we evaluated the pattern of hot spot somatic mutations and performed transcriptomic profiling using Sequenom and Affymetrix, respectively. Breast cancer molecular subtypes were defined using PAM50 and 3-Gene classifiers. We performed Gene set enrichment analysis (GSEA) to evaluate pathways associated with diagnosis during pregnancy. We investigated the differential expression of cancer-related genes and published gene sets according to pregnancy. We finally investigated genes associated with disease-free survival.

Publication Title

Biology of breast cancer during pregnancy using genomic profiling.

Sample Metadata Fields

Age, Disease stage

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accession-icon GSE65095
FinHER trial : Patients with human epidermal growth factor receptor 2 (HER2)positive breast cancer
  • organism-icon Homo sapiens
  • sample-icon 203 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U219 Array (hgu219)

Description

The FinHER trial is a multicentre phase 3 randomised adjuvant breast cancer trial that enrolled 1010 patients. The women were randomly assigned to receive three cycles of docetaxel or vinorelbine, followed by three cycles of fluorouracil, epirubicin, and cyclophosphamide.

Publication Title

Integrative proteomic and gene expression analysis identify potential biomarkers for adjuvant trastuzumab resistance: analysis from the Fin-her phase III randomized trial.

Sample Metadata Fields

Age, Disease stage

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accession-icon GSE43358
Transfer of clinically relevant gene expression signatures in breast cancer: from Affymetrix microarray to Illumina RNA-Sequencing technology
  • organism-icon Homo sapiens
  • sample-icon 51 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)

Description

Microarrays have revolutionized breast cancer (BC) research by enabling studies of gene expression on a transcriptome-wide scale. Recently, RNA-Sequencing (RNA-Seq) has emerged as an alternative for precise readouts of the transcriptome. To date, no study has compared the ability of the two technologies to quantify clinically relevant individual genes and microarray-derived gene expression signatures (GES) in a set of BC samples encompassing the known molecular BC's subtypes. To accomplish this, the RNA from 57 BCs representing the four main molecular subtypes (triple negative, HER2 positive, luminal A, luminal B), was profiled with Affymetrix HG-U133 Plus 2.0 chips and sequenced using the Illumina HiSeq 2000 platform. The correlations of three clinically relevant BC genes, six molecular subtype classifiers, and a selection of 21 GES were evaluated.

Publication Title

Transfer of clinically relevant gene expression signatures in breast cancer: from Affymetrix microarray to Illumina RNA-Sequencing technology.

Sample Metadata Fields

Specimen part, Disease stage

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accession-icon GSE6532
Definition of clinically distinct molecular subtypes in estrogen receptor positive breast carcinomas using genomic grade
  • organism-icon Homo sapiens
  • sample-icon 737 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133A Array (hgu133a)

Description

Purpose: A number of microarray studies have reported distinct molecular profiles of breast cancers (BC): basal-like, ErbB2-like and two to three luminal-like subtypes. These were associated with different clinical outcomes. However, although the basal and the ErbB2 subtypes are repeatedly recognized, identification of estrogen receptor (ER)-positive subtypes has been inconsistent. Refinement of their molecular definition is therefore needed.

Publication Title

Definition of clinically distinct molecular subtypes in estrogen receptor-positive breast carcinomas through genomic grade.

Sample Metadata Fields

Age, Disease stage

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accession-icon GSE9195
Predicting prognosis using molecular profiling in estrogen receptor-positive breast cancer treated with tamoxifen
  • organism-icon Homo sapiens
  • sample-icon 77 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)

Description

Background: Estrogen receptor positive (ER+) breast cancers (BC) are heterogeneous with regard to their clinical behavior and response to therapies. The ER is currently the best predictor of response to the anti-estrogen agent tamoxifen, yet up to 30-40% of ER+BC will relapse despite tamoxifen treatment. New prognostic biomarkers and further biological understanding of tamoxifen resistance are required. We used gene expression profiling to develop an outcome-based predictor using a training set of 255 ER+ BC samples from women treated with adjuvant tamoxifen monotherapy. We used clusters of highly correlated genes to develop our predictor to facilitate both signature stability and biological interpretation. Independent validation was performed using 362 tamoxifen-treated ER+ BC samples obtained from multiple institutions and treated with tamoxifen only in the adjuvant and metastatic settings.

