The effect of BRCA1/2 mutation on breast cancer and its impact on PARP inhibitor treatments: Differential expression genes approach

Rafika Indah Paramita Sonar Soni Panigoro Septelia Inawati Wanandi Fadilah Fadilah   

Open Access   

Published:  Jun 08, 2024

DOI: 10.7324/JAPS.2024.173495
Abstract

The occurrence of germline mutations within the BRCA1/2 genes has been linked to an elevated vulnerability toward the onset of breast cancer (BC). At present, ongoing clinical trials are being undertaken to evaluate the efficacy of poly(ADP-ribose) polymerase (PARP) inhibitors as a therapeutic intervention for BC, with particular emphasis on their application in the management of BC patients harboring BRCA1/2 gene mutations. The objective of this research was to investigate the presence of different expression genes in BC with BRCA1/2 mutations compared to the wild type and to evaluate the impact of PARP inhibitor therapy on the DEGs. This study utilized two distinct datasets sourced from the Gene Expression Omnibus (GEO) database. The initial datasets utilized in this study were GSE25835 and GSE40115. These datasets were employed to conduct a comparative analysis of differentially expressed genes (DEGs) in BC cases with BRCA1/2 mutations and those with wild-type status. Whereas in the GSE55399 dataset, the DEGs were compared between PARP inhibitor treatment and no PARP inhibitor treatment. The interactions among DEGs were assessed utilizing the search tool for the retrieval of interacting genes/proteins tool and subsequently displayed through the use of Cytoscape software. The molecular complex detection technique was employed for the identification of gene clusters within the interaction network. The DEGs that were discovered were further analyzed for gene ontology (GO) enrichment using Enrichr and CLueGO. Furthermore, the biological pathways linked to these DEGs were examined using REACTOME. We got significant DEGs by using parameter p-value of 0.05; log2FC > 1 and log2FC < −1. The GO analysis conducted on the DEGs revealed their significant involvement in crucial biological processes and molecular pathways. For datasets GSE25835 and GSE40115, it showed the effect on BRCA1/2 mutations was upregulating cell cycle response and downregulating mRNA splicing. For dataset GSE55399, the impact of PARP inhibitor treatments was upregulating the interferon signaling and downregulating the cytokine signaling. Our study identified hub genes of cell cycle response (CDK1 and BIRC5) that are strongly linked to BRCA1/2 mutation and hub genes of interferon signaling interferon-induced transmembrane 1 (IFITM1) and cytokine signaling (IL11) that are strongly linked to PARP inhibitor treatments in BRCA1/2 mutant carriers. We identified hub genes of cell cycle response (CDK1 and BIRC5) that are strongly linked to BRCA1/2 mutation. PARP inhibitor treatments in BRCA1/2 mutant carriers are strongly related to the upregulation of IFITM1 (interferon signaling) and the downregulation of IL11 (cytokine signaling). Therefore, PARP inhibitors may improve the treatment by activation/modulation the immune system and attenuating the inflammatory response. However, the dataset used to analyze the DEGs of PARP inhibitor treatments in BRCA1/2 mutant carriers still used BC cell lines, forthcoming research may be able to use clinical patients as the subjects. Moreover, functional studies are further needed to validate this finding.


Keyword:     Bioinformatics BRCA1/2 mutations breast cancer differentially expressed genes (DEGs) PARP inhibitor


Citation:

Paramita RI, Panigoro SS, Wanandi SI, Fadilah F. The effect of BRCA1/2 mutation on breast cancer and its impact on PARP inhibitor treatments: Differential expression genes approach. J Appl Pharm Sci. 2024. Online First. http://doi.org/10.7324/JAPS.2024.173495

Copyright: © The Author(s). This is an open-access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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Reference

1. Park S, Lee E, Park S, Lee S, Nam SJ, Kim SW, et al. Clinical characteristics and exploratory genomic analyses of germline BRCA1 or BRCA2 mutations in breast cancer. Mol Cancer Res. 2020;18(9):1315-25. https://doi.org/10.1158/1541-7786.MCR-19-1108

