Open Access

LSM3, NDUFB3, and PTGS2 may be potential biomarkers for BRCA1-mutation positive breast cancer


Cite

1. Güzey S, Aykan A, Avşar S, Yavan İ, Öztürk S. Recurrent Breast Cancer with Cutaneous Metastasis in the Late Term. Turkish Journal of Plastic Surgery. 2017;25(1):34+. DOI: 10.5152/TurkJPlast-Surg.2016.1980Search in Google Scholar

2. Siegel RL, Miller KD, Jemal A. Cancer Statistics, 2017. Ca Cancer J Clin. 2017;67(1):7-30. DOI: 10.3322/caac.2138710.3322/caac.21387Search in Google Scholar

3. Cancer UK. Breast cancer symptoms. 2010.Search in Google Scholar

4. McGuire, S. World Cancer Report 2014. Geneva, Switzerland: World Health Organization, International Agency for Research on Cancer, WHO Press, 2015. Advances in Nutrition: An International Review Journal. 2016;7(2):418-9. DOI: 10.3945/an.116.01221110.3945/an.116.012211Search in Google Scholar

5. Chen W, Zheng R, Baade PD, Zhang S, Zeng H, Bray F, et al. Cancer statistics in China, 2015. Ca Cancer J Clin. 2016;66(2):115-32. DOI: 10.3322/caac.2133810.3322/caac.21338Search in Google Scholar

6. Zhao X, Qu J, Sun Y, Wang J, Liu X, Wang F, et al. Prognostic significance of tumor-associated macrophages in breast cancer: a meta-analysis of the literature. Onco-target. 2017;8(18):30576-86. DOI: 10.18632/oncotarget.1573610.18632/oncotarget.15736Search in Google Scholar

7. Robson ME, Chappuis PO, Jaya S, Nora W, Jeff B, Goffin JR, et al. A combined analysis of outcome following breast cancer: differences in survival based on BRCA1/BRCA2 mutation status and administration of adjuvant treatment. Breast Cancer Res. 2003;6(1):R8. DOI: 10.1186/bcr65810.1186/bcr658Search in Google Scholar

8. Kuchenbaecker KB, Hopper JL, Barnes DR, Phillips KA, Mooij TM, Roos-Blom MJ, et al. Risks of Breast, Ovarian, and Contralateral Breast Cancer for BRCA1 and BRCA2 Mutation Carriers. Jama. 2017 Jun 20;317(23):2402-16.Search in Google Scholar

9. Anton-Culver H, Cohen PF, Gildea ME, Ziogas A. Characteristics of BRCA1 mutations in a population-based case series of breast and ovarian cancer. Eur J Cancer. 2000;36(10):1200-8. DOI: 10.1016/S0959-8049(00)00110-610.1016/S0959-8049(00)00110-6Search in Google Scholar

10. Liu X, Ma Y, Yang W, Wu X, Jiang L, Chen X. Identification of therapeutic targets for breast cancer using biological informatics methods. Mol Med Rep. 2015;12(2):1789. DOI: 10.3892/mmr.2015.356510.3892/mmr.2015.3565446409025824986Search in Google Scholar

11. Zhao Y, Bing F. Screening of biomarkers for prediction of response to and prognosis after chemotherapy for breast cancers. Onco Targets Ther. 2016;9(Issue 1):2593-600. DOI: 10.2147/OTT.S9235010.2147/OTT.S92350486100127217777Search in Google Scholar

12. Wu D, Han B, Guo L, Fan Z. Molecular mechanisms associated with breast cancer based on integrated gene expression profiling by bioinformatics analysis. J Obstetrics & Gynaecology. 2016;36(5):615-21. DOI: 10.3109/01443615.2015.112790210.3109/01443615.2015.112790226804550Search in Google Scholar

13. Athar A, Fullgrabe A, George N, Iqbal H, Huerta L, Ali A, et al. ArrayExpress update - from bulk to single-cell expression data. Nucleic acids res. 2019 Jan 8;47(D1):D711-d5. DOI: 10.1093/nar/gky96410.1093/nar/gky964632392930357387Search in Google Scholar

