Agonist/ antagonist compounds’ mechanism of action on estrogen receptor-positive breast cancer: a system-level investigation assisted by meta-analysis

سال انتشار: 1400
نوع سند: مقاله کنفرانسی
زبان: انگلیسی
مشاهده: 220

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شناسه ملی سند علمی:

IBIS10_119

تاریخ نمایه سازی: 5 تیر 1401

چکیده مقاله:

The largest group of breast cancer patients are estrogen receptor-positive (ER+). There is a vast amount ofstudies focused on breast cancer. That vastness provides the requisites for the integration and meta-analysisof the related studies. Meta-analysis could lead to more accurate results than single investigations.In the present work, a specific layout for meta-analysis of multiple RNA-seq datasets is proposed in order toobtain a final accurate, least error-prone methodology. Meta-analysis was separately performed on twoestrogen-treated MCF۷ and T۴۷D versus untreated cell lines to obtain meta-differentially expressed genes.Also, only shared significant genes between MCF۷ and T۴۷D cell lines were enriched to obtain morestringent results. The ER+ patients respond to both ER agonist (E۲) and ER antagonists (Tamoxifen,Fulvestrant, and Brilanestrant). Hence, we compared the meta-analysis results with genes obtained from ERantagonists to understand the function of ER and its affected genes. Genes involved in human mitochondriaand several keratin family members' genes were up-regulated in the meta-analysis. Still, they showed noalteration neither in individual datasets treated with E۲ and ER antagonists. Our findings indicated thatTamoxifen does not block specific genes directly affected by ER and has no effect on their expression.Moreover, to the best of the authors' knowledge, pathways were identified that were not previously reportedin BC. Meta-analysis of RNA-seq data with correct methodology could identify new genes and pathwaysthat are essential in breast cancer. If there are suitable datasets, it is recommended that the methodology beused for other diseases to obtain more accurate results.

نویسندگان

Zeynab Piryaei

Department of Bioinformatics, Kish International Campus University of Tehran, Kish, Iran- Laboratory of Complex Biological Systems and Bio-informatics (CBB), Department of Bioinformatics, Institute of Biochemistry and Biophysics (IBB), University of Tehra

Zahra Salehi

Department of Immunology, School of Medicine, Tehran University of Medical Sciences, Tehran, Iran

Mohammad Reza Tahsili

Department of Biology, Faculty of Science, University of Qom, Qom, Iran

Esmaeil Ebrahimie

School of Animal and Veterinary Sciences, The University of Adelaide, South Australia, Adelaide, Australia- Genomics Research Platform, School of Life Sciences, La Trobe University, Melbourne, Victoria, Australia

Mansour Ebrahimi

Department of Biology, Faculty of Science, University of Qom, Qom, Iran

Kaveh Kavousi

Laboratory of Complex Biological Systems and Bio-informatics (CBB), Department of Bioinformatics, Institute of Biochemistry and Biophysics (IBB), University of Tehran, Iran