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Identification of prognostic genes signature and construction of ceRNA network in pirarubicin treatment of triple-negative breast cancer

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Abstract

Background

The altered long non-coding RNA (lncRNA), circular RNA (circRNA) and mRNA expression in triple-negative breast cancer (TNBC) after pirarubicin (THP) treatment can be a critical factor in the development of tumor. Here, we identify a set of lncRNA, circRNA, and mRNA that can reveal the molecular target and molecular mechanism of THP, and can be used to predict the prognostic characteristics of TNBC.

Methods

Affymetrix GeneChip sequencing was performed to determine whether lncRNA, circRNA, and mRNA were changed in MDA-MB-231 cells after THP treatment, and qRT-PCR was used to verify the accuracy of GeneChip results. Bioinformatics methods were used to analyze the differentially expressed (DE) lncRNA, circRNA and mRNA, and the co-expression network and ceRNA network were constructed. The STRING database, Kaplan–meier Mapper database, GEPIA database, and Tumor Immunity Estimation Resource were used to screen hub genes with clinical value and important significance.

Results

THP 5 μM could significantly inhibit proliferation, migration and invasion of MDA-MB-231 cells for 24 h. 1547 DE lncRNAs, 4992 DE circRNAs, and 5777 DE mRNAs were identified. The reliability of the GeneChip was verified by qRT-PCR. An mRNA-lncRNA/circRNA co-expression network was constructed based on the Pearson correlation coefficient. Finally, we established a new ceRNA network, including three circRNAs, five miRNAs, and three mRNAs. The mRNAs are associated with immune infiltration. The mRNAs and miRNAs are significantly associated with survival outcomes in TNBC.

Conclusion

The results reveal the molecular target and mechanism of THP treatment of TNBC. These ceRNA network can be used as molecular targets for the treatment of TNBC patients and as molecular biomarkers to predict patient prognosis.

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Data availability

Additional data pertaining to this work can be obtained from the corresponding author upon request.

References

  1. Sung H, Ferlay J, Siegel RL, Laversanne M, Soerjomataram I, Jemal A, Bray F. Global Cancer Statistics 2020: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 Countries. CA Cancer J Clin. 2021;71:209–49.

    Article  PubMed  Google Scholar 

  2. Hortobagyi GN, Edge SB, Giuliano A. New and important changes in the TNM staging system for breast cancer. Am Soc Clin Oncol Educat Book. 2018;38:457–67.

    Article  Google Scholar 

  3. Li C-J, Tzeng Y-DT, Chiu Y-H, Lin H-Y, Hou M-F, Chu P-Y. Pathogenesis and potential therapeutic targets for triple-negative breast cancer. Cancers. 2021;13:2978.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  4. Mezi S, Botticelli A, Pomati G, Cerbelli B, Scagnoli S, Amirhassankhani S, D’Amati G, Marchetti P. Standard of care and promising new agents for the treatment of mesenchymal triple-negative breast cancer. Cancers. 2021;13:1080.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  5. Liao M, Zhang J, Wang G, Wang L, Liu J, Ouyang L, Liu B. Small-molecule drug discovery in triple negative breast cancer: current situation and future directions. J Med Chem. 2021;64:2382–418.

    Article  CAS  PubMed  Google Scholar 

  6. Angsutararux P, Luanpitpong S, Issaragrisil S. Chemotherapy-induced cardiotoxicity: overview of the roles of oxidative stress. Oxid Med Cell Longev. 2015;2015: 795602.

    Article  PubMed  PubMed Central  Google Scholar 

  7. Cech TR, Steitz JA. The noncoding RNA revolution-trashing old rules to forge new ones. Cell. 2014;157:77–94.

    Article  CAS  PubMed  Google Scholar 

  8. Venkatesh T, Suresh PS, Tsutsumi R. Non-coding RNAs: functions and applications in endocrine-related cancer. Mol Cell Endocrinol. 2015;416:88–96.

    Article  CAS  PubMed  Google Scholar 

  9. Wang J, Zhang Y, Liu L, Yang T, Song J. Circular RNAs: new biomarkers of chemoresistance in cancer. Cancer Biol Med. 2021;18:421–36.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  10. Han J, Han B, Wu X, Hao J, Dong X, Shen Q, Pang H. Knockdown of lncRNA H19 restores chemo-sensitivity in paclitaxel-resistant triple-negative breast cancer through triggering apoptosis and regulating Akt signaling pathway. Toxicol Appl Pharmacol. 2018;359:55–61.

    Article  CAS  PubMed  Google Scholar 

  11. Kartha RV, Subramanian S. Competing endogenous RNAs (ceRNAs): new entrants to the intricacies of gene regulation. Front Genet. 2014;5:8.

    Article  PubMed  PubMed Central  Google Scholar 

  12. Salmena L, Poliseno L, Tay Y, Kats L, Pandolfi PP. A ceRNA hypothesis: the Rosetta Stone of a hidden RNA language? Cell. 2011;146:353–8.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  13. Zheng SR, Huang QD, Zheng ZH, Zhang ZT, Guo GL. circGFRA1 affects the sensitivity of triple-negative breast cancer cells to paclitaxel via the miR-361-5p/TLR4 pathway. J Biochem. 2021;169:601–11.

