A pooled treatment-curated breast cancer gene-expression dataset
Ontology highlight
ABSTRACT:
ORGANISM(S): Homo sapiens
PROVIDER: GSE205568 | GEO | 2024/03/09
REPOSITORIES: GEO
Similar Datasets
Project description:Purpose Aromatase inhibitors (AIs) have an established role in breast cancer treatment. Response rates are only 50-70% in the neoadjuvant setting and lower in advanced disease. Accurate biomarkers are urgently needed to predict response in these settings and to determine which individuals will benefit from adjuvant AI therapy. Participants and Methods Pre- and on-treatment (after 2 weeks and 3 months) biopsies were obtained from 89 post-menopausal women with ER+ breast cancer receiving neoadjuvant letrozole for transcript profiling. Dynamic clinical response was assessed by three-dimensional ultrasound measurements. Results The molecular response to letrozole was characterised and a four gene classifier of clinical response was established (accuracy of 96%) based upon the level of two genes prior to treatment (one associated with immune signalling, IL6ST and the other with apoptosis, NGFRAP1) and two proliferation genes (ASPM, MCM4) at 2 weeks of therapy. The four gene signature was found to be 91% accurate in a blinded, completely independent validation dataset of patients treated with anastrozole. Matched 2 week on-treatment biopsies improved predictive power over pre-treatment biopsies alone. This signature also significantly predicted recurrence free survival (p=0.029) and breast cancer specific survival (p=0.009). We demonstrate that the test can also be performed using quantitative PCR or immunohistochemistry. Conclusion A four gene predictive model of clinical response to AIs by two weeks has been generated and validated. Deregulated immune and apoptotic responses before treatment and a failure to reduce proliferation by 2 weeks are functional characteristics of breast tumours that do not respond to AIs. 25 Pre treatment, 25 two week and 25 three month on-treatment primary breast tumour samples from the same patients. Data was analysed with two previously generated datasets, GSE55374 which was also processed on Illumina HT-12v4 BeadChips (GPL10558) and GSE20181 on Affymetrix U133A GeneChips (GPL96)
2015-07-06 | E-GEOD-59515 | biostudies-arrayexpress
Project description:Purpose: There is an unmet clinical need for biomarkers to identify breast cancer patients who are at increased risk of developing brain metastases. The objective is to identify gene signatures and biological pathways associated with HER2+ brain metastasis. Experimental Design: Gene expression of 19 HER2+ breast cancer brain metastases was compared with HER2+ nonmetastatic primary tumors. Gene Set Enrichment Analysis was used to identify a signature, which was evaluated for correlation with BRCA1 mutation status and clinical outcome using published microarray datasets and for correlation with pharmacological inhibition by a PARP inhibitor and temozolomide using published microarray datasets of breast cancer cell lines. Results: A BRCA1 Deficient-Like (BD-L) gene signature is significantly correlated with HER2+ metastases in both our and an independent cohort. BD-L signature is enriched in BRCA1 mutation carrier primary tumors and HER2-/ER- sporadic tumors, but high values are found in a subset of ER+ and HER2+ tumors. Elevated BD-L signature in primary tumors is associated with increased risk of overall relapse, brain relapse, and decreased survival. The BD-L signature correlates with pharmacologic response to PARP inhibitor and temozolomide in two independent microarray datasets, and the signature outperformed four published gene signatures of BRCA1/2 deficiency. Conclusions: The BD-L signature is enriched in breast cancer brain metastases and identifies a subset of primary tumors with increased propensity for brain metastasis. Furthermore, this signature may serve as a biomarker to identify sporadic breast cancer patients who could benefit from a therapeutic combination of PARP inhibitor and temozolomide. Gene expression of 19 HER2+ human breast cancer brain metastases was compared with gene expression of 19 HER2+ nonmetastatic primary human breast tumors.