2. Couch FJ, Johnson MR, Rabe KG, Brune K, De Andrade M, Goggins M, et al. The prevalence of BRCA2 mutations in familial pancreatic cancer. Cancer Epidemiol Biomarkers Prev. 2007;16(2):342-6. https://doi.org/10.1158/1055-9965.EPI-06-0783

3. Pritchard CC, Mateo J, Walsh MF, De Sarkar N, Abida W, Beltran H, et al. Inherited DNA-repair gene mutations in men with metastatic prostate cancer. N Engl J Med. 2016;375(5):443-53. https://doi.org/10.1056/NEJMoa1603144

4. Rebbeck TR, Mitra N, Wan F, Sinilnikova OM, Healey S, McGuffog L, et al. Association of type and location of BRCA1 and BRCA2 mutations with risk of breast and ovarian cancer. J Am Med Assoc. 2015;313(13):1347-61. https://doi.org/10.1001/jama.2014.5985

5. 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. J Am Med Assoc. 2017;317(23):2402-16. https://doi.org/10.1001/jama.2017.7112

6. Dziadkowiec KN, Gasiorowska E, Nowak-Markwitz E, Jankowska A. PARP inhibitors: review of mechanisms of action and BRCA1/2 mutation targeting. Prz Menopauzalny. 2016;15(4):215-9. https://doi.org/10.5114/pm.2016.65667

7. Wang YA, Jian J-W, Hung C-F, Peng H-P, Yang C-F, Cheng H-CS, et al. Germline breast cancer susceptibility gene mutations and breast cancer outcomes. BMC Cancer. 2018;18(1):315. https://doi.org/10.1186/s12885-018-4229-5

8. Udhaya Kumar S, Thirumal Kumar D, Bithia R, Sankar S, Magesh R, Sidenna M, et al. Analysis of differentially expressed genes and molecular pathways in familial hypercholesterolemia involved in atherosclerosis: a systematic and bioinformatics approach. Front Genet. 2020;11(July):1-16. https://doi.org/10.3389/fgene.2020.00734

9. Zhu C, Hu H, Li J, Wang J, Wang K, Sun J. Identification of key differentially expressed genes and gene mutations in breast ductal carcinoma in situ using RNA-seq analysis. World J Surg Oncol. 2020;18(1):52. https://doi.org/10.1186/s12957-020-01820-z

10. Zhang S, Jiang H, Gao B, Yang W, Wang G. Identification of diagnostic markers for breast cancer based on differential gene expression and pathway network. Front Cell Dev Biol. 2022;9(January):811585. https://doi.org/10.3389/fcell.2021.811585

11. Li J, Huang G, Ren C, Wang N, Sui S, Zhao Z, et al. Identification of differentially expressed genes-related prognostic risk model for survival prediction in breast carcinoma patients. Aging (Albany NY). 2021;13(12):16577-99. https://doi.org/10.18632/aging.203178

12. Proia TA, Keller PJ, Gupta PB, Klebba I, Jones AD, Sedic M, et al. Genetic predisposition directs breast cancer phenotype by dictating progenitor cell fate. Cell Stem Cell [Internet]. 2011 Feb;8(2):149- 63. https://doi.org/10.1016/j.stem.2010.12.007

13. Larsen MJ, Kruse TA, Tan Q, Lænkholm AV, Bak M, Lykkesfeldt AE, et al. Classifications within molecular subtypes enables identification of BRCA1/BRCA2 mutation carriers by RNA tumor profiling. PLoS One. 2013;8(5):e64268. https://doi.org/10.1371/journal.pone.0064268

14. Karginova O, Siegel MB, Van Swearingen AED, Deal AM, Adamo B, Sambade MJ, et al. Efficacy of carboplatin alone and in combination with ABT888 in intracranial murine models of BRCA-mutated and BRCA-wild-type triple-negative breast cancer. Mol Cancer Ther. 2015;14(4):920-30. https://doi.org/10.1158/1535-7163.MCT-14-0474

15. Sean D, Meltzer PS. GEOquery: a bridge between the Gene Expression Omnibus (GEO) and BioConductor. Bioinformatics. 2007;23(14):1846-7. https://doi.org/10.1093/bioinformatics/btm254

