scholarly journals Distinct gene expression profiles between primary breast cancers and brain metastases from pair-matched samples

2019 ◽  
Vol 9 (1) ◽  
Author(s):  
Takayuki Iwamoto ◽  
Naoki Niikura ◽  
Rin Ogiya ◽  
Hiroyuki Yasojima ◽  
Ken-ichi Watanabe ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Gene Expression ◽  
Brain Metastases ◽  
Therapeutic Target ◽  
Target Genes ◽  
Expression Profiles ◽  
Gene Expression Profiles ◽  
Breast Cancers ◽  
Mesenchymal Transition ◽  
Matched Samples

Abstract Our objectives were to determine whether clinic-pathological markers and immune-related gene signatures in breast cancer exhibit any change upon brain metastasis and whether previously reported genes significantly associated with brain metastases and the epithelial-mesenchymal transition (EMT) were reproducible and consistent in our dataset. Sixteen pair-matched samples from primary breast cancers and brain metastases diagnosed were collected from the Japan Clinical Oncology Group Breast Cancer Study Group. Gene expression profiles for immune-, brain metastases-, and EMT-related genes were compared between primary breast cancers and brain metastases. Potential therapeutic target genes of 41 FDA-approved or under-investigation agents for brain metastases were explored. Immune-related signatures exhibited significantly lower gene expression in brain metastases than in primary breast cancers. No significant differences were detected for the majority of genes associated with brain metastases and EMT in the two groups. Among 41 therapeutic target candidates, VEGFA and DNMT3A demonstrated significantly higher gene expression in brain metastases. We found that distinct patterns of gene expression exist between primary breast cancers and brain metastases. Further studies are needed to explore whether these distinct expression profiles derive from or underlie disease status and compare these features between metastases to the brain and other sites.

scholarly journals ”BIK/NBK Gene Expression as a Possible Marker of Circulating Breast Cancer Cells in Blood“

2011 ◽  
Vol 4 (1) ◽  
pp. 8-14
Author(s):  
E. Lopez-Munoz ◽  
N. Garcia-Hernandez ◽  
R. I. Penaloza-Espinosa ◽  
M. E. Gomez-Del Toro ◽  
G. Zarco-Espinosa ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Gene Expression ◽  
Cancer Cells ◽  
Therapeutic Target ◽  
Breast Cancer Cells ◽  
Expression Profiles ◽  
Gene Expression Profiles ◽  
Breast Cancer Tissue ◽  
Cancer Tissue ◽  
Mrna Gene

The detection of circulating breast cancer cells in blood could be of special interest as an indicator of diagnosis and prognosis, and for the selection of treatment. In a previous report, our research group determined gene expression profiles in samples of breast cancer tissue, identifying over-expression of the BIK/NBK mRNA gene in 90% of the analyzed samples. In this paper, we analyze the BIK/NBK gene expression as a possible biomarker of circulating breast cancer cells in blood. We demonstrate that the BIK/NBK gene expression is not a significant biomarker in the detection of circulating breast cancer cells in the blood of women with breast cancer. Several studies have evaluated the regulation of apoptosis by estrogens in breast cancer cells, demonstrating the importance of BIK/NBK protein, in estrogen-regulated breast cancer cell apoptosis, which suggests that the regulation of its expression may be an important therapeutic target or strategy in the management of cancer, and, although we did not find statistically significant differences among the patient groups to demonstrate that BIK/NBK gene expression is a biomarker of circulating breast cancer cells in blood, we consider it necessary to continue the study of this gene in breast cancer tissue and its role in the development and progression of breast cancer, its prognostic value, and its potential use as therapeutic target.

scholarly journals A novel immune subtype classification of ER-positive, PR-negative and HER2-negative breast cancer based on the genomic and transcriptomic landscape

2021 ◽  
Vol 19 (1) ◽  
Author(s):  
Peiling Xie ◽  
Rui An ◽  
Shibo Yu ◽  
Jianjun He ◽  
Huimin Zhang
Keyword(s):  
Breast Cancer ◽  
Gene Expression ◽  
Clinical Outcomes ◽  
Immune Escape ◽  
Expression Profiles ◽  
Gene Expression Profiles ◽  
Molecular Characteristics ◽  
Consensus Clustering ◽  
Breast Cancers ◽  
Her2 Breast Cancer

