Molecular characteristics and metastasis predictor genes of triple-negative breast cancer (II)
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ABSTRACT:
ORGANISM(S): Homo sapiens
PROVIDER: GSE53752 | GEO | 2014/01/02
SECONDARY ACCESSION(S): PRJNA232811
REPOSITORIES: GEO
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Project description:This microarray dataset contains 51 triple-negative breast cancers with clinical and recurrence information for at least 3 years of follow-up and 106 luminal breast cancers (reanalyzed data from Series GSE24124, GSE9309, and GSE17040). A novel set of 45-gene signature that was statistically predictive of distant metastasis recurrence for triple-negative breast cancer was identified in this study.
2012-11-01 | GSE33926 | GEO
Project description:This microarray dataset contains 51 triple-negative breast cancers, 25 normal breast tissues, and 106 luminal breast cancers (reanalyzed data from Series GSE24124, GSE9309, and GSE17040). Keywords: Expression profiling by array Specimens of breast cancer tissue were collected and snap-frozen from breast cancer patients who had surgery between 1995 and 2008 at National Taiwan University Hospital (NTUH, Taipei, Taiwan). Clinicopathological information was obtained for all breast cancer patients along with informed consent. The AJCC/UICC TNM system was used for breast cancer staging classification.
2014-01-02 | E-GEOD-53752 | biostudies-arrayexpress
Project description:This microarray dataset contains 51 triple-negative breast cancers, 25 normal breast tissues, and 106 luminal breast cancers (reanalyzed data from Series GSE24124, GSE9309, and GSE17040). Keywords: Expression profiling by array Specimens of breast cancer tissue were collected and snap-frozen from breast cancer patients who had surgery between 1995 and 2008 at National Taiwan University Hospital (NTUH, Taipei, Taiwan). Clinicopathological information was obtained for all breast cancer patients along with informed consent. The AJCC/UICC TNM system was used for breast cancer staging classification.
| S-ECPF-GEOD-53752 | biostudies-other
Project description:Determination of recurrent chromosomal aberrations in Luninal A, Luminal B, HER2-positve, and triple negative breast cancers 131 samples, Tumour DNA vs Normal DNA
2015-12-10 | E-GEOD-54140 | biostudies-arrayexpress
Project description:Determination of recurrent chromosomal aberrations in Luninal A, Luminal B, HER2-positve, and triple negative breast cancers
2015-12-10 | GSE54140 | GEO
Project description:Discrepancies in the prognosis of triple negative breast cancer exist between Caucasian and Asian populations. Yet, the gene signature of triple negative breast cancer specifically for Asians has not become available. Therefore, the purpose of this study is to construct a prediction model for recurrence of triple negative breast cancer in Taiwanese patients. Whole genome expression profiling of breast cancers from 185 patients in Taiwan from 1995 to 2008 was performed, and the results were compared to the previously published literature to detect differences between Asian and Western patients. Pathway analysis and Cox proportional hazard models were applied to construct a prediction model for the recurrence of triple negative breast cancer. Most expression data of samples (181/185) were reanalyzed from previous studies already uploaded to GEO (see "reanalysis of" links below). Four additional gene expression profiling data of triple negative breast cancer sample were added to this study.
2012-02-02 | E-GEOD-33095 | biostudies-arrayexpress
Project description:BackgroundTriple-negative breast cancer is a subtype of breast cancer with aggressive tumor behavior and distinct disease etiology. Due to the lack of an effective targeted medicine, treatment options for triple-negative breast cancer are few and recurrence rates are high. Although various multi-gene prognostic markers have been proposed for the prediction of breast cancer outcome, most of them were proven clinically useful only for estrogen receptor-positive breast cancers. Reliable identification of triple-negative patients with a favorable prognosis is not yet possible.Methodology/principal findingsClinicopathological information and microarray data from 157 invasive breast carcinomas were collected at National Taiwan University Hospital from 1995 to 2008. Gene expression data of 51 triple-negative and 106 luminal breast cancers were generated by oligonucleotide microarrays. Hierarchical clustering analysis revealed that the majority (94%) of triple-negative breast cancers were tightly clustered together carrying strong basal-like characteristics. A 45-gene prognostic signature giving 98% predictive accuracy in distant recurrence of our triple-negative patients was determined using the receiver operating characteristic analysis and leave-one-out cross validation. External validation of the prognostic signature in an independent microarray dataset of 59 early-stage triple-negative patients also obtained statistical significance (hazard ratio 2.29, 95% confidence interval (CI) 1.04-5.06, Cox P=0.04), outperforming five other published breast cancer prognostic signatures. The 45-gene signature identified in this study revealed that TGF-? signaling of immune/inflammatory regulation may play an important role in distant metastatic invasion of triple-negative breast cancer.Conclusions/significanceGene expression data and recurrence information of triple-negative breast cancer were collected and analyzed in this study. A novel set of 45-gene signature was found to be statistically predictive in disease recurrence of triple-negative breast cancer. The 45-gene signature, if further validated, may be a clinically useful tool in risk assessment of distant recurrence for early-stage triple-negative patients.
