Molecular Profiles of Human Breast Cancer and Their Association with Tumor Subtypes and Disease Prognosis
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ABSTRACT:
ORGANISM(S): Homo sapiens
PROVIDER: GSE39004 | GEO | 2013/11/01
SECONDARY ACCESSION(S): PRJNA169566
REPOSITORIES: GEO
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Project description:This SuperSeries is composed of the SubSeries listed below. Refer to individual Series
2013-11-01 | E-GEOD-39004 | biostudies-arrayexpress
Project description:This study identified DNA methylation patterns that were associated with tumor subtypes, disease outcome, and distinct metabolome and gene expression patterns. This study performed a large scale DNA methylation (Illumina HumanMethylation450 BeadChip [HumanMethylation450 15017482 v.1.1], N=73), gene expression (Affymetrix Human Gene 1.0 ST Array [HuGene-1_0-st], N=108), and metabolome (Metabolon, Inc. Durham, NC) analysis of fresh-frozen human breast tumors from African-American and European-American patients from the greater Baltimore area, Maryland (US), with survival follow-up.
| S-ECPF-GEOD-37751 | biostudies-other
Project description:This study identified DNA methylation patterns that were associated with tumor subtypes, disease outcome, and distinct metabolome and gene expression patterns. This study performed a large scale DNA methylation (Illumina HumanMethylation450 BeadChip [HumanMethylation450 15017482 v.1.1], N=73), gene expression (Affymetrix Human Gene 1.0 ST Array [HuGene-1_0-st], N=108), and metabolome (Metabolon, Inc. Durham, NC) analysis of fresh-frozen human breast tumors from African-American and European-American patients from the greater Baltimore area, Maryland (US), with survival follow-up.
2013-11-01 | E-GEOD-37751 | biostudies-arrayexpress
Project description:This study identified DNA methylation patterns that were associated with tumor subtypes, disease outcome, and distinct metabolome and gene expression patterns. This study performed a large scale DNA methylation (Illumina HumanMethylation450 BeadChip [HumanMethylation450 15017482 v.1.1], N=72), gene expression (Affymetrix Human Gene 1.0 ST Array [HuGene-1_0-st], N=108), and metabolome (Metabolon, Inc. Durham, NC) analysis of fresh-frozen human breast tumors from African-American and European-American patients from the greater Baltimore area, Maryland (US), with survival follow-up.
2013-11-01 | E-GEOD-37754 | biostudies-arrayexpress
Project description:This study identified DNA methylation patterns that were associated with tumor subtypes, disease outcome, and distinct metabolome and gene expression patterns.
2013-11-01 | GSE37754 | GEO
Project description:This study identified DNA methylation patterns that were associated with tumor subtypes, disease outcome, and distinct metabolome and gene expression patterns.
2013-11-01 | GSE37751 | GEO
Project description:Molecular Profiles of Human Breast Cancer and Their Association with Tumor Subtypes and Disease Prognosis
| PRJNA169566 | ENA
Project description:In breast cancer, inactivation of the RB tumor suppressor gene is believed to occur via multiple mechanisms to facilitate tumorigenesis. However, the prognostic and predictive value of RB status in disease-specific clinical outcomes has remained uncertain. We investigated RB pathway deregulation in the context of both ER-positive and ER-negative disease using combined microarray datasets encompassing over 900 breast cancer patient samples. Disease-specific characteristics of RB pathway deregulation were investigated in this dataset by evaluating correlation among pathway genes as well as differential expression across patient tumor populations defined by ER status. Survival analysis among these breast cancer samples demonstrates that the RB-loss signature is associated with poor disease outcome within several independent cohorts. Within the ER-negative subpopulation, the RB-loss signature is associated with improved response to chemotherapy and longer relapse-free survival. Additionally, while individual genes in the RB target signature closely reproduce its prognostic value, they also serve to predict and monitor response to therapeutic compounds, such as the cytostatic agent PD-0332991. These results indicate that the RB-loss signature expression is associated with poor outcome in breast cancer, but predicts improved response to chemotherapy based on data in ER-negative populations. While the RB-loss signature, as a whole, demonstrates prognostic and predictive utility, a small subset of markers could be sufficient to stratify patients based on RB function and inform the selection of appropriate therapeutic regimens.
