Abstract
Breast cancer is the first in incidence and the second in death among all solid tumors occurring in women. The identification of molecular genetic abnormalities in breast cancer is important to improve the results of treatment. In the present study, we analyzed microarray data of breast cancer expression profiling (NCBI GEO database, accession GSE65194), focusing on Na +/K +-ATPase coding genes. We found overexpression of the ATP1A1 and down-regulation of the ATP1A2. We expect that our research could help to improve the understanding of predictive and prognostic features of breast cancer.
Keywords: breast cancer, Na+/K+-ATPase, gene expression, abnormality, ATP1A1, ATP1A2
Introduction
Breast cancer is one of the most common and deadly female solid tumors 1. According to reports from Perou et al. 2, further confirmed by other investigators 3, 4, breast cancer is a highly molecularly heterogeneous disease. The identification of molecular genetic abnormalities in breast cancer is important to improve the results of treatment and, for instance, to reveal new targets for specific therapies. Recent studies based on original retrospective analysis of digitalis use in breast cancer patients have demonstrated the anticancer effect of cardiac glycosides 5 that directly inhibit Na +/K +-ATPase (NKA) activity. NKA signaling functions after interaction with cardiac glycosides were also shown 6. It seems rational that expression of NKA might influence breast cancer prognosis.
NKA is a significant integral membrane protein. NKA’s main function is the creation and maintenance of electrochemical gradients for sodium and potassium ions in the living cell. These gradients have critical importance for control of cell volume, osmolarity and resting potential 7, 8. The minimal functional NKA consists of two associated alpha- and beta- subunits. The catalytic alpha-subunit is responsible for conversion of ATP energy to transport of Na + and K + across cell membranes and has ATP and cardiac glycosides binding sites. It may be present in human tissues in four different isoforms (α1, α2, α3, α4 – found only in testicles). The beta-subunit is responsible for delivery and insertion of alpha one in cell membranes and has three distinct isoforms in humans (β1, β2, β3) 8– 10. NKA subunits are variably expressed in different human tissues 11. Changes in the relative expression between different isoforms are associated with a number of pathological processes including malignant transformation 12, 13. Both down- and up-regulation of alpha- and beta- subunits were shown in solid tumors of different origin 14– 19.
In the present study, we analyzed public breast cancer expression profiles made using Affymetrix Human Genome U133 Plus 2.0 Array (NCBI GEO database 20, accession GSE65194) for the expression of alpha subunits of NKA. We found abnormalities in ATP1A1 (coding α1-subunit) and ATP1A2 (coding α2-subunit) expression ( Table 1) in breast cancer samples relative to their expression in normal breast tissue. ATP1A1 was overexpressed approximately 1.5 times in all groups of breast cancer samples (p<0.05). Coincidently, ATP1A2 expression decreased by more than 2 times (p<0.05). There were no differences observed in the expression of ATP1A3 (coding α3-subunit).
Table 1. NKA genes expression in breast cancer samples relative to normal breast tissue.
| Breast cancer
group |
Lum A | Lum B | Her2 | TNBC |
|---|---|---|---|---|
| Gene | Relative expression/(ANOVA P-value) | |||
| ATP1A1 | 1.53
(0.009016) |
1.38
(0.04454) |
1.66
(0.005926) |
1.44
(0.015725) |
| ATP1A2 | -2.49
(1.85·10 -07) |
-2.52
(8.50·10 -09) |
-2.78
(5.48·10 -08) |
-2.87
(2.08·10-11) |
| ATP1A3 | -1.05
(0.429089) |
1.03
(0.308298) |
-1.04
(0.768041) |
-1.04
(0.527878) |
Methods
Preanalytical procedures consisted of a robust multichip analysis (RMA) algorithm 21, including background correction, probe set signal integration, and quantile normalization. For this purpose, we used Expression Console 1.4 software (Affymetrix, Inc. USA). We utilized Transcriptome Analysis Console 3.0 software (Affymetrix, Inc. USA) to analyze the obtained CHP files and to detect differentially expressed genes using one-way between subjects ANOVA. Array data for 41 triple negative samples (TNBC group), 30 Her2-positive (Her2 group), 30 Luminal B (Lum B group), 29 Luminal A (Lum A group) breast cancer samples and 11 normal breast tissue samples were investigated.
Conclusions
Using a public microarray dataset we found abnormalities in the expression of ATP1A1 and ATP1A2 in breast cancer samples. This may correlate with digitalis anticancer activity, but requires additional research. We expect that our research could help to improve the understanding of predictive and prognostic features of breast cancer.
Data and software availability
Raw data for Table 1 are available at:
https://www.ncbi.nlm.nih.gov/geo/download/?acc=GSE65194&format=file 22.
Expression Console 1.4 software and Transcriptome Analysis Console 3.0 software (Affymetrix, Inc. USA) are available after free customer registration at:
http://www.affymetrix.com/support/technical/software_downloads.affx.
Funding Statement
This work was supported by The Ministry of Education and Science of Russian Federation (unique identifier of applied research: RFMEFI60414X0070).
