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H, CharuMeena, R, Sagaya Jansi, S, Aishwarya, Shanmugaraj, Balamurugan, Panthagani, Praveen Kumar. (1404). Exploring Breast Cancer-Associated Genes: A Comprehensive Analysis and Competitive Endogenous RNA Network Construction. سامانه مدیریت نشریات علمی, 80(2), 447-460. doi: 10.32592/ARI.2025.80.2.447
CharuMeena H; Sagaya Jansi R; Aishwarya S; Balamurugan Shanmugaraj; Praveen Kumar Panthagani. "Exploring Breast Cancer-Associated Genes: A Comprehensive Analysis and Competitive Endogenous RNA Network Construction". سامانه مدیریت نشریات علمی, 80, 2, 1404, 447-460. doi: 10.32592/ARI.2025.80.2.447
H, CharuMeena, R, Sagaya Jansi, S, Aishwarya, Shanmugaraj, Balamurugan, Panthagani, Praveen Kumar. (1404). 'Exploring Breast Cancer-Associated Genes: A Comprehensive Analysis and Competitive Endogenous RNA Network Construction', سامانه مدیریت نشریات علمی, 80(2), pp. 447-460. doi: 10.32592/ARI.2025.80.2.447
H, CharuMeena, R, Sagaya Jansi, S, Aishwarya, Shanmugaraj, Balamurugan, Panthagani, Praveen Kumar. Exploring Breast Cancer-Associated Genes: A Comprehensive Analysis and Competitive Endogenous RNA Network Construction. سامانه مدیریت نشریات علمی, 1404; 80(2): 447-460. doi: 10.32592/ARI.2025.80.2.447

Exploring Breast Cancer-Associated Genes: A Comprehensive Analysis and Competitive Endogenous RNA Network Construction

Archives of Razi Institute
مقاله 10، دوره 80، شماره 2، خرداد و تیر 2025، صفحه 447-460    اصل مقاله (697.07 K)
نوع مقاله: Original Articles
شناسه دیجیتال (DOI): 10.32592/ARI.2025.80.2.447
نویسندگان
CharuMeena H1؛ Sagaya Jansi R* 2؛ Aishwarya S3؛ Balamurugan Shanmugaraj4؛ Praveen Kumar Panthagani5
1Department of Bioinformatics Stella Maris College, Chennai, Tamil Nadu, India
2Department of Bioinformatics, Stella Maris College, Chennai, Tamil Nadu, India
3Department of Bioinformatics, Stella Maris College, Chennai, Tamil Nadu, India
4Department of Biotechnology, Karpagam Academy of Higher Education, Coimbatore, 641021, Tamil Nadu, India
5Molecular Biology Department, Ampath Lab, Hyderabad, Telangana
چکیده
Breast cancer is a cancer affecting women in which cells become abnormal and multiplies in an uncontrollable fashion. These cancers are hereditary and gene mutations with geographic indications stand alone in most invasive breast cancer types, several other factors like age, gender, ethnic background and environment also contribute for the occurrence. Non-coding RNAs are competing endogenous RNAs that participate in the progression of different cancers. The present study intends to uncover the differentially expression genes in breast cancer. In this study, with the Breast cancer RNA-Seq data obtained from TCGA, expression and survival analyses were performed in order to study gene expression of the samples and genes computationally through R programming. The results obtained after each analysis were inferred visually and logically. Total 613 genes were found to be differentially expressed among the samples out of which 254 were up regulated and 359 were down regulated. The differentially expressed genes obtained using the package TCGA bio links was further used in the construction of ceRNA network. From the results of analyses using TCGA bio links, 352 lncRNAs, 183 miRNAs and 254 mRNAs were found to show aberrant expression in the breast cancer samples. Out of the 352 lncRNAs, the 2 most commonly and repeatedly expressed lncRNAs LINC00 461 and MALAT 1 were found to be more potent therapeutic biomarker and found that their regulated miRNA target genes are enriched in the samples. This study constructed the competing endogenous RNA networks and furthermore unravels the underlying biomarkers for breast cancer cohorts.
کلیدواژه‌ها
Breast cancer؛ miRNAs؛ lncRNAs؛ ceRNA network؛ R program
مراجع
  1. Danaei G, Vander Hoorn S, Lopez AD, Murray CJ, Ezzati M. Causes of cancer in the world: comparative risk assessment of nine behavioural and environmental risk factors. The lancet. 2005 Nov 19;366(9499):1784-93.
  2. Levine AJ, Puzio-Kuter AM. The control of the metabolic switch in cancers by oncogenes and tumor suppressor genes. Science. 2010 Dec 3;330(6009):1340-4.
  3. Howlader NN, Noone AM, Krapcho ME, Miller D, Brest A, Yu ME, Ruhl J, Tatalovich Z, Mariotto A, Lewis DR, Chen HS. SEER cancer statistics review, 1975–2016. National Cancer Institute. 2019 Apr 8;1.
  4. DeSantis C, Ma J, Bryan L, Jemal A. Breast cancer statistics, 2013. CA: a cancer journal for clinicians. 2014 Jan;64(1):52-62.
  5. Rouzier R, Perou CM, Symmans WF, Ibrahim N, Cristofanilli M, Anderson K, Hess KR, Stec J, Ayers M, Wagner P, Morandi P. Breast cancer molecular subtypes respond differently to preoperative chemotherapy. Clinical cancer research. 2005 Aug 15;11(16):5678-85.
