Phospho Flow Cytometry with Fluorescent Cell Barcoding for Single Cell Signaling Analysis and Biomarker Discovery

Mutational analysis and protein profiling predict drug sensitivity in multiple myeloma cell lines

INTRODUCTION

Multiple myeloma (MM) is a heterogeneous disease where cancer-driver mutations and aberrant signaling may lead to disease progression and drug resistance. Drug responses vary greatly, and there is an unmet need for biomarkers that can guide precision cancer medicine in this disease.

METHODS

To identify potential predictors of drug sensitivity, we applied integrated data from drug sensitivity screening, mutational analysis and functional signaling pathway profiling in 9 cell line models of MM. We studied the sensitivity to 33 targeted drugs and their association with the mutational status of cancer-driver genes and activity level of signaling proteins.

RESULTS

We found that sensitivity to mitogen-activated protein kinase kinase 1 (MEK1) and phosphatidylinositol-3 kinase (PI3K) inhibitors correlated with mutations in NRAS/KRAS, and PI3K family genes, respectively. Phosphorylation status of MEK1 and protein kinase B (AKT) correlated with sensitivity to MEK and PI3K inhibition, respectively. In addition, we found that enhanced phosphorylation of proteins, including Tank-binding kinase 1 (TBK1), as well as high expression of B cell lymphoma 2 (Bcl-2), correlated with low sensitivity to MEK inhibitors.

DISCUSSION

Taken together, this study shows that mutational status and signaling protein profiling might be used in further studies to predict drug sensitivities and identify resistance markers in MM.

Functional Testing to Characterize and Stratify PI3K Inhibitor Responses in Chronic Lymphocytic Leukemia

PURPOSE

PI3K inhibitors (PI3Ki) are approved for relapsed chronic lymphocytic leukemia (CLL). Although patients may show an initial response to these therapies, development of treatment intolerance or resistance remain clinical challenges. To overcome these, prediction of individual treatment responses based on actionable biomarkers is needed. Here, we characterized the activity and cellular effects of 10 PI3Ki and investigated whether functional analyses can identify treatment vulnerabilities in PI3Ki-refractory/intolerant CLL and stratify responders to PI3Ki.

EXPERIMENTAL DESIGN

Peripheral blood mononuclear cell samples (n = 51 in total) from treatment-naïve and PI3Ki-treated patients with CLL were studied. Cells were profiled against 10 PI3Ki and the Bcl-2 antagonist venetoclax. Cell signaling and immune phenotypes were analyzed by flow cytometry. Cell viability was monitored by detection of cleaved caspase-3 and the CellTiter-Glo assay.

RESULTS

pan-PI3Kis were most effective at inhibiting PI3K signaling and cell viability, and showed activity in CLL cells from both treatment-naïve and idelalisib-refractory/intolerant patients. CLL cells from idelalisib-refractory/intolerant patients showed overall reduced protein phosphorylation levels. The pan-PI3Ki copanlisib, but not the p110δ inhibitor idelalisib, inhibited PI3K signaling in CD4+ and CD8+ T cells in addition to CD19+ B cells, but did not significantly affect T-cell numbers. Combination treatment with a PI3Ki and venetoclax resulted in synergistic induction of apoptosis. Analysis of drug sensitivities to 73 drug combinations and profiling of 31 proteins stratified responders to idelalisib and umbralisib, respectively.

CONCLUSIONS

Our findings suggest novel treatment vulnerabilities in idelalisib-refractory/intolerant CLL, and indicate that ex vivo functional profiling may stratify PI3Ki responders.

Next-Generation Personalized Medicine: Implementation of Variability Patterns for Overcoming Drug Resistance in Chronic Diseases

Chronic diseases are a significant healthcare problem. Partial or complete non-responsiveness to chronic therapies is a significant obstacle to maintaining the long-term effect of drugs in these patients. A high degree of intra- and inter-patient variability defines pharmacodynamics, drug metabolism, and medication response. This variability is associated with partial or complete loss of drug effectiveness. Regular drug dosing schedules do not comply with physiological variability and contribute to resistance to chronic therapies. In this review, we describe a three-phase platform for overcoming drug resistance: introducing irregularity for improving drug response; establishing a deep learning, closed-loop algorithm for generating a personalized pattern of irregularity for overcoming drug resistance; and upscaling the algorithm by implementing quantified personal variability patterns along with other individualized genetic and proteomic-based ways. The closed-loop, dynamic, subject-tailored variability-based machinery can improve the efficacy of existing therapies in patients with chronic diseases.

