• info@icbcongress.com
• English
• Persian

• Login

Create Free Account

INTERNATIONAL CONGRESS OF

CancerGenetics

• Integrative Bioinformatics to Identify Cell Cycle-Related Prognostic Biomarkers in Triple-Negative Breast Cancer

• Maryam Sadat Sajadi Javan,^1,* Arsham Azari Dehkordi,² Pegah Bozorgzad Moghim ,³ Shiva Vaheb Hosseinabadi,⁴ Mansoureh Azadeh,⁵
  1. Zist Fanavari Novin Biotechnology Institute
  2. Zist Fanavari Novin Biotechnology Institute
  3. Zist Fanavari Novin Biotechnology Institute
  4. Zist Fanavari Novin Biotechnology Institute
  5. Zist Fanavari Novin Biotechnology Institute
  
  
  
• Introduction: Triple-negative Breast Cancer (TNBC) is the most aggressive subtype of breast cancer, characterized by the absence of estrogen, progesterone, and HER2 receptors. This molecular signature represents a considerable clinical burden due to the poor prognosis of this disease and the lack of approved targeted therapies. The recent development of bioinformatics and high-throughput sequencing offers a new chance to explore the multifaceted regulatory networks controlling TNBC. Among thousands of long non-coding RNAs (lncRNAs), these molecules and microRNAs (miRNAs) in particular, as key regulators of gene expression, are implicated in a variety of vital cellular processes, such as proliferation, apoptosis, and metastasis. The ceRNA hypothesis suggests a new regulatory mechanism: lncRNAs could function as a “sponge” of miRNAs to modulate the expression of target mRNAs. To discover novel biomarkers and therapeutic targets, such complex lncRNA-miRNA-mRNA networks must be deciphered by downstream research.
• Methods: To screen for TNBC differentially expressed genes (DEGs), a microarray analysis was conducted using the GSE65216 dataset (downloaded from Gene Expression Omnibus [GEO]). The above dataset was used to analyze the gene expression of TNBC tumor tissue relative to normal control samples using the GPL570 platform. A cut-off value of adjusted p < 0.05 and |LogFC| > 1 was considered significant to obtain the DEGs by using the GEO2R online tool. The expression levels of extraction genes were validated by GEPIA2 database and the effect on survival was also evaluated. The gene expression and clinical data for various cancers were also analyzed from The Cancer Genome Atlas (TCGA) database. The Kyoto Encyclopedia of Genes and Genomes (KEGG) database was used to analyze functional enrichment of the specific genes. Interactions between proteins (PPI) were analyzed using the STRING database to identify key hub genes. miRNA targets were predicted with miRDB, miRTarBase, and TargetScan. And the interactive long non-coding RNAs (lncRNAs) were screened using DIANA-LncBase v3.0 database. The lncRNA-miRNA-mRNA co-expression network was established and presented with Cytoscape software.
• Results: Several upregulated hub genes significantly enriched in the cell cycle pathway were confirmed by KEGG analysis.TTK was identified as a crucial hub gene (adj. P. Val = 9.98E-27, LogFC = 6.47). There was also an up-regulation in MAD2L1 (adj. P. Val = 6.96E-30, LogFC = 5.95). BUB1 was significantly overexpressed (adj. P.Val = 1.04E-28, LogFC = 5.31). CDK1 (adj. P. Val = 4.92E-29, LogFC = 6.37) and CCNB2 (adj.P. Val = 1.60E-29, LogFC = 6.17) were also recognized as critical hub genes.Up-regulation of these hub genes is closely related to poor overall survival of TNBC patients, asshowed by GEPIA2 gene expression and overall survival analysis. CeRNA network of miRNA-lncRNA-mRNA showed hsa-miR-5688, hsa-miR-335-5p, hsa-miR-340-5p, hsa-miR-101-3p, hsa-miR-143-3p, and hsa-miR-497-3p and lncRNAs such as TUG1, NEAT1, SNHG12, XIST, and MALAT1 were observed to be associated with the core genes. These results indicate that the screened genes may play a role as the TNBC predictive markers.
• Conclusion: This research highlights the significance of key hub genes associated with TNBC development. The upregulated genes, TTK, MAD2L1, BUB1, CDK1 and CCNB2 composed the network of five hub genes by bioinformatics. These genes are highly associated with worse overall survival in TNBC patients. These genes and their regulatory miRNAs, lncRNAs together might help in the uncontrolled cell proliferation and tumorigenesis. Such discoveries not only provide novel molecular insights into the genesis of TNBC but also may serve as novel biomarkers for early diagnosis and therapeutic targets.
• Keywords: Triple‑Negative Breast Cancer, Hub Genes, Cell Cycle, Bioinformatics Analysis