Publication Title

Predicting prognosis using molecular profiling in estrogen receptor-positive breast cancer treated with tamoxifen.

Sample Metadata Fields

Age, Disease stage, Treatment

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accession-icon GSE2990
Gene Expression Profiling in Breast Cancer: Understanding the Molecular Basis of Histologic Grade To Improve Prognosis
  • organism-icon Homo sapiens
  • sample-icon 185 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133A Array (hgu133a)

Description

Background: Histologic grade in breast cancer provides clinically important prognostic information. However, 30%-60% of tumors are classified as histologic grade 2. This grade is associated with an intermediate risk of recurrence and is thus not informative for clinical decision making. We examined whether histologic grade was associated with gene expression profi les of breast cancers and whether such profi les could be used to improve histologic grading.

Publication Title

Gene expression profiling in breast cancer: understanding the molecular basis of histologic grade to improve prognosis.

Sample Metadata Fields

Age, Disease stage

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accession-icon GSE27120
Characterization and clinical evaluation of CD10+ stroma cells in the breast cancer microenvironment
  • organism-icon Homo sapiens
  • sample-icon 79 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)

Description

Purpose: There is growing evidence that interaction between stromal and tumor cells is pivotal in breast cancer progression and response to therapy. Since the pioneer work of Allinen et al. suggested that during breast cancer progression striking changes occur in CD10+ stromal cells, we aimed to better characterize this cell population and its clinical relevance.

Publication Title

Characterization and clinical evaluation of CD10+ stroma cells in the breast cancer microenvironment.

Sample Metadata Fields

Specimen part, Disease stage

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accession-icon GSE7390
Strong Time Dependence of the 76-Gene Prognostic Signature
  • organism-icon Homo sapiens
  • sample-icon 197 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133A Array (hgu133a)

Description

Background: Recently a 76-gene prognostic signature able to predict distant metastases in lymph node-negative (N-) breast cancer patients was reported. The aims of this study conducted by TRANSBIG were to independently validate these results and to compare the outcome with clinical risk assessment. Materials and Methods: Gene expression profiling of frozen samples from 198 N- systemically untreated patients was performed at the Bordet Institute, blinded to clinical data and independent of Veridex. Genomic risk was defined by Veridex, blinded to clinical data. Survival analyses, done by an independent statistician, were performed with the genomic risk and adjusted for the clinical risk, defined by Adjuvant!Online. Results: The actual 5- and 10-year time to distant metastasis (TDM) were 98% (88%-100%) and 94% (83%-98%) respectively for the good profile group and 76% (68%- 82%) and 73% (65%-79%) for the poor profile group. The actual 5- and 10-year overall survival (OS) were 98% (88%-100%) and 87% (73%-94%) respectively for the good profile group and 84% (77%-89%) and 72% (63%-78%) for the poor profile group. We observed a strong time-dependency of this signature, leading to an adjusted HR of 13.58 (1.85-99.63) and 8.20 (1.10-60.90) at 5 years, and 5.11 (1.57-16.67) and 2.55 (1.07-6.10) at 10 years for TDM and OS respectively. Conclusion: This independent validation confirmed the performance of the 76-gene signature and adds to the growing evidence that gene expression signatures are of clinical relevance, especially for identifying patients at high risk of early distant metastases.

Publication Title

Strong time dependence of the 76-gene prognostic signature for node-negative breast cancer patients in the TRANSBIG multicenter independent validation series.

Sample Metadata Fields

Age, Disease stage

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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)

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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.

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