    Article  CAS  PubMed  Google Scholar 

  14. The Gene Ontology resource: enriching a GOld mine. Nucleic Acids Res. 2021;49:D325-d334.

  15. Kanehisa M, Sato Y, Kawashima M, Furumichi M, Tanabe M. KEGG as a reference resource for gene and protein annotation. Nucleic Acids Res. 2016;44:D457-462.

    Article  CAS  PubMed  Google Scholar 

  16. Györffy B, Lanczky A, Eklund AC, Denkert C, Budczies J, Li Q, Szallasi Z. An online survival analysis tool to rapidly assess the effect of 22,277 genes on breast cancer prognosis using microarray data of 1809 patients. Breast Cancer Res Treat. 2010;123:725–31.

    Article  PubMed  Google Scholar 

  17. Lánczky A, Nagy Á, Bottai G, Munkácsy G, Szabó A, Santarpia L, Győrffy B. miRpower: a web-tool to validate survival-associated miRNAs utilizing expression data from 2178 breast cancer patients. Breast Cancer Res Treat. 2016;160:439–46.

    Article  PubMed  Google Scholar 

  18. 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:W98–102.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  19. Li T, Fan J, Wang B, Traugh N, Chen Q, Liu JS, Li B, Liu XS. TIMER: a web server for comprehensive analysis of tumor-infiltrating immune cells. Cancer Res. 2017;77:e108–10.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  20. Li B, Severson E, Pignon JC, Zhao H, Li T, Novak J, Jiang P, Shen H, Aster JC, Rodig S, et al. Comprehensive analyses of tumor immunity: implications for cancer immunotherapy. Genome Biol. 2016;17:174.

    Article  PubMed  PubMed Central  Google Scholar 

  21. Dudekula DB, Panda AC, Grammatikakis I, De S, Abdelmohsen K, Gorospe M. CircInteractome: a web tool for exploring circular RNAs and their interacting proteins and microRNAs. RNA Biol. 2016;13:34–42.

    Article  PubMed  Google Scholar 

  22. Li JH, Liu S, Zhou H, Qu LH, Yang JH. starBase v2.0: decoding miRNA-ceRNA, miRNA-ncRNA and protein-RNA interaction networks from large-scale CLIP-Seq data. Nucleic Acids Res. 2014;42:D92-97.

    Article  CAS  PubMed  Google Scholar 

  23. Shannon P, Markiel A, Ozier O, Baliga NS, Wang JT, Ramage D, Amin N, Schwikowski B, Ideker T. Cytoscape: a software environment for integrated models of biomolecular interaction networks. Genome Res. 2003;13:2498–504.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  24. Cao X, Luo J, Gong T, Zhang ZR, Sun X, Fu Y. Coencapsulated doxorubicin and bromotetrandrine lipid nanoemulsions in reversing multidrug resistance in breast cancer in vitro and in vivo. Mol Pharm. 2015;12:274–86.

    Article  CAS  PubMed  Google Scholar 

  25. Schlessinger J. Receptor tyrosine kinases: legacy of the first two decades. Cold Spring Harb Perspect Biol. 2014;6:a008912.

    Article  PubMed  PubMed Central  Google Scholar 

  26. Oshi M, Gandhi S, Tokumaru Y, Yan L, Yamada A, Matsuyama R, Ishikawa T, Endo I, Takabe K. Conflicting roles of EGFR expression by subtypes in breast cancer. Am J Cancer Res. 2021;11:5094–110.

    CAS  PubMed  PubMed Central  Google Scholar 

  27. Kyriakopoulou K, Kefali E, Piperigkou Z, Riethmüller C, Greve B, Franchi M, Götte M, Karamanos NK. EGFR is a pivotal player of the E2/ERβ - mediated functional properties, aggressiveness, and stemness in triple-negative breast cancer cells. Febs j. 2022;289:1552–74.

    Article  CAS  PubMed  Google Scholar 

  28. Liu X, Adorno-Cruz V, Chang YF, Jia Y, Kawaguchi M, Dashzeveg NK, Taftaf R, Ramos EK, Schuster EJ, El-Shennawy L, et al. EGFR inhibition blocks cancer stem cell clustering and lung metastasis of triple negative breast cancer. Theranostics. 2021;11:6632–43.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  29. Gu Y, Liu Y, Fu L, Zhai L, Zhu J, Han Y, Jiang Y, Zhang Y, Zhang P, Jiang Z, et al. Tumor-educated B cells selectively promote breast cancer lymph node metastasis by HSPA4-targeting IgG. Nat Med. 2019;25:312–22.

    Article  CAS  PubMed  Google Scholar 

  30. Guestini F, Ono K, Miyashita M, Ishida T, Ohuchi N, Nakagawa S, Hirakawa H, Tamaki K, Ohi Y, Rai Y, et al. Impact of topoisomerase IIα, PTEN, ABCC1/MRP1, and KI67 on triple-negative breast cancer patients treated with neoadjuvant chemotherapy. Breast Cancer Res Treat. 2019;173:275–88.

