scholarly journals Mitochondrial DNA Affects the Expression of Nuclear Genes Involved in Immune and Stress Responses in a Breast Cancer Model

2020 ◽  
Vol 11 ◽  
Author(s):  
Carole Grasso ◽  
David A. Eccles ◽  
Stepana Boukalova ◽  
Marie-Sophie Fabre ◽  
Rebecca H. Dawson ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Gene Expression ◽  
Tumor Cells ◽  
Stress Responses ◽  
Communication Systems ◽  
Nuclear Genes ◽  
Host Cells ◽  
Differentially Expressed ◽  
Mitochondrial Transfer ◽  
Metabolic Remodeling

Tumor cells without mitochondrial (mt) DNA (ρ0 cells) are auxotrophic for uridine, and their growth is supported by pyruvate. While ATP synthesis in ρ0 cells relies on glycolysis, they fail to form tumors unless they acquire mitochondria from stromal cells. Mitochondrial acquisition restores respiration that is essential for de novo pyrimidine biosynthesis and for mitochondrial ATP production. The physiological processes that underpin intercellular mitochondrial transfer to tumor cells lacking mtDNA and the metabolic remodeling and restored tumorigenic properties of cells that acquire mitochondria are not well understood. Here, we investigated the changes in mitochondrial and nuclear gene expression that accompany mtDNA deletion and acquisition in metastatic murine 4T1 breast cancer cells. Loss of mitochondrial gene expression in 4T1ρ0 cells was restored in cells recovered from subcutaneous tumors that grew from 4T1ρ0 cells following acquisition of mtDNA from host cells. In contrast, the expression of most nuclear genes that encode respiratory complex subunits and mitochondrial ribosomal subunits was not greatly affected by loss of mtDNA, indicating ineffective mitochondria-to-nucleus communication systems for these nuclear genes. Further, analysis of nuclear genes whose expression was compromised in 4T1ρ0 cells showed that immune- and stress-related genes were the most highly differentially expressed, representing over 70% of those with greater than 16-fold higher expression in 4T1 compared with 4T1ρ0 cells. The monocyte recruiting chemokine, Ccl2, and Psmb8, a subunit of the immunoproteasome that generates MHCI-binding peptides, were the most highly differentially expressed. Early monocyte/macrophage recruitment into the tumor mass was compromised in 4T1ρ0 cells but recovered before mtDNA could be detected. Taken together, our results show that mitochondrial acquisition by tumor cells without mtDNA results in bioenergetic remodeling and re-expression of genes involved in immune function and stress adaptation.

Gene expression differences between disseminated tumor cells and tumor cells from overt bone metastases in patients with metastatic breast cancer

2009 ◽  
Vol 27 (15_suppl) ◽  
pp. 1040-1040
Author(s):  
R. J. Broom ◽  
E. Amir ◽  
T. Cawthorn ◽  
O. Freedman ◽  
D. Gianfelice ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Gene Expression ◽  
Bone Marrow ◽  
Bone Metastases ◽  
Tumor Cells ◽  
Disseminated Tumor Cells ◽  
Genetic Alterations ◽  
Differentially Expressed ◽  
Primary Tumors ◽  
Ct Guided

1040 Background: Despite extensive work evaluating molecular differences between primary tumors, circulating tumor cells, disseminated tumor cells (DTCs) and established metastases, it is not apparent which genetic alterations are required to form viable, independent bone metastases (BM). A major limitation in exploring the genetic differences between DTCs and established BM is the paucity of fresh BM tissue available. Methods: Ten breast cancer patients with BM underwent a CT-guided BM biopsy and a bone marrow aspiration (for DTCs). Tumor cells were enriched by immunomagnetic separation and RNA was extracted from each sample. Gene expression profiling was conducted using Illumina Human Ref-8 bead arrays. Microarray data was analyzed using BeadStudio software to identify differentially expressed genes. Ingenuity Pathway Analysis software was used to identify genes integral to specific pathways involved in tumor dissemination. Results: The yield of analyzable malignant cells from BM and bone marrow aspirates was 60% and 80%, respectively. A signature of 133 genes was identified that was differentially expressed between the two sample types. Paired analysis of samples from the same patients identified a subset of 161 genes, of which 52 overlapped with the initial unmatched signature. Several genes relevant to breast cancer metastasis to bone (i.e., osteopontin, CTGF, parathyroid hormone receptor, EGFR) were significantly over-expressed in the BM compared to the DTCs. Conclusions: Results suggest that there are specific subsets of genes, which are required for DTCs in the bone marrow to form overt BM. A number of genes identified are already known to participate in osteolytic BM formation. This signature may allow identification of patients at increased risk for developing BM. No significant financial relationships to disclose.

scholarly journals Key Genes and Prognostic Analysis in HER2+ Breast Cancer

2021 ◽  
Vol 20 ◽  
pp. 153303382098329
Author(s):  
Yujie Weng ◽  
Wei Liang ◽  
Yucheng Ji ◽  
Zhongxian Li ◽  
Rong Jia ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Gene Expression ◽  
Differentially Expressed Genes ◽  
Protein Interaction ◽  
Differentially Expressed ◽  
Protein Kinase Activity ◽  
Protein Protein Interaction ◽  
Risk Of Death ◽  
Her2 Breast Cancer ◽  
Key Genes