16. Szklarczyk D, Morris JH, Cook H, Kuhn M, Wyder S, Simonovic M, et al. The STRING database in 2017: quality-controlled protein-protein association networks, made broadly accessible. Nucleic Acids Res. 2017;45(D1):D362-8. https://doi.org/10.1093/nar/gkw937

17. Shannon P, Markiel A, Ozier O, Baliga NS, Wang JT, Ramage D, et al. Cytoscape: a software environment for integrated models of biomolecular interaction networks. Genome Res [Internet]. 2003 Nov;13(11):2498-504. https://doi.org/10.1101/gr.1239303

18. Li Q, Aishwarya S, Li JP, Pan DX, Shi JP. Gene expression profiling of glioblastoma to recognize potential biomarker candidates. Front Genet. 2022;13:832742. https://doi.org/10.3389/fgene.2022.832742

19. Bindea G, Mlecnik B, Hackl H, Charoentong P, Tosolini M, Kirilovsky A, et al. ClueGO: a cytoscape plug-in to decipher functionally grouped gene ontology and pathway annotation networks. Bioinformatics. 2009;25(8):1091-3. https://doi.org/10.1093/bioinformatics/btp101

20. Gillespie M, Jassal B, Stephan R, Milacic M, Rothfels K, Senff- Ribeiro A, et al. The reactome pathway knowledgebase 2022. Nucleic Acids Res. 2022;50(D1):D687-92. https://doi.org/10.1093/nar/gkab1028

21. Tang Z, Li C, Kang B, Gao G, Li C, Zhang Z. GEPIA: a web server for cancer and normal gene expression profiling and interactive analyses. Nucleic Acids Res. 2017;45(W1):W98-102. https://doi.org/10.1093/nar/gkx247

22. Albogami S. Comprehensive analysis of gene expression profiles to identify differential prognostic factors of primary and metastatic breast cancer. Saudi J Biol Sci [Internet]. 2022;29(7):103318. https://doi.org/10.1016/j.sjbs.2022.103318

23. Bryant HE, Schultz N, Thomas HD, Parker KM, Flower D, Lopez E, et al. Specific killing of BRCA2-deficient tumours with inhibitors of poly(ADP-ribose) polymerase. Nature. 2005;434(7035):913-7. https://doi.org/10.1038/nature03443

24. McCarthy N. A positive defect. Nat Rev Cancer [Internet]. 2005 May 20;5(5):333-333. https://doi.org/10.1038/nrc1618

25. Dhillon KK, Swisher EM, Taniguchi T. Secondary mutations of BRCA1/2 and drug resistance. Cancer Sci. 2011;102(4):663-9. https://doi.org/10.1111/j.1349-7006.2010.01840.x

26. Kaur G, Gupta S, Kaur G, Verma M, Kaur P. Bioinformatics: an important tool in oncology. In: biomedical data mining for information retrieval [Internet]. Hoboken, NJ: Wiley; 2021. p. 163-95. https://doi.org/10.1002/9781119711278.ch6

27. Deng JL, Xu YH, Wang G. Identification of potential crucial genes and key pathways in breast cancer using bioinformatic analysis. Front Genet. 2019;10(JUL):695. https://doi.org/10.3389/fgene.2019.00695

28. Fei H, Chen S, Xu C. RNA-sequencing and microarray data mining revealing: the aberrantly expressed mRNAs were related with a poor outcome in the triple negative breast cancer patients. Ann Transl Med. 2020;8(6):363. https://doi.org/10.21037/atm.2020.02.51

29. Zhou Q, Liu X, Lv M, Sun E, Lu X, Lu C. Genes that predict poor prognosis in breast cancer via bioinformatical analysis. Biomed Res Int. 2021;2021:6649660. https://doi.org/10.1155/2021/6649660

30. Oparina N, Erlandsson MC, Beding AF, Parris T, Helou K, Karlsson P, et al. Prognostic significance of birc5/survivin in breast cancer: results from three independent cohorts. Cancers (Basel). 2021;13(9):1-16. https://doi.org/10.3390/cancers13092209