2014-04-24 | E-GEOD-43837 | biostudies-arrayexpress
Project description:We comprehensively analyzed clinical, genomic and transcriptomic data of a cohort of 465 primary triple-negative breast cancer (TNBC). PIK3CA mutations and copy number gains of chromosome 22q11 were more frequent in our Chinese cohort than in The Cancer Genome Atlas. We classified TNBCs into four transcriptome-based subtypes: 1) luminal androgen receptor (LAR), 2) immunomodulatory (IM), 3) basal-like immune-suppressed (BLIS), and 4) mesenchymal (MES). Putative therapeutic targets or biomarkers were identified among each subtype. Importantly, the LAR subtype showed more ERBB2 somatic mutations, infrequent mutational signature 3 and frequent CDKN2A loss. The comprehensive profile of TNBCs provided here will serve as a reference to further advance the understanding and precision treatment of TNBC.
2019-03-09 | GSE118527 | GEO
Project description:Dynamics of Breast Cancer under Different Rates of Chemoradiotherapy.
Mkango SB1, Shaban N1, Mureithi E1, Ngoma T2.
Author information
1
Department of Mathematics, University of Dar es Salaam, P.O. Box 35062, Dar es Salaam, Tanzania.
2
Department of Clinical Oncology, Muhimbili University of Health and Allied Sciences, P.O. Box 65000, Dar es Salaam, Tanzania.
Abstract
A type of cancer which originates from the breast tissue is referred to as breast cancer. Globally, it is the most common cause of death in women. Treatments such as radiotherapy, chemotherapy, hormone therapy, immunotherapy, and gene therapy are the main strategies in the fight against breast cancer. The present study aims at investigating the effects of the combined radiotherapy and chemotherapy as a way to treat breast cancer, and different treatment approaches are incorporated into the model. Also, the model is fitted to data on patients with breast cancer in Tanzania. We determine new treatment strategies, and finally, we show that when sufficient amount of chemotherapy and radiotherapy with a low decay rate is used, the drug will be significantly more effective in combating the disease while health cells remain above the threshold.
Copyright © 2019 Sara B. Mkango et al.
2020-01-20 | MODEL1912120005 | BioModels
Project description:Gene expression signatures have the capacity to identify clinically significant features of breast cancer and can predict which individual patients are likely to be resistant to neoadjuvant therapy, thus providing the opportunity to guide treatment decisions. Data used in publication: Clin Cancer Res. 2006;12:819–826. 89. Dressman et.al., Gene Expression Profiles of Multiple Breast Cancer Phenotypes and Response to Neoadjuvant Chemotherapy Combining DCE-MRI imaging and genomics have identified putative genomic biomarkers that are associated with risk for pCR following neoadjuvant chemotherapy. Furthermore, IBC gene expression profiles were associated with long term overall survival. The genomic profiles identified in this pilot study are preliminary but novel, and thus of great interest to validate as biomarkers in independent datasets. 37 breast tissue samples were collected under ultrasound guidance from patients with stage IIB/III breast cancer before four cycles of neoadjuvant liposomal doxorubicinpaclitaxel chemotherapy combined with local whole breast hyperthermia. Gene expression analysis was done using Affymetrix U133 Plus 2.0 GeneChip arrays.
2014-03-31 | E-GEOD-52322 | biostudies-arrayexpress
Project description:Gene expression signatures have the capacity to identify clinically significant features of breast cancer and can predict which individual patients are likely to be resistant to neoadjuvant therapy, thus providing the opportunity to guide treatment decisions. Data used in publication: Clin Cancer Res. 2006;12:819–826. 89. Dressman et.al., Gene Expression Profiles of Multiple Breast Cancer Phenotypes and Response to Neoadjuvant Chemotherapy Combining DCE-MRI imaging and genomics have identified putative genomic biomarkers that are associated with risk for pCR following neoadjuvant chemotherapy. Furthermore, IBC gene expression profiles were associated with long term overall survival. The genomic profiles identified in this pilot study are preliminary but novel, and thus of great interest to validate as biomarkers in independent datasets.