Human epidermal growth factor 2 (HER2)+ breast cancer is considered the most dangerous type of breast cancers. Herein, we used bioinformatics methods to identify potential key genes in HER2+ breast cancer to enable its diagnosis, treatment, and prognosis prediction. Datasets of HER2+ breast cancer and normal tissue samples retrieved from Gene Expression Omnibus and The Cancer Genome Atlas databases were subjected to analysis for differentially expressed genes using R software. The identified differentially expressed genes were subjected to gene ontology and Kyoto Encyclopedia of Genes and Genomes pathway enrichment analyses followed by construction of protein-protein interaction networks using the STRING database to identify key genes. The genes were further validated via survival and differential gene expression analyses. We identified 97 upregulated and 106 downregulated genes that were primarily associated with processes such as mitosis, protein kinase activity, cell cycle, and the p53 signaling pathway. Visualization of the protein-protein interaction network identified 10 key genes ( CCNA2, CDK1, CDC20, CCNB1, DLGAP5, AURKA, BUB1B, RRM2, TPX2, and MAD2L1), all of which were upregulated. Survival analysis using PROGgeneV2 showed that CDC20, CCNA2, DLGAP5, RRM2, and TPX2 are prognosis-related key genes in HER2+ breast cancer. A nomogram showed that high expression of RRM2, DLGAP5, and TPX2 was positively associated with the risk of death. TPX2, which has not previously been reported in HER2+ breast cancer, was associated with breast cancer development, progression, and prognosis and is therefore a potential key gene. It is hoped that this study can provide a new method for the diagnosis and treatment of HER2 + breast cancer.

scholarly journals A shared gene expression signature in mouse models of EBV-associated and non–EBV-associated Burkitt lymphoma

Blood ◽  
2011 ◽  
Vol 118 (26) ◽  
pp. 6849-6859 ◽  
Author(s):  
Kathryn T. Bieging ◽  
Kamonwan Fish ◽  
Subbarao Bondada ◽  
Richard Longnecker
Keyword(s):  
Gene Expression ◽  
B Cells ◽  
Mouse Model ◽  
Tumor Cells ◽  
Burkitt Lymphoma ◽  
Gene Expression Signature ◽  
Differentially Expressed ◽  
Cell Phenotype ◽  
Phenotypic Differences ◽  
Tumor Onset

AbstractThe link between EBV infection and Burkitt lymphoma (BL) is strong, but the mechanism underlying that link has been elusive. We have developed a mouse model for EBV-associated BL in which LMP2A, an EBV latency protein, and MYC are expressed in B cells. Our model has demonstrated the ability of LMP2A to accelerate tumor onset, increase spleen size, and bypass p53 inactivation. Here we describe the results of total gene expression analysis of tumor and pretumor B cells from our transgenic mouse model. Although we see many phenotypic differences and changes in gene expression in pretumor B cells, the transcriptional profiles of tumor cells from LMP2A/λ-MYC and λ-MYC mice are strikingly similar, with fewer than 20 genes differentially expressed. We evaluated the functional significance of one of the most interesting differentially expressed genes, Egr1, and found that it was not required for acceleration of tumor onset by LMP2A. Our studies demonstrate the remarkable ability of LMP2A to affect the pretumor B-cell phenotype and tumorigenesis without substantially altering gene expression in tumor cells.

scholarly journals Differential expression of cyclin A2 in triple negative breast cancer.

2021 ◽  
Author(s):  
Shahan Mamoor
Keyword(s):  
Breast Cancer ◽  
Overall Survival ◽  
Differential Expression ◽  
Tumor Cells ◽  
Triple Negative Breast Cancer ◽  
Triple Negative ◽  
Differentially Expressed ◽  
Primary Tumors ◽  
Ductal Cells ◽  
Cyclin A2

Women diagnosed with triple negative breast cancer can benefit neither from endocrine therapy nor from HER2-targeted therapies (1). We mined published microarray datasets (2, 3) to determine in an unbiased fashion and at the systems level genes most differentially expressed in the primary tumors of patients with breast cancer. We report here significant differential expression of the gene encoding cyclin A2, CCNA2, when comparing the tumor cells of patients with triple negative breast cancer to normal mammary ductal cells (2). CCNA2 was also differentially expressed in bulk tumor in human breast cancer (3). CCNA2 mRNA was present at significantly increased quantities in TNBC tumor cells relative to normal mammary ductal cells. Analysis of human survival data revealed that expression of CCNA2 in primary tumors of the breast was correlated with overall survival in patients with basal-like type cancer, while within triple negative breast cancer, primary tumor expression of CCNA2 was correlated with overall survival in patients with basal-like 1, basal-like 2, and mesenchymal subtype disease. CCNA2 may be of relevance to initiation, maintenance or progression of triple negative breast cancers.

scholarly journals Integrative transcriptome data mining for identification of core lncRNAs in breast cancer

