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Additional file 1. Supplementary Tables: Table S1. Molecular subtypes of breast cancer cell lines. Table S2. Histopathological features of tissue microarray samples. Table S3. Clinical-pathological parameters and CBP & GCN5 expression in DCIS and breast carcinoma cases. Supplementary Figures: Fig. S1. Baseline expression level of ER and HER2 in a panel of normal cancer breast cells. Fig. S2. Efficiency of transfection kinetics for a, b HER2 siRNA, c-e ER siRNA and f, g both ER and HER2 siRNAs. Fig. S3. Efficiency of transfection kinetics for a, b CBP siRNA in MCF7 and T47D cells. Fig. S4. Uncropped blots for a CBP and b GCN5 proteins in normal and cancer breast cells. Fig. S5. Uncropped blots for HER2 and CBP proteins in a SkBr3 and b BT-474 cells transfected with HER2 siRNA for 24-96 hours. Fig. S6. Uncropped blots for CBP protein in a SkBr3 and b BT-474 cells treated with Trastuzumab for 24-96 hours. Fig. S7. Uncropped blots for ER and CBP proteins in a MCF7 and b T47D cells transfected with ER siRNA for 24-96 hours. Fig. S8. Uncropped blots for ER and CBP proteins in a BT-474 cells transfected with ER siRNA for 24-96 hours. Uncropped blots for CBP protein in b MCF7, c T47D and d BT-474 cells treated with Tamoxifen for 24-96 hours. Fig. S9. Uncropped blots for ER, HER2 and CBP proteins in a BT-474 cells transfected with ER and HER2 siRNAs for 24-96 hours. Uncropped blots for CBP protein in b BT-474 cells treated with Tamoxifen and Trastuzumab combination for 24-96 hours. Fig. S10. Uncropped blots for ER and CBP proteins in a MCF7 and b T47D cells transfected with CBP siRNA for 24-96 hours. Fig. S11. Kaplan-Meier survival curves of disease-free survival for CBP expression in a Luminal A, b Luminal B HER2 negative, c Luminal B HER2 positive, d HER2-positive and e Triple negative breast cancer patients. Fig. S12. Kaplan-Meier survival curves of disease-free survival for GCN5 expression in a Luminal A, b Luminal B HER2 negative, c Luminal B HER2 positive, d HER2-positive and e Triple negative breast cancer patients.

usc Cancer of the central nervous system (CNS) is ranked as the 19th most prevalent form of the disease in 2020. This study aims to identify candidate biomarkers and metabolic pathways affected by paclitaxel and etoposide, which serve as potential treatments for glioblastoma, and are linked to the pathogenesis of glioblastoma. We utilized an untargeted metabolomics approach using the highly sensitive ultra-high-performance liquid chromatography-electrospray ionization quadrupole time-of-flight mass spectrometry (UHPLC-ESI-QTOF-MS) for identification. In this study, 92 and 94 metabolites in U87 and U373 cell lines were profiled, respectively. The produced metabolites were then analyzed utilizing t-tests, volcano plots, and enrichment analysis modules. Our analysis revealed distinct metabolites to be significantly dysregulated (nutriacholic acid, L-phenylalanine, L-arginine, guanosine, ADP, hypoxanthine, and guanine), and to a lesser extent, mevalonic acid in paclitaxel and/or etoposide treated cells. Furthermore, both urea and citric acid cycles, and metabolism of polyamines and amino acids (aspartate, arginine, and proline) were significantly enriched. These findings can be used to create a map that can be utilized to assess the antitumor effect of paclitaxel and/or etoposide within the studied cancer cells. Refereed/Peer-reviewed