14. Carvalho BS, Irizarry RA. A framework for oligonucleotide microarray preprocessing. Bioinformatics. 2010;26(19):2363-7. DOI: 10.1093/bioinformatics/btq43110.1093/bioinformatics/btq431294419620688976Search in Google Scholar

15. Smyth GK. limma: Linear Models for Microarray Data. Bioinformatics & Computational Biology Solutions Using R & Bioconductor. 2011:397-420. DOI: 10.1007/0-387-29362-0_2310.1007/0-387-29362-0_23Search in Google Scholar

16. Subramanian A, Tamayo P, Mootha VK, Mukherjee S, Ebert BL, Gillette MA, et al. Gene set enrichment analysis: a knowledge-based approach for interpreting genome-wide expression profiles. Proc Natl Acad Sci U S A. 2005;102(43):15545-50. DOI: 10.1073/pnas.050658010210.1073/pnas.0506580102123989616199517Search in Google Scholar

17. Kanehisa M, Goto S. KEGG: Kyoto Encyclopedia of Genes and Genomes. Nucleic Acids Res. 2000 Jan 1;28(1):27-30. DOI: 10.1093/nar/28.1.2710.1093/nar/28.1.2710240910592173Search in Google Scholar

18. Shannon, P. Cytoscape: A Software Environment for Integrated Models of Biomolecular Interaction Networks. Genome Res. 2003;13(11):2498. DOI: 10.1101/gr.123930310.1101/gr.123930340376914597658Search in Google Scholar

19. Therneau TM, Grambsch PM, Modeling Survival Data: Extending The Cox Model. 2000. DOI: 10.1007/978-1-4757-3294-810.1007/978-1-4757-3294-8Search in Google Scholar

20. Fromont-Racine M, Rain JC, Legrain P. Toward a functional analysis of the yeast genome through exhaustive two-hybrid screens. Nat Genet. 1997 Jul;16(3):277-82. DOI: 10.1038/ng0797-27710.1038/ng0797-2779207794Search in Google Scholar

21. Fici P, Gallerani G, Morel AP, Mercatali L, Ibrahim T, Scarpi E, et al. Splicing factor ratio as an index of epithelial-mesenchymal transition and tumor aggressiveness in breast cancer. Oncotarget. 2017;8(2):2423-36. DOI: 10.18632/oncotarget.1368210.18632/oncotarget.13682535681227911856Search in Google Scholar

22. Xie N, Yao Y, Wan L, Zhu T, Liu L, Yuan J. Next-generation sequencing reveals lymph node metastasis associated genetic markers in colorectal cancer. Exp Ther Med. 2017;14(1):338-43. DOI: 10.3892/etm.2017.446410.3892/etm.2017.4464548863128672935Search in Google Scholar

23. Ashton TM, McKenna WG, Kunz-Schughart LA, Higgins GS. Oxidative phosphorylation as an emerging target in cancer therapy. Clin Cancer Res. 2018;24(11):2482-90. DOI: 10.1158/1078-0432.CCR-17-307010.1158/1078-0432.CCR-17-307029420223Search in Google Scholar

24. Sotgia F, Lisanti MP. Mitochondrial markers predict survival and progression in non-small cell lung cancer (NSCLC) patients: Use as companion diagnostics. Oncotarget. 2017;8(40):68095-107. DOI: 10.18632/onco-target.19677Search in Google Scholar

25. Liu X-H, Kirschenbaum A, Yao S, Stearns ME, Holland JF, Claffey K, et al. Upregulation of vascular endothelial growth factor by cobalt chloride-simulated hypoxia is mediated by persistent induction of cyclooxygenase-2 in a metastatic human prostate cancer cell line. Clin exp metastasis. 1999;17(8):687-94. DOI: 10.1023/A:100672811954910.1023/A:1006728119549Search in Google Scholar

