Mcl-1 and Bcl-xL levels predict responsiveness to dual MEK/Bcl-2 inhibition in B-cell malignancies

Immunophenotyping with (phospho)protein profiling and fluorescent cell barcoding for single-cell signaling analysis and biomarker discovery

The microenvironment of hematologic cancers contributes to tumor cell survival and proliferation, as well as treatment resistance. Understanding tumor- and drug-induced changes to the immune cell composition and functionality is therefore critical for implementing optimal treatment strategies and for the development of novel cancer therapies. The liquid nature of peripheral blood makes this organ uniquely suited for single-cell studies by flow cytometry. (Phospho)protein profiles detected by flow cytometry analyses have been shown to correlate with ex vivo drug sensitivity and to predict treatment outcomes in hematologic cancers, demonstrating that this method is suitable for pre-clinical studies. Here, we present a flow cytometry protocol that combines multi-parameter immunophenotyping with single-cell (phospho)protein profiling. The protocol makes use of fluorescent cell barcoding, which means that multiple cell samples, either collected from different donors or exposed to different treatment conditions, can be combined and analyzed as one experiment. This reduces variability between samples, increases the throughput of the experiment, and lowers experimental costs. This protocol may serve as a guide for the use and further development of assays to study immunophenotype and cell signaling at single-cell resolution in normal and malignant cells. The read-outs may provide biological insight into cancer pathogenesis, identify novel drug targets, and ultimately serve as a biomarker to guide clinical decision-making.

Standardized assays to monitor drug sensitivity in hematologic cancers

The principle of drug sensitivity testing is to expose cancer cells to a library of different drugs and measure its effects on cell viability. Recent technological advances, continuous approval of targeted therapies, and improved cell culture protocols have enhanced the precision and clinical relevance of such screens. Indeed, drug sensitivity testing has proven diagnostically valuable for patients with advanced hematologic cancers. However, different cell types behave differently in culture and therefore require optimized drug screening protocols to ensure that their ex vivo drug sensitivity accurately reflects in vivo drug responses. For example, primary chronic lymphocytic leukemia (CLL) and multiple myeloma (MM) cells require unique microenvironmental stimuli to survive in culture, while this is less the case for acute myeloid leukemia (AML) cells. Here, we present our optimized and validated protocols for culturing and drug screening of primary cells from AML, CLL, and MM patients, and a generic protocol for cell line models. We also discuss drug library designs, reproducibility, and quality controls. We envision that these protocols may serve as community guidelines for the use and interpretation of assays to monitor drug sensitivity in hematologic cancers and thus contribute to standardization. The read-outs may provide insight into tumor biology, identify or confirm treatment resistance and sensitivity in real time, and ultimately guide clinical decision-making.

A tumor microenvironment model of chronic lymphocytic leukemia enables drug sensitivity testing to guide precision medicine

The microenvironment of chronic lymphocytic leukemia (CLL) cells in lymph nodes, spleen, and bone marrow provides survival, proliferation, and drug resistance signals. Therapies need to be effective in these compartments, and pre-clinical models of CLL that are used to test drug sensitivity must mimic the tumor microenvironment to reflect clinical responses. Ex vivo models have been developed that capture individual or multiple aspects of the CLL microenvironment, but they are not necessarily compatible with high-throughput drug screens. Here, we report on a model that has reasonable associated costs, can be handled in a regularly equipped cell lab, and is compatible with ex vivo functional assays including drug sensitivity screens. The CLL cells are cultured with fibroblasts that express the ligands APRIL, BAFF and CD40L for 24 h. The transient co-culture was shown to support survival of primary CLL cells for at least 13 days, and mimic in vivo drug resistance signals. Ex vivo sensitivity and resistance to the Bcl-2 antagonist venetoclax correlated with in vivo responses. The assay was used to identify treatment vulnerabilities and guide precision medicine for a patient with relapsed CLL. Taken together, the presented CLL microenvironment model enables clinical implementation of functional precision medicine in CLL.

PI3K inhibitors in chronic lymphocytic leukemia: where do we go from here?

Phosphatidylinositol 3-kinase (PI3K) inhibitors are effective in chronic lymphocytic leukemia (CLL). However, the severe toxicity profile associated with the first-generation inhibitors idelalisib and duvelisib, combined with the availability of other more tolerable agents, have limited their use. CLL is still considered incurable, and relapse after treatment, development of resistance, and treatment intolerance are common. It is therefore of interest to optimize the administration of currently approved PI3K inhibitors and to develop next-generation agents to improve tolerability, so that this class of agents will be considered an effective and safe treatment option when needed. These efforts are reflected in the large number of emerging clinical trials with PI3K inhibitors in CLL. Current strategies to overcome treatment limitations include intermittent dosing, which is established for copanlisib and zandelisib and under investigation for duvelisib and parsaclisib. A second strategy is to combine the PI3K inhibitor with another novel agent, either as a continuous regimen or a fixedduration regimen, to deepen responses. In addition to these approaches, it is of interest to identify higher-resolution actionable biomarkers that can predict treatment responses and toxicity, and inform personalized treatment decisions. Here, we discuss the current status of PI3K inhibitors in CLL, factors limiting the use of currently approved PI3K inhibitors in CLL, current strategies to overcome these limitations, and where to go next.

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.

Functional precision cancer medicine: drug sensitivity screening enabled by cell culture models

Functional precision medicine is a new, emerging area that can guide cancer treatment by capturing information from direct perturbations of tumor-derived, living cells, such as by drug sensitivity screening. Precision cancer medicine as currently implemented in clinical practice has been driven by genomics, and current molecular tumor boards rely extensively on genomic characterization to advise on therapeutic interventions. However, genomic biomarkers can only guide treatment decisions for a fraction of the patients. In this review we provide an overview of the current state of functional precision medicine, highlight advances for drug-sensitivity screening enabled by cell culture models, and discuss how artificial intelligence (AI) can be coupled to functional precision medicine to guide patient stratification.

Tipping the balance: toward rational combination therapies to overcome venetoclax resistance in mantle cell lymphoma

Mantle cell lymphoma (MCL), an aggressive, but incurable B-cell lymphoma, is genetically characterized by the t(11;14) translocation, resulting in the overexpression of Cyclin D1. In addition, deregulation of the B-cell lymphoma-2 (BCL-2) family proteins BCL-2, B-cell lymphoma-extra large (BCL-XL), and myeloid cell leukemia-1 (MCL-1) is highly common in MCL. This renders these BCL-2 family members attractive targets for therapy; indeed, the BCL-2 inhibitor venetoclax (ABT-199), which already received FDA approval for the treatment of chronic lymphocytic leukemia (CLL) and acute myeloid leukemia (AML), shows promising results in early clinical trials for MCL. However, a significant subset of patients show primary resistance or will develop resistance upon prolonged treatment. Here, we describe the underlying mechanisms of venetoclax resistance in MCL, such as upregulation of BCL-XL or MCL-1, and the recent (clinical) progress in the development of inhibitors for these BCL-2 family members, followed by the transcriptional and (post-)translational (dys)regulation of the BCL-2 family proteins, including the role of the lymphoid organ microenvironment. Based upon these insights, we discuss how rational combinations of venetoclax with other therapies can be exploited to prevent or overcome venetoclax resistance and improve MCL patient outcome.

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.