Gene expression data for 637 human primary breast tumors with recurrence, ER/PR/HER2 status, and overall survival
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ABSTRACT:
ORGANISM(S): Homo sapiens
PROVIDER: GSE199633 | GEO | 2024/06/07
REPOSITORIES: GEO
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Project description:Gene expression data for 637 human primary breast tumors with recurrence, ER/PR/HER2 status, and overall survival
| PRJNA820880 | ENA
Project description:PURPOSE:To investigate the impact of chemotherapy relative dose intensity (RDI) on cause-specific and overall survival for stage I-III breast cancer: estrogen receptor or progesterone receptor positive, human epidermal-growth factor receptor negative (ER+/PR+ and HER2-) vs. triple-negative (TNBC) and to identify the optimal RDI cut-off points in these two patient populations. METHODS:Data were collected by the Louisiana Tumor Registry for two CDC-funded projects. Women diagnosed with stage I-III ER+/PR+, HER2- breast cancer, or TNBC in 2011 with complete information on RDI were included. Five RDI cut-off points (95, 90, 85, 80, and 75%) were evaluated on cause-specific and overall survival, adjusting for multiple demographic variables, tumor characteristics, comorbidity, use of granulocyte-growth factor/cytokines, chemotherapy delay, chemotherapy regimens, and use of hormone therapy. Cox proportional hazards models and Kaplan-Meier survival curves were estimated and adjusted by stabilized inverse probability treatment weighting (IPTW) of propensity score. RESULTS:Of 494 ER+/PR+, HER2- patients and 180 TNBC patients, RDI < 85% accounted for 30.4 and 27.8%, respectively. Among ER+/PR+, HER2- patients, 85% was the only cut-off point at which the low RDI was significantly associated with worse overall survival (HR = 1.93; 95% CI 1.09-3.40). Among TNBC patients, 75% was the cut-off point at which the high RDI was associated with better cause-specific (HR = 2.64; 95% CI 1.09, 6.38) and overall survival (HR = 2.39; 95% CI 1.04-5.51). CONCLUSIONS:Higher RDI of chemotherapy is associated with better survival for ER+/PR+, HER2- patients and TNBC patients. To optimize survival benefits, RDI should be maintained ? 85% in ER+/PR+, HER2- patients, and ? 75% in TNBC patients.
| S-EPMC6190707 | biostudies-literature
Project description:Because histologic types are subjective and difficult to reproduce between pathologists, tissue morphology often takes a back seat to molecular testing for the selection of breast cancer treatments. This work explores whether a deep-learning algorithm can learn objective histologic H&E features that predict the clinical subtypes of breast cancer, as assessed by immunostaining for estrogen, progesterone, and Her2 receptors (ER/PR/Her2). Translating deep learning to this and related problems in histopathology presents a challenge due to the lack of large, well-annotated data sets, which are typically required for the algorithms to learn statistically significant discriminatory patterns. To overcome this limitation, we introduce the concept of "tissue fingerprints," which leverages large, unannotated datasets in a label-free manner to learn H&E features that can distinguish one patient from another. The hypothesis is that training the algorithm to learn the morphological differences between patients will implicitly teach it about the biologic variation between them. Following this training internship, we used the features the network learned, which we call "fingerprints," to predict ER, PR, and Her2 status in two datasets. Despite the discovery dataset being relatively small by the standards of the machine learning community (n = 939), fingerprints enabled the determination of ER, PR, and Her2 status from whole slide H&E images with 0.89 AUC (ER), 0.81 AUC (PR), and 0.79 AUC (Her2) on a large, independent test set (n = 2531). Tissue fingerprints are concise but meaningful histopathologic image representations that capture biological information and may enable machine learning algorithms that go beyond the traditional ER/PR/Her2 clinical groupings by directly predicting theragnosis.
| S-EPMC7190637 | biostudies-literature
Project description:BackgroundGenetic alterations in cellular signaling networks are a hallmark of cancer, however, effective methods to discover them are lacking. A novel form of abnormality called acquired uniparental disomy (aUPD) was recently found to pinpoint the region of mutated genes in various cancers, thereby identifying the region for next-generation sequencing.Methods/principal findingsWe retrieved large genomic data sets from the Gene Expression Omnibus database to perform genome-wide analysis of aUPD in breast tumor samples and cell lines using approaches that can reliably detect aUPD. aUPD was identified in 52.29% of the tumor samples. The most frequent aUPD regions were located at chromosomes 2q, 3p, 5q, 9p, 9q, 10q, 11q, 13q, 14q and 17q. We evaluated the data for any correlation between the most frequent aUPD regions and HER2/neu, ER, and PR status, and found a statistically significant correlation between the recurrent regions of aUPD and triple negative (TN) breast cancers. aUPD at chromosome 17q (VEZF1, WNT3), 3p (SUMF1, GRM7), 9p (MTAP, NFIB) and 11q (CASP1, CASP4, CASP5) are predictors for TN. The frequency of aUPD was found to be significantly higher in TN breast cancer cases compared to HER2/neu-positive and/or ER or PR-positive cases. Furthermore, using previously published mutation data, we found TP53 homozygously mutated in cell lines having aUPD in that locus.Conclusions/significanceWe conclude that aUPD is a common and non-random molecular feature of breast cancer that is most prominent in triple negative cases. As aUPD regions are different among the main pathological subtypes, specific aUPD regions may aid the sub-classification of breast cancer. In addition, we provide statistical support using TP53 as an example that identifying aUPD regions can be an effective approach in finding aberrant genes. We thus conclude that a genome-wide scale analysis of aUPD regions for homozygous sequence alterations can provide valuable insights into breast tumorigenesis.