Abstract Background The diversity and plasticity behind ER+/PR−/HER2− breast cancer have not been widely explored. It is essential to identify heterogeneous microenvironment phenotypes and investigate specific genomic events driving the formation of these phenotypes. Methods Based on the immune-related gene expression profiles of 411 ER+/PR−/HER2− breast cancers in the METABRIC cohort, we used consensus clustering to identify heterogeneous immune subtypes and assessed their reproducibility in an independent meta-cohort including 135 patients collected from GEO database. We further analyzed the differences of cellular and molecular characteristics, and potential immune escape mechanism among immune subtypes. In addition, we constructed a transcriptional trajectory to visualize the distribution of individual patient. Results Our analysis identified and validated five reproducible immune subtypes with distinct cellular and molecular characteristics, potential immune escape mechanisms, genomic drivers, as well as clinical outcomes. An immune-cold subtype, with the least amount of lymphocyte infiltration, had a poorer prognosis. By contrast, an immune-hot subtype, which demonstrated the highest infiltration of CD8+ T cells, DCs and NK cells, and elevated IFN-γ response, had a comparatively favorable prognosis. Other subtypes showed more diverse gene expression and immune infiltration patterns with distinct clinical outcomes. Finally, our analysis revealed a complex immune landscape consisting of both discrete cluster and continuous spectrum. Conclusion Overall, this study revealed five heterogeneous immune subtypes among ER+/PR–/HER2− breast cancer, also provided important implications for clinical translations.

scholarly journals Identification and characterization of critical genes associated with tamoxifen resistance in breast cancer

PeerJ ◽  
2020 ◽  
Vol 8 ◽  
pp. e10468
Author(s):  
Kai Zhang ◽  
Kuikui Jiang ◽  
Ruoxi Hong ◽  
Fei Xu ◽  
Wen Xia ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Gene Expression ◽  
Target Genes ◽  
Expression Profiles ◽  
Tamoxifen Resistance ◽  
Gene Expression Profiles ◽  
Gene Expression Omnibus ◽  
Ppi Network ◽  
Hub Genes ◽  
Mcf 7

Background Tamoxifen resistance in breast cancer is an unsolved problem in clinical practice. The aim of this study was to determine the potential mechanisms of tamoxifen resistance through bioinformatics analysis. Methods Gene expression profiles of tamoxifen-resistant MCF-7/TR and MCF-7 cells were acquired from the Gene Expression Omnibus dataset GSE26459, and differentially expressed genes (DEGs) were detected with R software. We conducted Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes pathway enrichment analyses using Database for Annotation, Visualization and Integrated Discovery. A protein–protein interaction (PPI) network was generated, and we analyzed hub genes in the network with the Search Tool for the Retrieval of Interacting Genes database. Finally, we used siRNAs to silence the target genes and conducted the MTS assay. Results We identified 865 DEGs, 399 of which were upregulated. GO analysis indicated that most genes are related to telomere organization, extracellular exosomes, and binding-related items for protein heterodimerization. PPI network construction revealed that the top 10 hub genes—ACLY, HSPD1, PFAS, GART, TXN, HSPH1, HSPE1, IRAS, TRAP1, and ATIC—might be associated with tamoxifen resistance. Consistently, RT-qPCR analysis indicated that the expression of these 10 genes was increased in MCF-7/TR cells comparing with MCF-7 cells. Four hub genes (TXN, HSPD1, HSPH1 and ATIC) were related to overall survival in patients who accepted tamoxifen. In addition, knockdown of HSPH1 by siRNA may lead to reduced growth of MCF-7/TR cell with a trend close to significance (P = 0.07), indicating that upregulation of HSPH1 may play a role in tamoxifen resistance. Conclusion This study revealed a number of critical hub genes that might serve as therapeutic targets in breast cancer resistant to tamoxifen and provided potential directions for uncovering the mechanisms of tamoxifen resistance.