| S-EPMC3055199 | biostudies-literature
Project description:BackgroundFeatures in preoperative ultrasound could predict the prognosis of triple-negative breast cancer (TNBC), while its prognostic value in other molecular subtypes of breast cancer (BC) was unknown. The study aimed to assess the prognostic value of preoperative sonographic features, including orientations, on long-term outcomes in BC and its association with different molecular subtypes.MethodsWomen diagnosed with invasive BC > 5 mm who underwent surgery were retrospectively reviewed. Clinical, pathological, and sonographic profiles were collected and recurrence-free survival (RFS) and breast cancer-specific survival (BCSS) were reported. Interactions between clinicopathological features and tumor orientations in predicting RFS and BCSS were analyzed. Competing risk model was performed to estimate prognostic values of sonographic features for RFS and BCSS.ResultsA total of 2812 patients were included. With a median follow-up of 60.0 months, 268 (9.5%) patients suffered from recurrences and 104 (3.7%) died of BC. The prognostic values of vertical orientation in predicting RFS (P = .001) and BCSS (P = .001) were strongly associated with molecular subtypes. Non-TNBC tumors with vertical orientation had less recurrence events compared with parallel orientation (6.3% vs 8.7%, P = .035), whereas failed to predict disease outcomes in multivariate analysis (P > .05). Oppositely, in TNBC, vertical orientation was associated with worse RFS (HR = 3.50; 95% confidence interval [CI] 1.69-7.24; P < .001) and BCSS (HR = 6.36; 95% CI 2.86-14.14; P < .001) in multivariate analysis with a 5-year RFS and BCSS of 73.4% and 74.6%. Meanwhile, vertical orientation was related with smaller tumor size (P < .001), human epidermal growth factor receptor 2 nonamplification (P < .001), and lower Ki-67 expression (P = .001) among non-TNBC population, whereas TNBC tumors with vertical orientation had a higher burden of axillary lymph node metastases (2.8 ± 1.0 vs 1.4 ± 0.2, P = .001).ConclusionsPrognostic values of sonographic orientation in predicting BC disease outcomes were associated with molecular subtypes. Vertical orientation in preoperative sonogram may serve as a prognostic biomarker for TNBC patients.
| S-EPMC7476839 | biostudies-literature
Project description:To advance in our understanding of the biological pathways involved in breast cancer tumor progression we have analyzed a set of breast tumor biopsies in order to identify the genomic pathways in which tumor may develop. With this objective, a cDNA microarray platform containing 800 genes was constructed. These genes were chosen because they are in several representatives signaling pathways, namely estrogen and progesterone receptor related pathways, cell cycle, DNA repair, chromatin remodeling, cell proliferation, apoptosis, cell adhesion, cell invasion and angiogenesis. An analysis of the gene expression profile of a large group of breast tumors was carried out and good correlation with their clinical-histopathological data was obtained. We identified different tumor subclusters with distinctive phenotype characteristics within our population, which later correlated with clinical outcome. The most significant genes able to discriminate between different tumor phenotypes of our training set of samples were determined applying a “Leave-one-out” cross-validation method of statistical analysis called PAM (Prediction analysis of microarrays). The predictor was further tested on a new incoming set of samples where we determined to which subtype of tumor new samples were allocated and predicted outcome was compared to clinical data, showing how some distinct tumor phenotypes correlate with a poor prognosis. Pathway analysis of the most significant genes belonging to each phenotype was performed to elucidate the most representative biological signaling pathways through which tumor progression might elapse. We constructed a real time expression profiling platform with a selection of the most differentially expressed genes in each subtype, which could be used as a technique to help improve the diagnosis and prognosis of the breast tumor samples of our sample population.
2017-12-31 | GSE18908 | GEO