ABSTRACT
Breast cancer is the most commonly occurring malignancy in women and the second most common cause of cancer-related deaths. ER+ breast cancer constitutes approximately 70% of all breast cancer cases. The standard of care for ER+ breast cancer involves estrogen antagonists such as tamoxifen or fulvestrant in combination with CDK4/6 inhibitors such as palbociclib. However, these treatments are often not curative, with disease recurrence and metastasis being responsible for patient mortality. Overexpression of the epigenetic regulator, BRD4, has been shown to be a negative prognostic indicator in breast cancer, and BET family inhibitors such as ARV-825 and ABBV-744 have garnered interest for their potential to improve and prolong the response to current therapeutic strategies. The current work examined the potential of utilizing ARV-825 and ABBV-744 to increase the effectiveness of tamoxifen or fulvestrant plus palbociclib. ARV-825 was effective in both p53 wild-type (WT) breast tumor cells and in cells lacking functional p53 either alone or in combination with tamoxifen, while the effectiveness of ABBV-744 was limited to fulvestrant plus palbociclib in p53 WT cells. These differential effects may be related to the capacity to suppress c-Myc, a downstream target of BRD4.
ABSTRACT
Methods such as liquid chromatography coupled with high-resolution mass spectrometry (LC-HRMS) are crucial for differentiating compounds with highly similar masses. This is a necessity when analyzing highly complex samples; however, the size of high-resolution LC-HRMS data sets can cause difficulties when applying advanced data analysis techniques. In this work, LC-HRMS analyses of known amphetamine samples and unknown bacterial lipid samples were carried out, and multivariate curve resolution-alternating least squares (MCR-ALS) was applied to the data to obtain mathematical separation of overlapped analyte signals. In order to minimize computational strain, a novel strategy was developed which minimizes the number of irrelevant masses analyzed at full resolution. To do this, data were first binned to unit mass resolution, and MCR-ALS was performed. This provided mathematical components for each analyte present plus background components. In the resolved spectral profiles of analyte components, masses above a preset intensity threshold were extracted, discarding all other masses, and expanded to successively higher levels of resolution, applying MCR-ALS at each level. These steps were repeated until 0.001 amu resolution was achieved, as dictated by the resolution of the instrument-in this case, a time-of-flight mass spectrometer. This strategy allowed for the accurate recovery of all known amphetamine compounds and select bacterial lipid extracts while minimizing the size of the data, therefore minimizing computational analysis time and data storage requirements. This relatively simple strategy enables the effective coupling of LC-HRMS with MCR-ALS.
