Genetic background of different cancer cell lines influences the gene set involved in chromosome 8 mediated breast tumor suppression

2006 ◽  
Vol 45 (6) ◽  
pp. 612-627 ◽  
Author(s):  
Susanne Seitz ◽  
Eberhard Korsching ◽  
Jörg Weimer ◽  
Anja Jacobsen ◽  
Norbert Arnold ◽  
...  
Pathogens ◽  
2021 ◽  
Vol 10 (6) ◽  
pp. 641
Author(s):  
Kaitlin M. Branch ◽  
Erica C. Garcia ◽  
Yin Maggie Chen ◽  
Matthew McGregor ◽  
Mikayla Min ◽  
...  

Breast cancer is the leading cause of cancer deaths among women worldwide. There are many known risk factors for breast cancer, but the role of infectious disease remains unclear. Human cytomegalovirus (HCMV) is a widespread herpesvirus that usually causes little disease. Because HCMV has been detected in breast tumor biopsy samples and is frequently transmitted via human breast milk, we investigated HCMV replication in breast tumor cells. Four human breast cancer cell lines with different expression profiles for the key diagnostic markers of the estrogen receptor (ER), progesterone receptor (PR), and human epidermal growth factor receptor 2 (HER2), were infected with a bacterial artificial chromosome-derived HCMV clinical strain TB40/E tagged with green fluorescent protein (GFP). Fluorescence microscopy confirmed that all four breast cancer cell lines supported virus entry. RNA was isolated from infected cells and the expression of immediate early (UL123), early (UL54), and late (UL111A) genes was confirmed using PCR. Viral proteins were detected by immunoblotting, and viral progeny were produced during the infection of breast tumor cells, as evidenced by subsequent infection of fibroblasts with culture supernatants. These results demonstrate that breast tumor cells support productive HCMV infection and could indicate that HCMV replication may play a role in breast cancer progression.


2014 ◽  
Vol 4 (1) ◽  
Author(s):  
Alain R. Bateman ◽  
Nehme El-Hachem ◽  
Andrew H. Beck ◽  
Hugo J. W. L. Aerts ◽  
Benjamin Haibe-Kains

2020 ◽  
Vol 4 (1) ◽  
Author(s):  
Anne Mullin ◽  
Bertrand Jean-Claude

Breast tumor cells overexpressing the proto-oncogene HER2/neu are known to be less responsive to certain DNA-binding chemotherapeutic agents. The current study specifically investigates the correlation between chemosensitivity to the DNA-binding drug doxorubicin and cellular HER2/neu protein levels in a panel of eight breast cancer cell lines (HS-578, BT-474, MDA-MB-453, MDA-MB-231, MDA-MB-175, MCF-7, ZR-75-1 and T47D). The IC50 (the drug concentration required to inhibit cell growth by 50%) values for the cell lines were determined by the sulforhodamine B assay. IC50 values were correlated with HER2/neu protein levels determined by Western blotting. An almost linear relationship between IC50 and HER2/neu protein level for seven cell lines (p = 0.02, r2 = 0.680) was found, with protein levels increasing as resistance increased. The findings suggest that overexpression of HER2/neu correlates with increased resistance to doxorubicin in seven of eight breast cancer cell lines studied. The observation that, in one cell line (MDA-MB-175), doxorubicin IC50 did not correlate with HER2/neu levels, suggests that in these cells, an as-of-yet unidentified factor contributes to resistance. If the observed correlation, which was present in seven of eight cell lines, is confirmed in a larger sample size, increased HER2/neu levels may be implemented as a predictor of breast tumor sensitivity to doxorubicin.


2019 ◽  
Author(s):  
James H. Joly ◽  
William E. Lowry ◽  
Nicholas A. Graham

AbstractGene Set Enrichment Analysis (GSEA) is an algorithm widely used to identify statistically enriched gene sets in transcriptomic data. However, to our knowledge, there exists no method for examining the enrichment of two gene sets relative to one another. Here, we present Differential Gene Set Enrichment Analysis (DGSEA), an adaptation of GSEA that assesses the relative enrichment of two gene sets. Using the metabolic pathways glycolysis and oxidative phosphorylation as an example, we demonstrate that DGSEA accurately captures the hypoxia-induced shift towards glycolysis. We also show that DGSEA is more predictive than GSEA of the metabolic state of cancer cell lines, including lactate secretion and intracellular concentrations of lactate and AMP. Furthermore, we demonstrate that DGSEA identifies novel metabolic dependencies not found by GSEA in cancer cell lines. Together, these data demonstrate that DGSEA is a novel tool to examine the relative enrichment of two gene sets.


2003 ◽  
Vol 143 (2) ◽  
pp. 100-112 ◽  
Author(s):  
Peter Wilson ◽  
Andrew Cuthbert ◽  
Anna Marsh ◽  
Jeremy Arnold ◽  
James Flanagan ◽  
...  

1992 ◽  
Vol 5 (1) ◽  
pp. 91-95 ◽  
Author(s):  
Kai Van Der Bosch ◽  
Ilona Becker ◽  
Larisa Savelyeva ◽  
Silke Brüderlein ◽  
Peter Schlag ◽  
...  

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