  6. Wang P, Li J, Zhao W, Shang C, Jiang X, Wang Y, Zhou B, Bao F, Qiao H. A novel LncRNA-miRNA-mRNA triple network identifies LncRNA RP11-363E7. 4 as an important regulator of miRNA and gene expression in gastric Cancer. Cellular Physiology and Biochemistry. 2018 Jul 26;47(3):1025-41.
  7. Kapranov P, Cheng J, Dike S, Nix DA, Duttagupta R, Willingham AT, Stadler PF, Hertel J, Hackermüller J, Hofacker IL, Bell I. RNA maps reveal new RNA classes and a possible function for pervasive transcription. Science. 2007 Jun 8;316(5830):1484-8.
  8. Sana J, Faltejskova P, Svoboda M, Slaby O. Novel classes of non-coding RNAs and cancer. Journal of translational medicine. 2012 Dec;10:1-21.
  9. Ye Y, Li SL, Wang SY. Construction and analysis of mRNA, miRNA, lncRNA, and TF regulatory networks reveal the key genes associated with prostate cancer. PloS one. 2018 Aug 23;13(8):e0198055.
  10. Zhou M, Diao Z, Yue X, Chen Y, Zhao H, Cheng L, Sun J. Construction and analysis of dysregulated lncRNA-associated ceRNA network identified novel lncRNA biomarkers for early diagnosis of human pancreatic cancer. Oncotarget. 2016a Jul 28;7(35):56383.
  11. Zhou M, Wang X, Shi H, Cheng L, Wang Z, Zhao H, Yang L, Sun J. Characterization of long non-coding RNA-associated ceRNA network to reveal potential prognostic lncRNA biomarkers in human ovarian cancer. Oncotarget. 2016b Feb 3;7(11):12598.
  12. Fang XN, Yin M, Li H, Liang C, Xu C, Yang GW, Zhang HX. Comprehensive analysis of competitive endogenous RNAs network associated with head and neck squamous cell carcinoma. Scientific Reports. 2018 Jul 12;8(1):10544.
  13. Yuan W, Li X, Liu L, Wei C, Sun D, Peng S, Jiang L. Comprehensive analysis of lncRNA-associated ceRNA network in colorectal cancer. Biochemical and biophysical research communications. 2019 Jan 8;508(2):374-9.
  14. Tomczak K, Czerwińska P, Wiznerowicz M. Review The Cancer Genome Atlas (TCGA): an immeasurable source of knowledge. Contemporary Oncology/Współczesna Onkologia. 2015 Jan 20;2015(1):68-77.
  15. Lu TP, Lee CY, Tsai MH, Chiu YC, Hsiao CK, Lai LC, Chuang EY. miRSystem: an integrated system for characterizing enriched functions and pathways of microRNA targets. PLoS One. 2012;7(8):e42390. 
  16. Jeggari A, Marks DS, Larsson E. miRcode: a map of putative microRNA target sites in the long non-coding transcriptome. Bioinformatics. 2012 Aug 1;28(15):2062-3.
  17. Otasek D, Morris JH, Bouças J, Pico AR, Demchak B. Cytoscape automation: empowering workflow-based network analysis. Genome biology. 2019 Dec;20:1-5.
  18. Donepudi MS, Kondapalli K, Amos SJ, Venkanteshan P. Breast cancer statistics and markers. Journal of cancer research and therapeutics. 2014 Jul 1;10(3):506-11.
  19. Akram M, Iqbal M, Daniyal M, Khan AU. Awareness and current knowledge of breast cancer. Biological research. 2017 Dec;50:1-23.
  20. Dai X, Xiang L, Li T, Bai Z. Cancer hallmarks, biomarkers and breast cancer molecular subtypes. Journal of cancer. 2016 Jun 23;7(10):1281.
  21. Malta TM, Sokolov A, Gentles AJ, Burzykowski T, Poisson L, Weinstein JN, Kamińska B, Huelsken J, Omberg L, Gevaert O, Colaprico A. Machine learning identifies stemness features associated with oncogenic dedifferentiation. Cell. 2018 Apr 5;173(2):338-54.
  22. Sui J, Li YH, Zhang YQ, Li CY, Shen X, Yao WZ, Peng H, Hong WW, Yin LH, Pu YP, Liang GY. Integrated analysis of long non-coding RNA-associated ceRNA network reveals potential lncRNA biomarkers in human lung adenocarcinoma. International journal of oncology. 2016 Sep 30;49(5):2023-36.
  23. Anders S, Huber W. Differential expression analysis for sequence count data. Genome Biology 2010;11(10):R106.
  24. Colaprico A, Silva TC, Olsen C, Garofano L, Cava C, Garolini D, Sabedot TS, Malta TM, Pagnotta SM, Castiglioni I, Ceccarelli M. TCGAbiolinks: an R/Bioconductor package for integrative analysis of TCGA data. Nucleic acids research. 2016 May 5;44(8):e71.
  25. Chen J, Xu J, Li Y, Zhang J, Chen H, Lu J, Wang Z, Zhao X, Xu K, Li Y, Li X. Competing endogenous RNA network analysis identifies critical genes among the different breast cancer subtypes. Oncotarget. 2016 Dec 29;8(6):10171.
  26. Zhou X, Liu J, Wang W. Construction and investigation of breast‐cancer‐specific ceRNA network based on the mRNA and miRNA expression data. IET systems biology. 2014 Jun;8(3):96-103.
  27. Zhou S, Wang L, Yang Q, Liu H, Meng Q, Jiang L, Wang S, Jiang W. Systematical analysis of lncRNA–mRNA competing endogenous RNA network in breast cancer subtypes. Breast cancer research and treatment. 2018 Jun;169:267-75.
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