| S-EPMC2994899 | biostudies-literature
Project description:The risk of locoregional or distant failure in advanced HPV-negative head and neck squamous cell carcinoma (HNSCC) patients is high. However, no suitable markers for stratification are clinically available. Thus, we aimed to identify a microRNA(miRNA)-signature predicting disease recurrence. For this purpose the miRNA profiles from 162 HNSCC samples were analysed with regard to identification of a low-complex porgnostic signature. The data set consists of a discovery dataset (n=85) and a validation dataset (n=77). The study resulted in a prognostic 5-miRNA signature significantly predicting the relevant clinical endpoint freedom from recurrence.
2018-09-06 | E-MTAB-5793 | biostudies-arrayexpress
Project description:The calcium-activated chloride channel Ano1 (TMEM16A) is overexpressed in many tumors. However, conflicting data exist regarding the role of Ano1 in cell proliferation. Here, we performed immunohistochemistry to investigate the expression of Ano1 and Ki67 in 403 patients with breast cancer, and analyzed the association between the expression of Ano1 and Ki67 in breast cancer subtypes categorized according to estrogen receptor (ER), progesterone receptor (PR), and human epidermal growth factor receptor 2 (HER2). Ano1 expression was negatively correlated with Ki67 expression. Ano1 overexpression more frequently occurred in ER-positive or HER2-negative patients with the low expression of Ki67. Ano1 overexpression was associated with longer overall survival (OS) in breast cancer with the low expression of Ki67, especially in ER-positive, PR-positive, and HER2-negative breast cancer. Multivariate Cox regression analysis showed that Ano1 overexpression was a prognostic factor for longer overall survival in ER-positive, PR-positive, or HER2-negative patients with the low expression of Ki67. Furthermore, Ano1 promoted cell proliferation in ER-positive, PR-positive, and HER2-negative MCF7 cells, but inhibited cell proliferation in ER-negative, PR-negative, and HER2-negative MDA-MB-435S cells. Our findings suggest that Ano1 may differentially regulate cell proliferation in a subtype of breast cancer defined by ER, PR, and HER2. Combined expression of Ano1 and Ki67 may be used for predicting clinical outcomes of breast cancer patients with different subtypes of ER, PR, and HER2.
| S-EPMC5689589 | biostudies-literature
Project description:Progesterone receptor (PR) is usually co-localized with estrogen receptor (ER) in normal mammary cells. It is not known whether ER/PR-negative human breast cancer arises from an ER/PR-negative cell or from an ER/PR-positive cell that later lost ER/PR. Using intraductal injection of a lentivirus to deliver both an oncogene (ErbB2) and a floxed green fluorescent protein (GFP) in PR(Cre/+)mice, whose Cre gene is under the control of the PR promoter, we were able to trace the PR status of the infected cells as they progressed to cancer. We found that the resulting early lesions stained negative for PR in most of the cells and usually retained GFP. The resulting tumors lacked ER and PR, and 75% (15/20) of them retained the GFP signal in all tumor cells, suggesting PR was never expressed throughout the evolution of a majority of these tumors. In conclusion, our data demonstrate that ErbB2-initiated ER/PR-negative mammary tumors primarily originate from the subset of the mammary epithelium that is negative for PR and probably ER as well. These findings also provide an explanation for why antihormonal therapy fails to prevent ER-negative breast cancers.
