RUNX1 and RUNX2 transcription factors function in opposing roles to regulate breast cancer stem cells.

Breast cancer stem cells (BCSCs) are competent to initiate tumor formation and growth and refractory to conventional therapies. Consequently BCSCs are implicated in tumor recurrence. Many signaling cascades associated with BCSCs are critical for epithelial-to-mesenchymal transition (EMT). We developed a model system to mechanistically examine BCSCs in basal-like breast cancer using MCF10AT1 FACS sorted for CD24 (negative/low in BCSCs) and CD44 (positive/high in BCSCs). Ingenuity Pathway Analysis comparing RNA-seq on the CD24-/low versus CD24+/high MCF10AT1 indicates that the top activated upstream regulators include TWIST1, TGFß1, OCT4, and other factors known to be increased in BCSCs and during EMT. The top inhibited upstream regulators include ESR1, TP63, and FAS. Consistent with our results, many genes previously demonstrated to be regulated by RUNX factors are altered in BCSCs. The RUNX2 interaction network is the top significant pathway altered between CD24-/low and CD24+/high MCF10AT1. RUNX1 is higher in expression at the RNA level than RUNX2. RUNX3 is not expressed. While, human-specific quantitative polymerase chain reaction primers demonstrate that RUNX1 and CDH1 decrease in human MCF10CA1a cells that have grown tumors within the murine mammary fat pad microenvironment, RUNX2 and VIM increase. Treatment with an inhibitor of RUNX binding to CBFß for 5 days followed by a 7-day recovery period results in EMT suggesting that loss of RUNX1, rather than increase in RUNX2, is a driver of EMT in early stage breast cancer. Increased understanding of RUNX regulation on BCSCs and EMT will provide novel insight into therapeutic strategies to prevent recurrence.

When False-Positives Arise: Troubleshooting a SARS-Coronavirus-2 (SARS-CoV-2) Detection Assay on a Semi-Automated Platform.

BACKGROUND: During the COVID-19 pandemic, many molecular diagnostic laboratories performed high-throughput SARS-CoV-2 testing often with implementation of automated workflows. In parallel, vaccination campaigns resulted increasingly in specimens from fully vaccinated patients, with resultant clinical inquiries regarding positive results in this patient population. This prompted a quality improvement initiative to investigate the semi-automated testing workflow for false-positive results. The troubleshooting workflow is described and procedural improvements are outlined that serve as a resource for other molecular diagnostic laboratories that need to overcome testing anomalies in a semi-automated environment. METHODS: This workflow utilized the MagMax-96 Viral RNA kit and the CDC 2019-nCoV RT-qPCR Panel on the Agilent Bravo Liquid-Handler (Bravo). Screening of the environment, personnel, and the mechanical performance of instrumentation using low Ct checkerboard challenges was executed to identify sources of cross-contamination. Evaluation of the assay and reporting design was conducted. RESULTS: Specimen contamination was observed during the viral extraction process on the Bravo. Changes to the program reduced plate contamination by 50% and importantly revealed consistent hallmarks of contaminated samples. We adjusted the reporting algorithm using these indicators of false positives. False positives that were identified made up 0.11% of the 45 000+ tests conducted over the following 8 months. CONCLUSIONS: These adjustments provided confident and quality results while maintaining turnaround time for patients and pandemic-related public health initiatives. This corrected false-positive rate is concordant with previously published studies from diagnostic laboratories utilizing automated systems and may be considered a laboratory performance standard for this type of testing.