LinkedIn

 آمار

تعداد نشریات20
تعداد شماره‌ها1,191
تعداد مقالات10,861
تعداد مشاهده مقاله73,140,965
تعداد دریافت فایل اصل مقاله13,103,049
Dayakar, Sivapriya, Pandi, Anitha, Pandi, Chandra, Arumugam, Paramasivam, Jayaseelan, Vijayashree Priyadharsini. (1403). Deciphering the Genetic Alterations in PIK3CA Gene Interacting Network and Their Putative Association with Breast Cancer: A Computational Approach. سامانه مدیریت نشریات علمی, 16(1), 49-58. doi: 10.30476/mejc.2024.100126.1972
Sivapriya Dayakar; Anitha Pandi; Chandra Pandi; Paramasivam Arumugam; Vijayashree Priyadharsini Jayaseelan. "Deciphering the Genetic Alterations in PIK3CA Gene Interacting Network and Their Putative Association with Breast Cancer: A Computational Approach". سامانه مدیریت نشریات علمی, 16, 1, 1403, 49-58. doi: 10.30476/mejc.2024.100126.1972
Dayakar, Sivapriya, Pandi, Anitha, Pandi, Chandra, Arumugam, Paramasivam, Jayaseelan, Vijayashree Priyadharsini. (1403). 'Deciphering the Genetic Alterations in PIK3CA Gene Interacting Network and Their Putative Association with Breast Cancer: A Computational Approach', سامانه مدیریت نشریات علمی, 16(1), pp. 49-58. doi: 10.30476/mejc.2024.100126.1972
Dayakar, Sivapriya, Pandi, Anitha, Pandi, Chandra, Arumugam, Paramasivam, Jayaseelan, Vijayashree Priyadharsini. Deciphering the Genetic Alterations in PIK3CA Gene Interacting Network and Their Putative Association with Breast Cancer: A Computational Approach. سامانه مدیریت نشریات علمی, 1403; 16(1): 49-58. doi: 10.30476/mejc.2024.100126.1972

Deciphering the Genetic Alterations in PIK3CA Gene Interacting Network and Their Putative Association with Breast Cancer: A Computational Approach

Middle East Journal of Cancer
مقاله 4، دوره 16، شماره 1 - شماره پیاپی 61، فروردین 2025، صفحه 49-58    اصل مقاله (1.77 M)
نوع مقاله: Original Article(s)
شناسه دیجیتال (DOI): 10.30476/mejc.2024.100126.1972
نویسندگان
Sivapriya Dayakar1، 2؛ Anitha Pandi2؛ Chandra Pandi3؛ Paramasivam Arumugam2؛ Vijayashree Priyadharsini Jayaseelan* 2
1Saveetha Medical College and Hospital, Saveetha Institute of Medical and Technical Sciences [SIMATS], Saveetha University, Chennai, India
2Clinical Genetics Lab, Centre for Cellular and Molecular Research, Saveetha Dental College and Hospital, Saveetha Institute of Medical and Technical Sciences [SIMATS], Saveetha University, Chennai, India
3Molecular Biology Lab, Centre for Cellular and Molecular Research, Saveetha Dental College and Hospital, Saveetha Institute of Medical and Technical Sciences [SIMATS], Saveetha Universi ty, Chennai, India
چکیده
Background: Cancer is a polygenic complex disorder involving a network of genes. The phosphatidylinositol 3-kinase (PIK3CA) has been reported as an oncogene that plays a role in many cancer types. The present study aims to demonstrate the association between the genetic alterations observed in the PIK3CA gene network and its role in establishing breast cancer.
Method: In the present observational study, we used multiple tools (STRING, cBioportal, PANTHER, and UALCAN) to demonstrate the genetic alterations in the Breast Cancer Dataset (TCGA, Firehose Legacy). The PIK3CA gene interaction network was deduced, followed by the identification of genetic alterations, gene ontology, gene expression and survival analysis.
Results: The PIK3CA gene was found to harbor 36% of genetic alterations in the form of gene amplification and mutations. The gene expression profile indicated the significant downregulation of PIK3CA gene transcripts. Interestingly, the Kaplan Meier survival analysis demonstrated that low/medium expression of PIK3CA presented with a good prognosis when compared with the high expression group. These results support the fact that PIK3CA is oncogenic.
Conclusion: The PIK3CA gene has been considered as one of the potential druggable targets for breast cancer. The genetic alterations reported in the gene might influence its function. Therefore, further experimental validation is required to provide more insight into the functional association of mutations. Also, the effect of tumor suppressors and epigenetic factors targeting PIK3CA has to be assessed to gain more insight into the increased expression of PIK3CA in breast cancer patients.