| S-EPMC5944622 | biostudies-literature
Project description:Breast cancers are categorized into three subtypes based on protein expression of estrogen receptor (ER), progesterone receptor (PR), and human epidermal growth factor receptor-2 (HER2/ERBB2). Patients enroll onto experimental clinical trials based on ER, PR, and HER2 status and, as receptor status is prognostic and defines treatment regimens, central receptor confirmation is critical for interpreting results from these trials. Patients enrolling onto experimental clinical trials in the metastatic setting often have limited available archival tissue that might better be used for comprehensive molecular profiling rather than slide-intensive reconfirmation of receptor status. We developed a Random Forests-based algorithm using a training set of 158 samples with centrally confirmed IHC status, and subsequently validated this algorithm on multiple test sets with known, locally determined IHC status. We observed a strong correlation between target mRNA expression and IHC assays for HER2 and ER, achieving an overall accuracy of 97 and 96%, respectively. For determining PR status, which had the highest discordance between central and local IHC, incorporation of expression of co-regulated genes in a multivariate approach added predictive value, outperforming the single, target gene approach by a 10% margin in overall accuracy. Our results suggest that multiplexed qRT-PCR profiling of ESR1, PGR, and ERBB2 mRNA, along with several other subtype associated genes, can effectively confirm breast cancer subtype, thereby conserving tumor sections and enabling additional biomarker data to be obtained from patients enrolled onto experimental clinical trials.
| S-EPMC4223539 | biostudies-literature
Project description:Background: Extensive amounts of archived formalin fixed paraffin embedded (FFPE) human tumor tissues are the ultimate resource to investigate signaling network underlying tumorigenesis in human. Yet, their usage is severely limited for lacking of suitable protein techniques. In this study, a quantitative, objective, absolute, and high throughput immunoblot method, quantitative dot blot (QDB), was explored to address this issue by investigating the putative relationship between estrogen receptor (ER)/progesterone receptor (PR) and human epidermal growth factor receptor 2 (Her2) pathways in breast cancer tumorigenesis. Methods: In this descriptive observational retrospective study, ER, PR, Her2, and Ki67 protein levels were measured absolutely and quantitatively in 852 FFPE breast cancer tissues using the QDB method. ER, PR, and Her2 levels were charted on the X, Y, and Z-axes to observe samples distribution in a 3D scatterplot. Results: A "seesaw" relationship between ER/PR and Her2 pathways was observed in ER-PR-Her2 space, characterized by the expression levels of these 3 proteins. Specimens with strong expressions of ER/PR proteins were found spreading along the ER/PR floor while those with strong Her2 expression were found wrapping around the Her2 axis. Those lacking strong expressions of all 3 proteins were found accumulating at the intersection of the ER, PR, and Her2 axes. Few specimens floated in the ER-PR-Her2 space to suggest the lack of co-expression of all 3 proteins simultaneously. Ki67 levels were found to be significantly reduced in specimens spreading in the ER-PR space. Conclusions: The unique distribution of specimens in ER-PR-Her2 space prior to any clinical intervention provided visual support of bidirectional talk between ER/PR and Her2 pathways in breast cancer specimens. Clinical interventions to suppress these 2 pathways alternatively warrant further exploration for breast cancer patients accordingly. Our study also demonstrated that the QDB method is an effective tool to analyze archived FFPE cancer specimens in biomedical research.
| S-EPMC8674721 | biostudies-literature
Project description:Background: Although intrinsic molecular subtype has been widely used, there remains great clinical heterogeneity of prognosis in the estrogen receptor (ER)- and/or progesterone receptor (PR)-positive and human epidermal growth factor receptor 2 (HER2)-negative breast cancer (BC). Methods: The transcriptome expression data of messenger RNA (mRNA) were downloaded from The Cancer Genome Atlas (TCGA), Molecular Taxonomy of Breast Cancer International Consortium (METABRIC), and the Gene Expression Omnibus (GEO) databases. Immune-related genes were acquired from the ImmPort database and additional literature search. Univariate Cox, LASSO regression, and multivariate Cox regression were used to screen prognostic immune-related genes and establish the risk signature. The correlation between the risk signature and clinical characteristics, the abundances of immune cells within the tumor microenvironment, and cancer phenotypes were further assessed. Results: Of note, 102 immune-related prognostic genes were identified in the METABRIC dataset by univariate Cox analysis. Consecutively, 7 immune-related genes (SHMT2, AGA, COL17A1, FLT3, SLC7A2, ATP6AP1, and CCL19) were selected to establish the risk signature by LASSO regression and multivariate Cox analysis. Its performance was further verified in TCGA and GSE21653 datasets. Multivariate Cox analysis showed that the risk signature was an independent prognostic factor. The 7-gene signature showed a significant correlation with intrinsic molecular subtypes and 70-gene signature. Furthermore, the CD4+ memory T cells were significantly higher in the low-risk group while a significantly higher proportion of M0-type macrophages was found in the high-risk group in both METABRIC and TCGA cohorts, which may have an influence on the prognosis. Furthermore, we found that the low-risk group may be associated with the immune-related pathway and the high-risk group was with the cell cycle-related pathway, which also showed an impact on the prognosis. Conclusion: These seven immune-related gene risk signatures provided an effective method for prognostic stratification in ER (+) and/or PR (+) and HER2 (-) BC.
| S-EPMC9201983 | biostudies-literature