PeerJ ◽  
2019 ◽  
Vol 7 ◽  
pp. e7821 ◽  
Author(s):  
Xiaoming Zhang ◽  
Jing Zhuang ◽  
Lijuan Liu ◽  
Zhengguo He ◽  
Cun Liu ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Gene Expression ◽  
Prognostic Value ◽  
Early Stage ◽  
Expression Profiles ◽  
Diagnostic Value ◽  
The Cancer Genome Atlas ◽  
Functional Enrichment ◽  
Differentially Expressed ◽  
Data Set

Background Cumulative evidence suggests that long non-coding RNAs (lncRNAs) play an important role in tumorigenesis. This study aims to identify lncRNAs that can serve as new biomarkers for breast cancer diagnosis or screening. Methods First, the linear fitting method was used to identify differentially expressed genes from the breast cancer RNA expression profiles in The Cancer Genome Atlas (TCGA). Next, the diagnostic value of all differentially expressed lncRNAs was evaluated using a receiver operating characteristic (ROC) curve. Then, the top ten lncRNAs with the highest diagnostic value were selected as core genes for clinical characteristics and prognosis analysis. Furthermore, core lncRNA-mRNA co-expression networks based on weighted gene co-expression network analysis (WGCNA) were constructed, and functional enrichment analysis was performed using the Database for Annotation, Visualization and Integrated Discovery (DAVID). The differential expression level and diagnostic value of core lncRNAs were further evaluated by using independent data set from Gene Expression Omnibus (GEO). Finally, the expression status and prognostic value of core lncRNAs in various tumors were analyzed based on Gene Expression Profiling Interactive Analysis (GEPIA). Results Seven core lncRNAs (LINC00478, PGM5-AS1, AL035610.1, MIR143HG, RP11-175K6.1, AC005550.4, and MIR497HG) have good single-factor diagnostic value for breast cancer. AC093850.2 has a prognostic value for breast cancer. AC005550.4 and MIR497HG can better distinguish breast cancer patients in early-stage from the advanced-stage. Low expression of MAGI2-AS3, LINC00478, AL035610.1, MIR143HG, and MIR145 may be associated with lymph node metastasis in breast cancer. Conclusion Our study provides candidate biomarkers for the diagnosis and prognosis of breast cancer, as well as a bioinformatics basis for the further elucidation of the molecular pathological mechanism of breast cancer.

PP 83 Gene expression profiling of circulating tumor cells in breast cancer

2011 ◽  
Vol 47 ◽  
pp. S12-S13
Author(s):  
V. Cappelletti ◽  
E. Fina ◽  
P. Miodini ◽  
M. Callari ◽  
V. Musella ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Gene Expression ◽  
Gene Expression Profiling ◽  
Tumor Cells ◽  
Circulating Tumor Cells ◽  
Expression Profiling

scholarly journals Gene Expression Signatures in Circulating Tumor Cells Correlate with Response to Therapy in Metastatic Breast Cancer

2017 ◽  
Vol 63 (10) ◽  
pp. 1585-1593 ◽  
Author(s):  
Maren Bredemeier ◽  
Philippos Edimiris ◽  
Pawel Mach ◽  
Mikael Kubista ◽  
Robert Sjöback ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Gene Expression ◽  
Metastatic Breast Cancer ◽  
Disease Progression ◽  
Tumor Cells ◽  
Circulating Tumor Cells ◽  
Metastatic Breast ◽  
Response To Therapy ◽  
Clinical Staging ◽  
Significant Differential Expression

Abstract BACKGROUND Circulating tumor cells (CTCs) are thought to be an ideal surrogate marker to monitor disease progression in metastatic breast cancer (MBC). We investigated the prediction of treatment response in CTCs of MBC patients on the basis of the expression of 46 genes. METHODS From 45 MBC patients and 20 healthy donors (HD), 2 × 5 mL of blood was collected at the time of disease progression (TP0) and at 2 consecutive clinical staging time points (TP1 and TP2) to proceed with the AdnaTest EMT-2/StemCellSelectTM (QIAGEN). Patients were grouped into (a) responder (R) and non-responder (NR) at TP1 and (b) overall responder (OR) and overall non-responder (ONR) at TP2. A 46-gene PCR assay was used for preamplification and high-throughput gene expression profiling. Data were analyzed by use of GenEx (MultiD) and SAS. RESULTS The CTC positivity was defined by the four-gene signature (EPCAM, KRT19, MUC1, ERBB2 positivity). Fourteen genes were identified as significantly differentially expressed between CTC+ and CTC− patients (KRT19, FLT1, EGFR, EPCAM, GZMM, PGR, CD24, KIT, PLAU, ALDH1A1, CTSD, MKI67, TWIST1, and ERBB2). KRT19 was highly expressed in CTC+ patients and ADAM17 in the NR at TP1. A significant differential expression of 4 genes (KRT19, EPCAM, CDH1, and SCGB2A2) was observed between OR and ONR when stratifying the samples into CTC+ or CTC−. CONCLUSIONS ADAM17 could be a key marker in distinguishing R from NR, and KRT19 was powerful in identifying CTCs.

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