تازه های تحقیق

Vijayashree Priyadharsini Jayaseelan (Google Scholar)

کلیدواژه‌ها
Breast neoplasms؛ Candidate gene؛ Mutation؛ Gene ontology
مراجع
  1. Yanes T, Young MA, Meiser B, James PA. Clinical applications of polygenic breast cancer risk: a critical review and perspectives of an emerging field. Breast Cancer Res. 2020;22(1):21. doi: 10.1186/s13058-020-01260-3.
  2. Sung H, Ferlay J, Siegel RL, Laversanne M, Soerjomataram I, Jemal A, et al. Global Cancer Statistics 2020: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries. CA Cancer J Clin. 2021;71(3):209-49. doi: 10.3322/caac.21660. 
  3. Arnold M, Morgan E, Rumgay H, Mafra A, Singh D, Laversanne M, et al. Current and future burden of breast cancer: Global statistics for 2020 and 2040. 2022;66:15-23. doi: 10.1016/j.breast.2022.08.010. 
  4. Viral P, Pavithran K, Beena K, Shaji A, Vijaykumar DK. Ten-year survival outcome of breast cancer patients in India. J Carcinog. 2021;20:1. doi: 10.4103/jcar.JCar_26_20.
  5. Saatci O, Huynh-Dam KT, Sahin O. Endocrine resistance in breast cancer: from molecular mechanisms to therapeutic strategies. J Mol Med (Berl). 2021;99(12):1691-710. doi: 10.1007/s00109-021-02136-5
  6. Pan H, Gray R, Braybrooke J, Davies C, Taylor C, McGale P, et al. 20-year risks of breast-cancer recurrence after stopping endocrine therapy at 5 years. N Engl J Med. 2017;377(19):1836-46. doi: 10.1056/NEJMoa1701830.
  7. Alqahtani A, Ayesh HSK, Halawani H. PIK3CA Gene mutations in solid malignancies: association with clinicopathological parameters and prognosis. Cancers (Basel). 2019;12(1):93. doi: 10.3390/cancers12010093. 
  8. Martínez-Sáez O, Chic N, Pascual T, Adamo B, Vidal M, González-Farré B, et al. Frequency and spectrum of PIK3CA somatic mutations in breast cancer. Breast Cancer Res. 2020;22(1):45. doi: 10.1186/s13058-020-01284-9. 
  9. Merid SK, Goranskaya D, Alexeyenko A. Distinguishing between driver and passenger mutations in individual cancer genomes by network enrichment analysis. BMC Bioinformatics. 2014;15(1):308. doi: 10.1186/1471-2105-15-308.
  10. Waarts MR, Stonestrom AJ, Park YC, Levine RL. Targeting mutations in cancer. J Clin Invest. 2022;132(8):e154943. doi: 10.1172/JCI154943.
  11. Nakai M, Yamada T, Sekiya K, Sato A, Hankyo M, Kuriyama S, et al. Use of liquid biopsy to detect PIK3CA mutation in metastatic breast cancer. J Nippon Med Sch. 2022;89(1):66-71. doi: 10.1272/jnms.JNMS.2022_89-107. 
  12. Li J, Sun A, Zhong G, He Y, Xiong H, Yuan X. Mutation analysis of a 10-gene panel for colorectal cancer in Huizhou, Guangdong Province of China. J Int Med Res. 2021;49(11):3000605211061040. doi: 10.1177/03000605211061040.
  13. Long F, Li S, Xu Y, Liu M, Zhang X, Zhou J, et al. Dynamic gene screening enabled the identification of a 10-gene panel for early detection and progression assessment of gastric cancer. Comput Struct Biotechnol J. 2022;21:677-87. doi: 10.1016/j.csbj.2022.12.036.
  14. Ji X, Che N, Lin R, Chen J, Wu X. Efficient ten-gene analysis of NSCLC tissue samples by next-generation sequencing. Pathol Res Pract. 2019;215(5):1066-70. doi: 10.1016/j.prp.2019.02.017. 
  15. Cerami E, Gao J, Dogrusoz U, Gross BE, Sumer SO, Aksoy BA, et al. The cBio cancer genomics portal: an open platform for exploring multidimensional cancer genomics data. Cancer Discov. 2012;2(5):401-4. doi: 10.1158/2159-8290.CD-12-0095. Erratum in: Cancer Discov. 2012;2(10):960.
  16. Gao J, Aksoy BA, Dogrusoz U, Dresdner G, Gross B, Sumer SO, et al. Integrative analysis of complex cancer genomics and clinical profiles using the cBioPortal. Sci Signal. 2013;6(269):pl1. doi 10.1126/scisignal.2004088.