Computational Pipeline for Rational Drug Combination Screening in Patient-Derived Cells

In many complex diseases, such as cancers, resistance to monotherapies easily occurs, and longer-term treatment responses often require combinatorial therapies as next-line regimens. However, due to a massive number of possible drug combinations to test, there is a need for systematic and rational approaches to finding safe and effective drug combinations for each individual patient. This protocol describes an ecosystem of computational methods to guide high-throughput combinatorial screening that help experimental researchers to identify optimal drug combinations in terms of synergy, efficacy, and/or selectivity for further preclinical and clinical investigation. The methods are demonstrated in the context of combinatorial screening in primary cells of leukemia patients, where the translational aim is to identify drug combinations that show not only high synergy but also maximal cancer-selectivity. The mechanism-agnostic and cost-effective computational methods are widely applicable to various cancer types, which are amenable to drug testing, as the computational methods take as input only the phenotypic measurements of a subset of drug combinations, without requiring target information or genomic profiles of the patient samples.

Plasma LOX-Products and Monocyte Signaling Is Reduced by Adjunctive Cyclooxygenase-2 Inhibitor in a Phase I Clinical Trial of Tuberculosis Patients

Introduction

Eicosanoids and intracellular signaling pathways are potential targets for host-directed therapy (HDT) in tuberculosis (TB). We have explored the effect of cyclooxygenase 2 inhibitor (COX-2i) treatment on eicosanoid levels and signaling pathways in monocytes.

Methods

Peripheral blood mononuclear cells isolated from TB patients included in a randomized phase I clinical trial of standard TB treatment with (n=21) or without (n=18) adjunctive COX-2i (etoricoxib) were analyzed at baseline, day 14 and day 56. Plasma eicosanoids were analyzed by ELISA and liquid chromatography-mass spectrometry (LC-MS), plasma cytokines by multiplex, and monocyte signaling by phospho-flow with a defined set of phospho-specific antibodies.

Results

Lipoxygenase (LOX)-derived products (LXA4 and 12-HETE) and pro-inflammatory cytokines were associated with TB disease severity and were reduced during TB therapy, possibly accelerated by adjunctive COX-2i. Phosphorylation of p38 MAPK, NFkB, Erk1/2, and Akt in monocytes as well as plasma levels of MIG/CXCL9 and procalcitonin were reduced in the COX-2i group compared to controls.

Conclusion

COX-2i may reduce excess inflammation in TB via the LOX-pathway in addition to modulation of phosphorylation patterns in monocytes. Immunomodulatory effects of adjunctive COX-2i in TB should be further investigated before recommended for use as a HDT strategy.

Carboxyl-Terminal Src Kinase Binds CD28 upon Activation and Mutes Downstream Signaling

Full T cell activation depends on stimulation of the TCR in conjunction with a costimulatory receptor. The involvement of costimulatory molecules is potent, and a mechanistic understanding of how downstream signaling is regulated is required to fully understand T cell responsiveness. In this study, a proteomic approach was taken to identify the interactomes of the coreceptors CD2 and CD28. These coreceptors are both positive regulators of T cell activation, but CD28 less potently induces TCR-proximal signaling. C-terminal Src kinase (CSK), a negative regulator of TCR signaling, was identified as a specific and direct interactor only of activated CD28. CSK is recruited to CD28 upon T cell activation, and the in vitro kinase activity of CSK is enhanced in the presence of phosphorylated CD28. Interruption of the CSK/CD28 interaction prior to TCR/CD28 costimulation induces a signaling response which mimics the more potent CD2-induced TCR-proximal pathway activation. Thus, CD28 functions as a novel adaptor protein for CSK, and CSK regulates signaling downstream of CD28.

Cryopreservation of primary B cells minimally influences their signaling responses

Phospho flow is a powerful approach to detect cell signaling aberrations, identify biomarkers and assess pharmacodynamics, and can be performed using cryopreserved samples. The effects of cryopreservation on signaling responses and the reproducibility of phospho flow measurements are however unknown in many cell systems. Here, B lymphocytes were isolated from healthy donors and patients with the B cell malignancy chronic lymphocytic leukemia and analyzed by phospho flow using phospho-specific antibodies targeting 20 different protein epitopes. Cells were analyzed both at basal conditions and after activation of cluster of differentiation 40 (CD40) or the B cell receptor. Pharmacodynamics of the novel pathway inhibitor ibrutinib was also assessed. At all conditions, fresh cells were compared to cryopreserved cells. Minimal variation between fresh and frozen samples was detected. Reproducibility was tested by running samples from the same donors in different experiments. The results demonstrate reproducibility across different phospho flow runs and support the use of cryopreserved samples in future phospho flow studies of B lymphocytes.