26. Dossus L, Kaaks R, Canzian F, Albanes D, Berndt SI, Boeing H, et al. PTGS2 and IL6 genetic variation and risk of breast and prostate cancer: results from the Breast and Prostate Cancer Cohort Consortium (BPC3). Carcinogenesis. 2010;31(3):455-61. DOI: 10.1093/carcin/bgp30710.1093/carcin/bgp307Search in Google Scholar

27. Festa-Vasconcellos JS, Piranda DN, Amaral LM, Indio-do-Brasil V, Koifman S, Vianna-Jorge R. Polymorphisms in cycloxygenase-2 gene and breast cancer prognosis: association between PTGS2 haplotypes and histopathological features. Breast cancer res treat. 2012;132(1):251-8. DOI: 10.1007/s10549-011-1828-010.1007/s10549-011-1828-0Search in Google Scholar

28. De CP, Hamy AS, Lehmann-Che J, Scott V, Sigal B, Mathieu MC, et al. COX2/PTGS2 Expression Is Predictive of Response to Neoadjuvant Celecoxib in HER2-negative Breast Cancer Patients. Anticancer Res. 2018;38(3):1485. DOI: 10.21873/anticanres.1237510.21873/anticanres.12375Search in Google Scholar

29. Goswami BB, Michael K, Diana N, Cebula TA. Apoptosis induced by a cytopathic hepatitis A virus is dependent on caspase activation following ribosomal RNA degradation but occurs in the absence of 2’-5’ oligoadenylate synthetase. Antiviral Res. 2004;63(3):153-66. DOI: 10.1016/j.antiviral.2004.02.00410.1016/j.antiviral.2004.02.004Search in Google Scholar

30. Kocic G, Jevtovic T, Pavlovic D, Bjelakovic G, Kocic R. 290 A role of IFN-α in the double-stranded RNA degradation during Fas-ligand induced liver apoptosis and balance between proliferation and death. J Hepatol. 2006;44(06):S113-S. DOI: 10.1016/S0168-8278(06)80291-610.1016/S0168-8278(06)80291-6Search in Google Scholar

31. Koedoot E, Dévédec SL, Water BVD. Abstract 893: Systematic assessment of spliceosome components as drivers of breast cancer progression. Cancer Res. 2017;77(13 Supplement):893. DOI: 10.1158/1538-7445.AM2017-89310.1158/1538-7445.AM2017-893Search in Google Scholar

32. Quidville V, Alsafadi S, Goubar A, Commo F, Scott V, Pioche-Durieu C, et al. Targeting the deregulated spliceosome core machinery in cancer cells triggers mTOR blockade and autophagy. Cancer Res. 2013;73(7):2247-58. DOI: 10.1158/0008-5472.CAN-12-250110.1158/0008-5472.CAN-12-250123358685Search in Google Scholar

33. Soto-Guzman A, Villegas-Comonfort S, Cortes-Reynosa P, Salazar EP. Role of arachidonic acid metabolism in Stat5 activation induced by oleic acid in MDA-MB-231 breast cancer cells. Prostaglandins Leukotrienes & Essential Fatty Acids. 2013;88(3):243-9. DOI: 10.1016/j. plefa.2012.12.003Search in Google Scholar

34. Wang Z, Wang N, Han S, Wang D, Mo S, Yu L, et al. Dietary compound isoliquiritigenin inhibits breast cancer neoangiogenesis via VEGF/VEGFR-2 signaling pathway. Plos One. 2013;8(7):e68566. DOI: 10.1371/journal.pone.006856610.1371/journal.pone.0068566370261423861918Search in Google Scholar

35. Chun-Te C, Yi D, Hirohito Y, Jung-Mao H, Hsu-Ping K, Hortobagyi GN, et al. Targeting the IKKβ/mTOR/VEGF signaling pathway as a potential therapeutic strategy for obesity-related breast cancer. Mol Cancer Ther. 2012;11(10):2212-21. DOI: 10.1158/1535-7163. MCT-12-0180Search in Google Scholar

eISSN:
2284-5623
Language:
English
Publication timeframe:
4 times per year
Journal Subjects:
Life Sciences, Molecular Biology, Biochemistry, Human Biology, Microbiology and Virology