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KMID : 1132720230210020020
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Genomics & Informatics
2023 Volume.21 No. 2 p.20 ~ p.20
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The genomic landscape associated with resistance to aromatase inhibitors in breast cancer
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Kirithika Sadasivam
Jeevitha Priya Manoharan
Hema Palanisamy
Subramanian Vidyalakshmi
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Abstract
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Aromatase inhibitors (AI) are drugs that are widely used in treating estrogen receptor (ER)?positive breast cancer patients. Drug resistance is a major obstacle to aromatase inhibition therapy. There are diverse reasons behind acquired AI resistance. This study aims at identifying the plausible cause of acquired AI resistance in patients administered with non-steroidal AIs (anastrozole and letrozole). We used genomic, transcriptomic, epigenetic, and mutation data of breast invasive carcinoma from The Cancer Genomic Atlas database. The data was then separated into sensitive and resistant sets based on patients’ responsiveness to the non-steroidal AIs. A sensitive set of 150 patients and a resistant set of 172 patients were included for the study. These data were collectively analyzed to probe into the factors that might be responsible for AI resistance. We identified 17 differentially regulated genes (DEGs) among the two groups. Then, methylation, mutation, miRNA, copy number variation, and pathway analyses were performed for these DEGs. The top mutated genes (FGFR3, CDKN2A, RNF208, MAPK4, MAPK15, HSD3B1, CRYBB2, CDC20B, TP53TG5, and MAPK8IP3) were predicted. We also identified a key miRNA - hsa-mir-1264 regulating the expression of CDC20B. Pathway analysis revealed HSD3B1 to be involved in estrogen biosynthesis. This study reveals the involvement of key genes that might be associated with the development of AI resistance in ER-positive breast cancers and hence may act as a potential prognostic and diagnostic biomarker for these patients.
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KEYWORD
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acquired drug resistance, ER-positive breast cancer, non-steroidal Ais, pathway analysis, TCGA-BRCA patient data
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