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All Journal Jurnal Ilmu Dasar Jurnal Statistika Universitas Muhammadiyah Semarang Unisda Journal of Mathematics and Computer Science (UJMC) J Statistika: Jurnal Ilmiah Teori dan Aplikasi Statistika JAST : Jurnal Aplikasi Sains dan Teknologi EIGEN MATHEMATICS JOURNAL Mandalika Mathematics and Educations Journal Seminar Nasional Hasil Riset dan Pengabdian (SNHRP) Southeast Asian Journal of Islamic Education Journal of Community Research and Engagement
Gangga Anuraga
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Humanities Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Engineering Environmental Science Health Professions Languange, Linguistic, Communication & Media Mathematics Public Health Social Sciences Other

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Journal : EIGEN MATHEMATICS JOURNAL

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Integrative Bioinformatics and Statistical Approaches for Identifying Prognostic Biomarkers and Therapeutic Targets in Breast Cancer Zulhan Widya Baskara; Anuraga, Gangga; Anurogo, Dito; Fitriani, Fenny; Rochmanto, Hani Brilianti; Baskara, Zulhan Widya
Eigen Mathematics Journal Vol 8 No 1 (2025): June
Publisher : University of Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29303/emj.v8i1.277

Abstract

Breast cancer is a leading cause of cancer-related mortality worldwide, necessitating the identification of reliable biomarkers for prognosis and targeted therapy. This study employed an integrative bioinformatics and statistical approach to analyze differentially expressed genes (DEGs) in breast cancer using datasets GSE70947 and GSE22820 from the gene expression omnibus (GEO). A protein-protein interaction (PPI) network was constructed to identify hub genes, followed by functional enrichment analysis to determine their biological significance. Survival analysis using the KMplot database revealed that CDC45, KIF2C, CCNB1, KIF4A, CENPE, CHEK1, KIF15, AURKB, NCAPG, and HJURP were significantly associated with poor prognosis. These genes were primarily enriched in cell cycle regulation, mitotic spindle organization, and DNA damage response, highlighting their role in tumor progression. Among them, CCNB1, CHEK1, and AURKB were strongly linked to cell cycle progression and checkpoint regulation, while KIF2C and CENPE played essential roles in mitotic division. High expression levels of these genes correlated with reduced overall survival, suggesting their potential as prognostic biomarkers and therapeutic targets in breast cancer.These discoveries help us better understand how breast cancer develops and point to potential targets for tailored treatments.
Co-Authors Achmad Chikham Nouriel Rosyadi Alfisyahrina Hapsery Anggi Emeliani Arianto, Bagus Wicaksono Bambang Widjanarko Otok Dito Anurogo, Dito Dwi Cahya Julia Kartikasari Edy Sulistiyawan, Edy Erika Zahra Fitriananta Faramaysty, Laura Sekar Fathur Rahman Fitriani, Fenny Hani Brilianti Rochmanto Harun Al Azies Intan Amelia Haryanto Izequela De Jesus Madeira Jerhi Wahyu Fernanda, Jerhi Wahyu Lusia, Dwi Ayu Madeira, Izequela De Jesus Permadina K. Arieska Pingky Febriyanti pramesti, wara Pretesya Septiliani Syukur Putri Amelia Divaio Rabiatul Adawiyah Ratu Bunga Prawesti Arie Salim Renita Donasari, Renita Risa Mudji Istiawati Sadewa, Arief Triatmaja Permana Saputri Dyah Pratiwi Utami, Diva Aprilia Trisha Zulhan Widya Baskara