AN UPDATED DEBARCODING TOOL FOR MASS CYTOMETRY WITH CELL TYPE-SPECIFIC AND CELL SAMPLE-SPECIFIC STRINGENCY ADJUSTMENT

Pooled sample analysis by mass cytometry barcoding carries many advantages: reduced antibody consumption, increased sample throughput, removal of cell doublets, reduction of cross-contamination by sample carryover, and the elimination of tube-to-tube-variability in antibody staining. A single-cell debarcoding algorithm was previously developed to improve the accuracy and yield of sample deconvolution, but this method was limited to using fixed parameters for debarcoding stringency filtering, which could introduce cell-specific or sample-specific bias to cell yield in scenarios where barcode staining intensity and variance are not uniform across the pooled samples. To address this issue, we have updated the algorithm to output debarcoding parameters for every cell in the sample-assigned FCS files, which allows for visualization and analysis of these parameters via flow cytometry analysis software. This strategy can be used to detect cell type-specific and sample-specific effects on the underlying cell data that arise during the debarcoding process. An additional benefit to this strategy is the decoupling of barcode stringency filtering from the debarcoding and sample assignment process. This is accomplished by removing the stringency filters during sample assignment, and then filtering after the fact with 1-and 2-dimensional gating on the debarcoding parameters which are output with the FCS files. These data exploration strategies serve as an important quality check for barcoded mass cytometry datasets, and allow cell type and sample-specific stringency adjustment that can remove bias in cell yield introduced during the debarcoding process

Dual blockade of lipid and cyclin-dependent kinases induces synthetic lethality in malignant glioma

Malignant glioma, the most common primary brain tumor, is generally incurable. Although phosphatidylinositol-3-kinase (PI3K) signaling features prominently in glioma, inhibitors generally block proliferation rather than induce apoptosis. Starting with an inhibitor of both lipid and protein kinases that induced prominent apoptosis and that failed early clinical development because of its broad target profile and overall toxicity, we identified protein kinase targets, the blockade of which showed selective synthetic lethality when combined with PI3K inhibitors. Prioritizing protein kinase targets for which there are clinical inhibitors, we demonstrate that cyclin-dependent kinase (CDK)1/2 inhibitors, siRNAs against CDK1/2, and the clinical CDK1/2 inhibitor roscovitine all cooperated with the PI3K inhibitor PIK-90, blocking the antiapoptotic protein Survivin and driving cell death. In addition, overexpression of CDKs partially blocked some of the apoptosis caused by PIK-75. Roscovitine and PIK-90, in combination, were well tolerated in vivo and acted in a synthetic-lethal manner to induce apoptosis in human glioblastoma xenografts. We also tested clinical Akt and CDK inhibitors, demonstrating induction of apoptosis in vitro and providing a preclinical rationale to test this combination therapy in patients

A pharmacological map of the PI3-K family defines a role for p110alpha in insulin signaling

Phosphoinositide 3-kinases (PI3-Ks) are an important emerging class of drug targets, but the unique roles of PI3-K isoforms remain poorly defined. We describe here an approach to pharmacologically interrogate the PI3-K family. A chemically diverse panel of PI3-K inhibitors was synthesized, and their target selectivity was biochemically enumerated, revealing cryptic homologies across targets and chemotypes. Crystal structures of three inhibitors bound to p110gamma identify a conformationally mobile region that is uniquely exploited by selective compounds. This chemical array was then used to define the PI3-K isoforms required for insulin signaling. We find that p110alpha is the primary insulin-responsive PI3-K in cultured cells, whereas p110beta is dispensable but sets a phenotypic threshold for p110alpha activity. Compounds targeting p110alpha block the acute effects of insulin treatment in vivo, whereas a p110beta inhibitor has no effect. These results illustrate systematic target validation using a matrix of inhibitors that span a protein family