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Project description:Purpose: The biological subtypes of breast cancer designated as Luminal A, Luminal B, HER2+/ER-, and Basal-like are clinically important for prognosis and planning treatment strategies. Recognizing that there is a continuum in both the spectrum of breast cancer disease and the risk of survival, we sought to develop a clinical test for the biological subtypes using a supervised risk classier.Methods: Microarray and real-time quantitative RT-PCR (qRT-PCR) data from 189 samples, procured as fresh-frozen and formalin-fixed, paraffin-embedded tissues, were used to statistically select prototypical samples and genes for the biological subtypes of breast cancer. Predictions for biological subtype and risk of recurrence were determined for different stages of disease, treatments, and across analytical platforms. Results: The biological subtype predictions on a large combined microarray test set showed prognostic significance across all patients (1244 subjects; p<0.0001), on node negative patients with no adjuvant systemic therapy (738 subjects; p<0.0001), and on patients treated with endocrine therapy (404 subjects; p=0.001). Analysis of a neoadjuvant chemotherapy study revealed a high pathologic complete response (pCR) rate in HER2+/ER- and Basal-like patients. The subtype and risk predications were also highly significant when using the qRT-PCR assay from archived FFPE breast cancers. Conclusion: Our risk predictor based on distance to biological subtype centroids provides a continuous risk score that applies to all stages of breast cancer given current therapies. The assay can be performed using archived breast tissues and a real-time qRT-PCR assay, thus facilitating application to retrospective cohorts and clinical samples. Keywords: reference x sample Comparison of reference samples against treatment
2010-06-24 | E-GEOD-10886 | biostudies-arrayexpress
Project description:The goal of this dataset is to compare the gene expression patterns between primary and metastatic tumors Metastatic cancer patients typically have short survival times and their successful treatment represents one of most challenging aspects of patient care. This poor prognostic behavior is likely due to many factors, including increased clonal heterogeneity, multiple drug resistance mechanisms, and the role of the tumor microenvironment. The AURORA US Metastasis Project was established to collect and molecularly characterize specimens from 55 breast cancer (BC) patients representing 51 primary cancers and 102 metastases. The 153 unique tumors were assayed using RNAseq, tumor/germline DNA exomes and low pass whole genome sequencing, and global DNA methylation microarrays. We found intrinsic molecular subtype differences between primary tumors and their matched metastases to be rare in triple negative breast cancer (TNBC)/Basal-like subtype tumors. Conversely, tumor subtype changes were relatively frequent in estrogen receptor positive (ER+) cancers where ~30% of Luminal A cases switched to Luminal B or HER2-enriched (HER2E) subtype. Clonal evolution studies identified changes in expression subtype coincident with DNA clonality shifts, especially involving HER2 amplification and/or the HER2E expression subtype. Microenvironment differences varied according to tumor subtype where ER+/Luminal metastases had lower fibroblast and endothelial cell content, while TNBC/Basal-like metastases showed a dramatic decrease in adaptive immunity. In 17% of metastatic tumors, we identified DNA methylation and/or focal DNA deletions near HLA-A that were associated with its significantly reduced expression, and with lower immune cell infiltrates. We also identified low immune cell features in brain and liver metastases when compared to other metastatic sites, even within the same patient. These findings have direct implications for the treatment of metastatic breast cancer patients with immune- and HER2-targeting therapies and suggest potential novel therapeutic avenues for the improvement of outcomes for some MBC patients.
2023-01-03 | GSE193103 | GEO
Project description:Purpose: The biological subtypes of breast cancer designated as Luminal A, Luminal B, HER2+/ER-, and Basal-like are clinically important for prognosis and planning treatment strategies. Recognizing that there is a continuum in both the spectrum of breast cancer disease and the risk of survival, we sought to develop a clinical test for the biological subtypes using a supervised risk classier.Methods: Microarray and real-time quantitative RT-PCR (qRT-PCR) data from 189 samples, procured as fresh-frozen and formalin-fixed, paraffin-embedded tissues, were used to statistically select prototypical samples and genes for the biological subtypes of breast cancer. Predictions for biological subtype and risk of recurrence were determined for different stages of disease, treatments, and across analytical platforms. Results: The biological subtype predictions on a large combined microarray test set showed prognostic significance across all patients (1244 subjects; p<0.0001), on node negative patients with no adjuvant systemic therapy (738 subjects; p<0.0001), and on patients treated with endocrine therapy (404 subjects; p=0.001). Analysis of a neoadjuvant chemotherapy study revealed a high pathologic complete response (pCR) rate in HER2+/ER- and Basal-like patients. The subtype and risk predications were also highly significant when using the qRT-PCR assay from archived FFPE breast cancers. Conclusion: Our risk predictor based on distance to biological subtype centroids provides a continuous risk score that applies to all stages of breast cancer given current therapies. The assay can be performed using archived breast tissues and a real-time qRT-PCR assay, thus facilitating application to retrospective cohorts and clinical samples. Keywords: reference x sample
2009-02-11 | GSE10886 | GEO