  17. Szklarczyk D, Gable AL, Lyon D, Junge A, Wyder S, Huerta-Cepas J, et al. STRING v11: protein-protein association networks with increased coverage, supporting functional discovery in genome-wide experimental datasets. Nucleic Acids Res. 2019;47(D1):D607-D613. doi: 10.1093/nar/gky1131.
  18. Mi H, Thomas P. PANTHER pathway: an ontology-based pathway database coupled with data analysis tools. Methods Mol Biol. 2009;563:123-40. doi: 10.1007/978-1-60761-175-2_7.
  19. Mi H, Ebert D, Muruganujan A, Mills C, Albou LP, Mushayamaha T, et al. PANTHER version 16: a revised family classification, tree-based classification tool, enhancer regions and extensive API. Nucleic Acids Res. 2021;49(D1):D394-D403. doi: 10.1093/nar/gkaa1106.
  20. Chandrashekar DS, Karthikeyan SK, Korla PK, Patel H, Shovon AR, Athar M, et al. UALCAN: An update to the integrated cancer data analysis platform. 2022;25:18-27. doi: 10.1016/j.neo.2022.01.001.
  21. Rasti AR, Guimaraes-Young A, Datko F, Borges VF, Aisner DL, Shagisultanova E.PIK3CA mutations drive therapeutic resistance in human epidermal growth factor receptor 2-positive breast cancer. JCO Precis Oncol. 2022;6:e2100370. doi: 10.1200/PO.21.00370.
  22. Liu N, Wang X, Li X, Lv X, Xie H, Guo Z, et al. Identification of effective natural PIK3CA H1047R inhibitors by computational study. Aging (Albany NY). 2021;13(16):20246-57. doi: 10.18632/aging.203409. 
  23. Correia L, Magno R, Xavier JM, de Almeida BP, Duarte I, Esteves F, et al. Allelic expression imbalance of PIK3CA mutations is frequent in breast cancer and prognostically significant. NPJ Breast Cancer. 2022;8(1):71. doi: 10.1038/s41523-022-00435-9.
  24. Palimaru I, Brügmann A, Wium-Andersen MK, Nexo E, Sorensen BS. Expression of PIK3CA, PTEN mRNA and PIK3CA mutations in primary breast cancer: association with lymph node metastases. 2013;2(1):464. doi: 10.1186/2193-1801-2-464.
  25. Alowiri NH, Hanafy SM, Haleem RA, Abdellatif A. PIK3CA and PTEN genes expressions in breast cancer. Asian Pac J Cancer Prev. 2019;20(9):2841-6. doi: 10.31557/APJCP.2019.20.9.2841.
  26. Jaikumarr Ram A, Girija As S, Jayaseelan VP, Arumugam P. Overexpression of BASP1 indicates a poor prognosis in head and neck squamous cell carcinoma. Asian Pac J Cancer Prev. 2020;21(11):3435-9. doi: 10.31557/APJCP.2020.21.11.3435.
  27. Jayaseelan VP, Ramesh A, Arumugam P. Breast cancer and DDT: putative interactions, associated gene alterations, and molecular pathways. Environ Sci Pollut Res Int. 2021;28(21):27162-73. doi: 10.1007/s11356-021-12489-6.
  28. Aparna J, Smiline-Girija AS, Paramasivam A, Vijayashree-Priyadharsini J. Deciphering the genetic alterations in matrix metallo-proteinase gene family and its putative association with head and neck squamous cell carcinoma. Mol Biol Res Commun. 2021;10(1):13-22. doi: 10.22099/mbrc.2020.38344.1544.
  29. J VP, A P. Virtual screening of mutations in antioxidant genes and its putative association with HNSCC: An in silico approach. Mutat Res. 2020;821:111710. doi: 10.1016/j.mrfmmm.2020.111710.
  30. Fathima T, Arumugam P, Girija As S, Priyadharsini JV. Decoding the genetic alterations in genes of DNMT family (DNA methyl-transferase) and their association with head and neck squamous cell carcinoma. Asian Pac J Cancer Prev. 2020;21(12):3605-12. doi: 10.31557/APJCP.2020.21.12.3605.
آمار
تعداد مشاهده مقاله: 380
تعداد دریافت فایل اصل مقاله: 286


سامانه مدیریت نشریات علمی. قدرت گرفته از سیناوب