2014-03-31 | GSE52322 | GEO
Project description:Despite the advancement of genomic classification of breast cancer, current clinical tests and treatment decisions are commonly based on protein level information. Formalin-fixed paraffin-embedded (FFPE) tissue specimens are widely available and can be directly linked to extended clinical outcomes. We performed comprehensive proteomic profiling of 300 FFPE breast cancer surgical specimens, 75 of each PAM50 subtype, with linked clinical outcomes. Using our highly sensitive SP3-Clinical Tissue Proteomics platform, we quantified 4214 proteins across all 300 samples. The analysis identified a distinct proteomic group characterized by high expression of immune response proteins and favorable survival rates. Four clinically distinct proteomic clusters within samples classified as triple negative breast cancer by immunohistochemistry had features of “basal-immune hot”, “basal-immune cold”, “mesenchymal”, and “luminal androgen receptor”. Our proteomic analysis characterizes the heterogeneity of breast cancer in a clinically-applicable manner, identifies potential biomarkers and therapeutic targets, and provides a resource for clinical breast cancer classification.
2022-02-22 | PXD024322 | Pride
Project description:Recently, expression profiling of breast carcinomas has revealed gene signatures that predict clinical outcome, and discerned prognostically relevant breast cancer subtypes. Measurement of the degree of genomic instability provides a very similar stratification of prognostic groups. We therefore hypothesized that these features are linked. We used gene expression profiling of 48 breast cancer specimens that profoundly differed in their degree of genomic instability and identified a set of 12 genes that defines the two groups. The biological and prognostic significance of this gene set was established through survival prediction in published datasets from patients with breast cancer. Of note, the gene expression signatures that define specific prognostic subtypes in other breast cancer datasets predicted genomic instability in our samples. This remarkable congruence suggests a biological dependency of poor-prognosis gene signatures, breast cancer subtypes, genomic instability, and clinical outcome. Keywords: disease state analysis 44 samples
2009-11-30 | E-GEOD-11901 | biostudies-arrayexpress
Project description:Comparison of gene expression data between control and MFP-treated C4-HD tumors. The role of active antitumor immunity in hormone receptor positive (HR+) breast cancer has been historically underlooked. The aim of this study was to determine the contribution of the immune system to antiprogestin-induced tumor growth inhibition using a hormone-dependent breast cancer model. BALB/c-GFP+ bone marrow (BM) cells were transplanted into immunodeficient NSG mice to generate an immunocompetent NSG/BM-GFP+ (NSG-R) mouse model. Treatment with the antiprogestin Mifepristone (MFP) inhibited growth of 59-2-HI tumors with similar kinetics in both animal models. Interestingly, MFP treatment reshaped the tumor microenvironment, enhancing the production of proinflammatory cytokines and chemokines. Tumors in MFP-treated immunocompetent mice showed increased infiltration of F4/80+ macrophages, NK, and CD8 T cells, displaying a central memory phenotype. Mechanistically, MFP induced immunogenic cell death in vivo and in vitro, as depicted by the expression and subcellular localization of the alarmins calreticulin and HMGB-1 and the induction of an immunogenic cell death gene program. Moreover, MFP-treated tumor cells efficiently activated immature dendritic cells, evidenced by enhanced expression of MHC-II and CD86, and induced a memory T cell response, attenuating tumor onset and growth after re-challenge. Finally, MFP treatment increased the sensitivity of HR+ 59-2-HI tumor to PD-L1 blockade, suggesting that antiprogestins may improve immunotherapy response rates. These results contribute to a better understanding of the mechanisms underlying the antitumor effect of hormonal treatment and the rational design of therapeutic combinations based on endocrine and immunomodulatory agents in HR+ breast cancer.
2020-11-07 | GSE161012 | GEO