31. Dai JB, Zhu B, Lin WJ, Gao HY, Dai H, Zheng L, et al. Identification of prognostic significance of BIRC5 in breast cancer using integrative bioinformatics analysis. Biosci Rep. 2020;40(2):1-12. https://doi.org/10.1042/BSR20193678

32. Mehraj U, Aisha S, Sofi S, Mir MA. Expression pattern and prognostic significance of baculoviral inhibitor of apoptosis repeat-containing 5 (BIRC5) in breast cancer: a comprehensive analysis. Adv Cancer Biol - Metastasis. 2022;4(March):100037. https://doi.org/10.1016/j.adcanc.2022.100037

33. Promkan M, Liu G, Patmasiriwat P, Chakrabarty S. BRCA1 modulates malignant cell behavior, the expression of survivin and chemosensitivity in human breast cancer cells. Int J Cancer. 2009;125(12):2820-8. https://doi.org/10.1002/ijc.24684

34. Wang RH, Zheng Y, Kim HS, Xu X, Cao L, Luhasen T, et al. Interplay among BRCA1, SIRT1, and survivin during BRCA1-Associated Tumorigenesis. Mol Cell [Internet]. 2008;32(1):11-20. https://doi.org/10.1016/j.molcel.2008.09.011

35. Izadi S, Nikkhoo A, Hojjat-Farsangi M, Namdar A, Azizi G, Mohammadi H, et al. CDK1 in breast cancer: implications for theranostic potential. Anticancer Agents Med Chem [Internet]. 2020 Jul 3;20(7):758-67. https://doi.org/10.2174/1871520620666200203125712

36. Xing Z, Wang X, Liu J, Zhang M, Feng K, Wang X. Expression and prognostic value of CDK1, CCNA2, and CCNB1 gene clusters in human breast cancer. J Int Med Res. 2021;49(4):300060520 980647.

37. Gómez-Herranz M, Faktor J, Yébenes Mayordomo M, Pilch M, Nekulova M, Hernychova L, et al. Emergent Role of IFITM1/3 towards splicing factor (SRSF1) and antigen-presenting molecule (HLA-B) in Cervical Cancer. Biomolecules. 2022;12(8):1-21. https://doi.org/10.3390/biom12081090

38. Reisländer T, Lombardi EP, Groelly FJ, Miar A, Porru M, Di Vito S, et al. BRCA2 abrogation triggers innate immune responses potentiated by treatment with PARP inhibitors. Nat Commun [Internet]. 2019 Jul 17;10(1):3143. https://doi.org/10.1038/s41467-019-11048-5

39. Ernst M, Putoczki TL. Molecular pathways: IL11 as a tumor-promoting cytokine-translational implications for cancers. Clin Cancer Res. 2014;20(22):5579-88. https://doi.org/10.1158/1078-0432.CCR-13-2492

40. Johnstone CN, Chand A, Putoczki TL, Ernst M. Emerging roles for IL-11 signaling in cancer development and progression: focus on breast cancer. Cytokine Growth Factor Rev. 2015;26(5): 489-98. https://doi.org/10.1016/j.cytogfr.2015.07.015

41. Rom S, Zuluaga-Ramirez V, Reichenbach NL, Dykstra H, Gajghate S, Pacher P, et al. PARP inhibition in leukocytes diminishes inflammation via effects on integrins/cytoskeleton and protects the blood-brain barrier. J Neuroinflammation [Internet]. 2016;13(1):1- 16. https://doi.org/10.1186/s12974-016-0729-x

42. Liu Z, Wang H, Wang S, Gao J, Niu L. PARP-1 inhibition attenuates the inflammatory response in the cartilage of a rat model of osteoarthritis. Bone Joint Res. 2021;10(7):401-10. https://doi.org/10.1302/2046-3758.107.BJR-2020-0200.R2

43. Lee EK, Konstantinopoulos PA. PARP inhibition and immune modulation: scientific rationale and perspectives for the treatment of gynecologic cancers. Ther Adv Med Oncol [Internet]. 2020 Jan 24;12(6):1758835920944116. https://doi.org/10.1177/1758835920944116

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