    Article  CAS  PubMed  Google Scholar 

  31. Bao C, Liu T, Qian L, Xiao C, Zhou X, Ai H, Wang J, Fan W, Pan J. Shikonin inhibits migration and invasion of triple-negative breast cancer cells by suppressing epithelial-mesenchymal transition via miR-17-5p/PTEN/Akt pathway. J Cancer. 2021;12:76–88.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  32. Uzelac B, Krivokuca A, Brankovic-Magic M, Magic Z, Susnjar S, Milovanovic Z, Supic G. Expression of SIRT1, SIRT3 and SIRT6 genes for predicting survival in triple-negative and hormone receptor-positive subtypes of breast cancer. Pathol Oncol Res. 2020;26:2723–31.

    Article  CAS  PubMed  Google Scholar 

  33. Podralska M, Ziółkowska-Suchanek I, Żurawek M, Dzikiewicz-Krawczyk A, Słomski R, Nowak J, Stembalska A, Pesz K, Mosor M. Genetic variants in ATM, H2AFX and MRE11 genes and susceptibility to breast cancer in the polish population. BMC Cancer. 2018;18:452.

    Article  PubMed  PubMed Central  Google Scholar 

  34. Lu J, Wei Q, Bondy ML, Brewster AM, Bevers TB, Yu TK, Buchholz TA, Meric-Bernstam F, Hunt KK, Singletary SE, Wang LE. Genetic variants in the H2AFX promoter region are associated with risk of sporadic breast cancer in non-Hispanic white women aged <or=55 years. Breast Cancer Res Treat. 2008;110:357–66.

    Article  CAS  PubMed  Google Scholar 

  35. Du W, Hu J, Hu R, Yang M, Peng Y, Zhang Z, Li Y, He X. circ0101675 promotes malignant process via sponging miR-1278 and upregulating WNT3A/5A in non-small cell lung cancer. J Cancer. 2021;12:4209–17.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  36. Rong Z, Shi S, Tan Z, Xu J, Meng Q, Hua J, Liu J, Zhang B, Wang W, Yu X, Liang C. Circular RNA CircEYA3 induces energy production to promote pancreatic ductal adenocarcinoma progression through the miR-1294/c-Myc axis. Mol Cancer. 2021;20:106.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  37. Li H, Li HH, Chen Q, Wang YY, Fan CC, Duan YY, Huang Y, Zhang HM, Li JP, Zhang XY, et al. miR-142-5p inhibits cell invasion and migration by targeting DNMT1 in breast cancer. Oncol Res. 2022;28:885–97.

    Article  PubMed  PubMed Central  Google Scholar 

  38. Hua B, Li Y, Yang X, Niu X, Zhao Y, Zhu X. MicroRNA-361-3p promotes human breast cancer cell viability by inhibiting the E2F1/P73 signalling pathway. Biomed Pharmacother. 2020;125: 109994.

    Article  CAS  PubMed  Google Scholar 

  39. Hu S, Song Y, Zhou Y, Jiao Y, Wang S. MiR-1270 suppresses the malignant progression of breast cancer via targeting MMD2. J Healthc Eng. 2022;2022:3677720.

    Article  PubMed  PubMed Central  Google Scholar 

  40. Hao J, Du X, Lv F, Shi Q. Knockdown of circ_0006528 suppresses cell proliferation, migration, invasion, and adriamycin chemoresistance via regulating the miR-1236-3p/CHD4 axis in breast cancer. J Surg Res. 2021;260:104–15.

    Article  CAS  PubMed  Google Scholar 

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Authors and Affiliations

  1. Department of Experimental Pharmacology and Toxicology, School of Pharmaceutical Sciences, Jilin University, Changchun, China

    Jiulong Ma, Chen Chen, Jiahua Ji, Peng Huang, Dexian Wei & Liqun Ren

  2. Department of Hepatobiliary Surgery, Songyuan Central Hospital, Songyuan, China

    Fengjun Wang

  3. Department of Vascular Surgery, The First Hospital of Jilin University, Changchun, China

    Yang Zhang

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  1. Jiulong Ma
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Contributions

JM, YZ, LR conceived and designed experiments. JM performed experiments. CC and FW carried out data analysis. JJ, PH, and DW participated in the preparation of reagents/materials/analysis tools. JM wrote the manuscript. YZ, LR supervised the manuscript. All data were generated in-house, and no paper mill was used. All authors agree to be accountable for all aspects of this work including the integrity and accuracy of the data presented.

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Correspondence to Yang Zhang or Liqun Ren.

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Ma, J., Wang, F., Chen, C. et al. Identification of prognostic genes signature and construction of ceRNA network in pirarubicin treatment of triple-negative breast cancer. Breast Cancer 30, 379–392 (2023). https://doi.org/10.1007/s12282-023-01433-w

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  • DOI: https://doi.org/10.1007/s12282-023-01433-w

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