scholarly journals Integrative Analysis with Monte Carlo Cross-Validation Reveals miRNAs Regulating Pathways Cross-Talk in Aggressive Breast Cancer

2015 ◽  
Vol 2015 ◽  
pp. 1-17 ◽  
Author(s):  
Antonio Colaprico ◽  
Claudia Cava ◽  
Gloria Bertoli ◽  
Gianluca Bontempi ◽  
Isabella Castiglioni
Keyword(s):  
Breast Cancer ◽  
Gene Expression ◽  
Cross Talk ◽  
Target Genes ◽  
Expression Profiles ◽  
Gene Expression Profiles ◽  
Integrated Approach ◽  
Random Forest Classification ◽  
Forest Classification ◽  
Stem Cell Pluripotency

In this work an integrated approach was used to identify functional miRNAs regulating gene pathway cross-talk in breast cancer (BC). We first integrated gene expression profiles and biological pathway information to explore the underlying associations between genes differently expressed among normal and BC samples and pathways enriched from these genes. For each pair of pathways, a score was derived from the distribution of gene expression levels by quantifying their pathway cross-talk. Random forest classification allowed the identification of pairs of pathways with high cross-talk. We assessed miRNAs regulating the identified gene pathways by a mutual information analysis. A Fisher test was applied to demonstrate their significance in the regulated pathways. Our results suggest interesting networks of pathways that could be key regulatory of target genes in BC, including stem cell pluripotency, coagulation, and hypoxia pathways and miRNAs that control these networks could be potential biomarkers for diagnostic, prognostic, and therapeutic development in BC. This work shows that standard methods of predicting normal and tumor classes such as differentially expressed miRNAs or transcription factors could lose intrinsic features; instead our approach revealed the responsible molecules of the disease.

Gene expression profiling can predict pathological complete response (pCR) to anthracycline-based therapy in estrogen- receptor (ER) negative breast cancer (BC) patients

2007 ◽  
Vol 25 (18_suppl) ◽  
pp. 10564-10564
Author(s):  
C. Desmedt ◽  
F. André ◽  
E. Azambuja ◽  
B. Haibe-Kains ◽  
D. Larsimont ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Gene Expression ◽  
Expression Profiles ◽  
Single Agent ◽  
Gene Expression Profiles ◽  
Molecular Transport ◽  
Complete Response ◽  
Dominant Factor ◽  
Breast Cancers ◽  
Two Samples

10564 Background: Breast cancers show variable sensitivity to anthracycline (A)-based therapy. Here we aimed to identify gene expression profiles associated with pCR to this treatment. As it has repeatedly and consistently been shown that ER is the most dominant factor influencing the molecular composition of breast cancer, defining different types of BC disease and because we wanted to eliminate the confounding effect of indirect ovarian suppression in ER+ BC, we focused in this study on ER-negative patients only. Methods: We analyzed Affymetrix gene expression profiles generated from 132 ER- pre-treatment samples, constituting the largest series of ER- preoperatively A-treated BC (n=132/35 pCR). Sixty-two samples derived from the prospective multicentric TOP trial (epirubicin single-agent), 41 from Institut G. Roussy (retrospective selection/ FEC) and 27 from MD Anderson (prospective study/ FAC). Results: A student t- test analysis on the combined population of A-treated pts was performed identifying 102 genes that were significantly associated with pCR (p<.01). These genes were mainly involved in cell death, DNA replication and recombination, molecular transport, cell cycle and morphology. Interestingly, 14 of these genes were located on the topoIIa amplicon. Of interest, none of these 14 genes seem to carry any prognostic value in untreated ER- pts (N=161). When we considered gene expression indices for specific A-targets such as topoIIa and helicase, we found that both were associated with pCR. However, subgroup analysis revealed that topoIIa index was predictive in ERBB2+ but not in ERBB2- subgroup. None of the genes from the adriamycin predictor (Potti et al.) or the p53 signature (Miller et al.) were significantly associated with pCR. Conclusions: This study suggests that a group of genes associated with topoIIa can identify ER-negative BC pts likely to respond to A-based therapy. These promising results are currently being validated in a larger series. No significant financial relationships to disclose.

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