FoxO1 signaling in B cell malignancies and its therapeutic targeting.

FoxO transcription factors (FoxO1, FoxO3a, FoxO4, FoxO6) are a highly evolutionary conserved subfamily of the 'forkhead' box proteins. They have traditionally been considered tumor suppressors, but FoxO1 also exhibits oncogenic properties. The complex nature of FoxO1 is illustrated by its various roles in B cell development and differentiation, immunoglobulin gene rearrangement and cell-surface B cell receptor (BCR) structure, DNA damage control, cell cycle regulation, and germinal center reaction.

FoxO1/Rictor axis induces a nongenetic adaptation to ibrutinib via Akt activation in chronic lymphocytic leukemia.

Bruton tyrosine kinase (BTK) inhibitor therapy induces peripheral blood lymphocytosis in chronic lymphocytic leukemia (CLL), which lasts for several months. It remains unclear whether nongenetic adaptation mechanisms exist, allowing CLL cells' survival during BTK inhibitor-induced lymphocytosis and/or playing a role in therapy resistance. We show that in approximately 70% of CLL cases, ibrutinib treatment in vivo increases Akt activity above pretherapy levels within several weeks, leading to compensatory CLL cell survival and a more prominent lymphocytosis on therapy.

Computational Design of Pore-Forming Peptides with Potent Antimicrobial and Anticancer Activities.

Peptides that form transmembrane barrel-stave pores are potential alternative therapeutics for bacterial infections and cancer. However, their optimization for clinical translation is hampered by a lack of sequence-function understanding. Recently, we have designed the first synthetic barrel-stave pore-forming antimicrobial peptide with an identified function of all residues.

Integrative protocol for quantifying cholesterol-related sterols in human serum samples and building decision support systems.

The growing interest in clinical diagnostics has recently focused on metabolic biomarkers. Here, we present a protocol for sample preparation, extraction of cholesterol-related sterols, and quantification of 10 sterols in human blood serum samples using targeted liquid chromatography-tandem mass spectrometry (LC-MS/MS). We also describe steps of machine learning techniques to develop novel decision-making systems that offer potential benefits in disease monitoring and surveillance by measuring metabolic pathways.