[version 1; referees: 2 approved]
References
- 1. Siegel RL, Miller KD, Jemal A: Cancer statistics, 2016. CA Cancer J Clin. 2016;66(1):7–30. 10.3322/caac.21332 [DOI] [PubMed] [Google Scholar]
- 2. Perou CM, Sørlie T, Eisen MB, et al. : Molecular portraits of human breast tumours. Nature. 2000;406(6797):747–52. 10.1038/35021093 [DOI] [PubMed] [Google Scholar]
- 3. Sørlie T, Perou CM, Tibshirani R, et al. : Gene expression patterns of breast carcinomas distinguish tumor subclasses with clinical implications. Proc Natl Acad Sci U S A. 2001;98(19):10869–74. 10.1073/pnas.191367098 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 4. Sørlie T, Tibshirani R, Parker J, et al. : Repeated observation of breast tumor subtypes in independent gene expression data sets. Proc Natl Acad Sci U S A. 2003;100(14):8418–23. 10.1073/pnas.0932692100 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 5. Prassas I, Diamandis EP: Novel therapeutic applications of cardiac glycosides. Nat Rev Drug Discov. 2008;7(11):926–35. 10.1038/nrd2682 [DOI] [PubMed] [Google Scholar]
- 6. Schoner W, Scheiner-Bobis G: Endogenous and exogenous cardiac glycosides: their roles in hypertension, salt metabolism, and cell growth. Am J Physiol Cell Physiol. 2007;293(2):C509–C36. 10.1152/ajpcell.00098.2007 [DOI] [PubMed] [Google Scholar]
- 7. Skou JC: The influence of some cations on an adenosine triphosphatase from peripheral nerves. Biochim Biophys Acta. 1957;23(2):394–401. 10.1016/0006-3002(57)90343-8 [DOI] [PubMed] [Google Scholar]
- 8. Skou JC, Esmann M: The Na,K-ATPase. J Bioenerg Biomembr. 1992;24(3):249–61. [DOI] [PubMed] [Google Scholar]
- 9. McDonough AA, Geering K, Farley RA: The sodium pump needs its beta subunit. FASEB J. 1990;4(6):1598–605. [DOI] [PubMed] [Google Scholar]
- 10. Mercer RW: Structure of the Na,K-ATPase. Int Rev Cytol. 1993;137C:139–68. [PubMed] [Google Scholar]
- 11. Blanco G, Mercer RW: Isozymes of the Na-K-ATPase: heterogeneity in structure, diversity in function. Am J Physiol. 1998;275(5 Pt 2):F633–50. [DOI] [PubMed] [Google Scholar]
- 12. Babula P, Masarik M, Adam V, et al. : From Na+/K+-ATPase and cardiac glycosides to cytotoxicity and cancer treatment. Anticancer Agents Med Chem. 2013;13(7):1069–87. 10.2174/18715206113139990304 [DOI] [PubMed] [Google Scholar]
- 13. Suhail M: Na(+), K(+)-ATPase: Ubiquitous Multifunctional Transmembrane Protein and its Relevance to Various Pathophysiological Conditions. J Clin Med Res. 2010;2(1):1–17. 10.4021/jocmr2010.02.263w [DOI] [PMC free article] [PubMed] [Google Scholar]
- 14. Suñol M, Cusi V, Cruz O, et al. : Immunohistochemical analyses of alpha1 and alpha3 Na+/K+-ATPase subunit expression in medulloblastomas. Anticancer Res. 2011;31(3):953–8. [PubMed] [Google Scholar]
- 15. Rajasekaran SA, Huynh TP, Wolle DG, et al. : Na,K-ATPase subunits as markers for epithelial-mesenchymal transition in cancer and fibrosis. Mol Cancer Ther. 2010;9(6):1515–24. 10.1158/1535-7163.mct-09-0832 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 16. Inge LJ, Rajasekaran SA, Yoshimoto K, et al. : Evidence for a potential tumor suppressor role for the Na,K-ATPase beta1-subunit. Histol Histopathol. 2008;23(4):459–67. 10.14670/HH-23.459 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 17. Espineda C, Seligson DB, James Ball W, Jr, et al. : Analysis of the Na,K-ATPase alpha- and beta-subunit expression profiles of bladder cancer using tissue microarrays. Cancer. 2003;97(8):1859–68. 10.1002/cncr.11267 [DOI] [PubMed] [Google Scholar]
- 18. Rajasekaran SA, Ball WJ, Jr, Bander NH, et al. : Reduced expression of beta-subunit of Na,K-ATPase in human clear-cell renal cell carcinoma. J Urol. 1999;162(2):574–80. 10.1016/S0022-5347(05)68629-6 [DOI] [PubMed] [Google Scholar]
- 19. Mijatovic T, Ingrassia L, Facchini V, et al. : Na+/K+-ATPase alpha subunits as new targets in anticancer therapy. Expert Opin Ther Targets. 2008;12(11):1403–17. 10.1517/14728222.12.11.1403 [DOI] [PubMed] [Google Scholar]
- 20. Edgar R, Domrachev M, Lash AE: Gene Expression Omnibus: NCBI gene expression and hybridization array data repository. Nucleic Acids Res. 2002;30(1):207–10. 10.1093/nar/30.1.207 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 21. Irizarry RA, Bolstad BM, Collin F, et al. : Summaries of Affymetrix GeneChip probe level data. Nucleic Acids Res. 2003;31(4):e15. 10.1093/nar/gng015 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 22. GEO accession GSE65194, Dubois T: Expression profiling of breast cancer samples from Institut Curie (Maire cohort) --Affy CDF.2015. Reference Source [Google Scholar]