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Ranking breast cancer drugs and biomarkers identification using machine learning and pharmacogenomics

Research Authors
Aamir Mehmood, Sadia Nawab, Yifan Jin, Hesham Hassan, Aman Chandra Kaushik, Dong-Qing Wei
Research Date
Research Department
Research Member
Research Year
2023
Research Abstract

Breast cancer is one of the major causes of death in women worldwide. It is a diverse illness with substantial intersubject heterogeneity, even among individuals with the same type of tumor, and customized therapy has become increasingly important in this sector. Because of the clinical and physical variability of different kinds of breast cancers, multiple staging and classification systems have been developed. As a result, these tumors exhibit a wide range of gene expression and prognostic indicators. To date, no comprehensive investigation of model training procedures on information from numerous cell line screenings has been conducted together with radiation data. We used human breast cancer cell lines and drug sensitivity information from Cancer Cell Line Encyclopedia (CCLE) and Genomics of Drug Sensitivity in Cancer (GDSC) databases to scan for potential drugs using cell line data. The results are