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.
The Gene expression Grade Index: a potential predictor of relapse for endocrine-treated breast cancer patients in the BIG 1-98 trial.
Age, Specimen part, Disease stage, Treatment
View SamplesGerstmann 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.
Distribution of Misfolded Prion Protein Seeding Activity Alone Does Not Predict Regions of Neurodegeneration.
Sex, Specimen part
View SamplesUsing 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.
Biology of breast cancer during pregnancy using genomic profiling.
Age, Disease stage
View SamplesThe 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.
Integrative proteomic and gene expression analysis identify potential biomarkers for adjuvant trastuzumab resistance: analysis from the Fin-her phase III randomized trial.
Age, Disease stage
View SamplesMicroarrays 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.
Transfer of clinically relevant gene expression signatures in breast cancer: from Affymetrix microarray to Illumina RNA-Sequencing technology.
Specimen part, Disease stage
View SamplesPurpose: 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.
Definition of clinically distinct molecular subtypes in estrogen receptor-positive breast carcinomas through genomic grade.
Age, Disease stage
View SamplesBackground: 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.
Predicting prognosis using molecular profiling in estrogen receptor-positive breast cancer treated with tamoxifen.
Age, Disease stage, Treatment
View SamplesBackground: 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.
Gene expression profiling in breast cancer: understanding the molecular basis of histologic grade to improve prognosis.
Age, Disease stage
View SamplesPurpose: 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.
Characterization and clinical evaluation of CD10+ stroma cells in the breast cancer microenvironment.
Specimen part, Disease stage
View SamplesBackground: 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.
Strong time dependence of the 76-gene prognostic signature for node-negative breast cancer patients in the TRANSBIG multicenter independent validation series.
Age, Disease stage
View Samples