Quantitative Immunofluorescence Reveals the Signature of Active B-cell Receptor Signaling in Diffuse Large B-cell Lymphoma

Cui

American Journal of Surgical Pathology

et al. 2015

B-cell receptor (BCR) signaling is crucial for the survival of normal and neoplastic B cells, and inhibitors targeting BCR signaling pathways have shown promising therapeutic outcomes for patients with B-cell lymphomas. In the current study, we analyzed de novo diffuse large B-cell lymphoma without BCR expression (DLBCL, BCR) in 25 cases to determine the BCR/phosphatidylinositol-3-kinase/AKT (BCR/PI3K/AKT) signaling status, clinicopathologic features, and underlying causes leading to the loss of BCR. On the basis of clinical features, 15 (60%) DLBCL, BCR patients were classified into the low-risk group, and 18 (86%) experienced complete remission. Morphologically and immunophenotypically, DLBCL, BCR demonstrated centroblastic cytology (21/25, 84%) and germinal center B-cell-like cell origin (18/25, 72%). Other components in BCR complexity remained intact, on the basis of immunohistochemical findings. Epstein-Barr virus infection, deficiency in B-lineage transcription factors (PAX5, Oct-2, and Bob.1), and oncogene rearrangement did not seem to be associated with BCR loss. The activated form of signaling proteins (pSYK and pAKT) involved in the BCR/PI3K/AKT pathway were expressed at low levels in DLBCL, BCR tissue. In vitro validation revealed that in DLBCL, BCR cell lines, the BCR/PI3K/AKT pathway did not respond to BCR stimulation or inhibition. Our findings suggest that DLBCL, BCR was characterized by a silent BCR/PI3K/AKT pathway, germinal center phenotype, and low risk and may not be a candidate for BCR-targeted therapies.

Section: Discussionsupporting

confidence: 71%

mentioning

confidence: 99%

Loss of B-cell Receptor Expression Defines a Subset of Diffuse Large B-cell Lymphoma Characterized by Silent BCR/PI3K/AKT Signaling and a Germinal Center Phenotype Displaying Low-risk Clinicopathologic Features

Cui

American Journal of Surgical Pathology

et al. 2015

“…6 Btk is highly expressed in multiple myeloma, 7 acute myeloid leukemia (AML), 8 chronic lymphocytic leukemia (CLL), 9 and non-Hodgkin’s lymphoma (NHL). 10, 11 Given its importance, Btk has emerged as a molecular target for treatment of B-lineage leukemias and lymphomas. In addition, Btk plays a key role in macrophage polarization through signaling downstream of TLR4.…”

Section: Introductionmentioning

confidence: 99%

Optimized Near-IR Fluorescent Agents for in Vivo Imaging of Btk Expression

et al. 2015

Bruton’s tyrosine kinase (Btk) is intricately involved in anti-apototic signaling pathways in cancer and in regulating innate immune response. A number of Btk inhibitors are in development for use in treating B-cell malignancies and certain immunologic diseases. To develop robust companion imaging diagnostics for in vivo use, we set up to explore the effects of red wavelength fluorochrome modifications of two highly potent irreversible Btk inhibitors, Ibrutinib and AVL-292. Surprisingly, we found that subtle chemical differences in the fluorochrome had considerable effects on target localization. Based on iterative designs, we developed a single optimized version with superb in vivo imaging characteristics enabling single cell Btk imaging in vivo. This agent (Ibrutinib-SiR-COOH) is expected to be valuable chemical tool in deciphering Btk biology in cancer and host cells in vivo.

“…We first made several modifications to the model to accommodate the differences between normal BCR signaling and aberrant BCR signaling in ABC DLBCL. Instead of applying a temporal upstream stimulus, we assumed constitutive LYN and SYK phosphorylation as observed both in ABC DLBCL cell lines and in primary DLBCL patient samples (2,42) (see Materials and Methods). Additionally, we accounted for genetic alterations in members of the BCR signaling network in TMD8 compared to normal B cells.…”

Section: Resultsmentioning

confidence: 99%

Effective Combination Therapies for B-cell Lymphoma Predicted by a Virtual Disease Model

Goldstein

Jiang

et al. 2017

Cancer Research

The complexity of cancer signaling networks limits the efficacy of most single agent treatments and brings about challenges in identifying effective combinatorial therapies. In this study, we used chronic active B cell receptor (BCR) signaling in diffuse large B cell lymphoma (DLBCL) as a model system to establish a computational framework to optimize combinatorial therapy in silico. We constructed a detailed kinetic model of the BCR signaling network, which captured the known complex crosstalk between the NFκB, ERK and AKT pathways and multiple feedback loops. Combining this signaling model with a data-derived tumor growth model, we predicted viability responses of many single drug and drug combinations in agreement with experimental data. Under this framework, we exhaustively predicted and ranked the efficacy and synergism of all possible combinatorial inhibitions of eleven currently targetable kinases in the BCR signaling network. Ultimately, our work establishes a detailed kinetic model of the core BCR signaling network and provides the means to explore the large space of possible drug combinations. Major Findings Using chronic active B cell receptor (BCR) signaling in diffuse large B cell lymphoma (DLBCL) as a model system, we developed a kinetic-modeling based computational framework for predicting effective combination therapy in silico. By integrative modeling of signal transduction, drug kinetics and tumor growth, we were able to directly predict drug-induced cell viability responses at various dosages, which were in agreement with published cell line experimental data. We implemented computational screening methods that identified potent and synergistic combinations in silico and validated our independent predictions in vitro. Quick Guide to Equations and Assumptions A kinetic model was constructed for the BCR signaling network according to the following rules. For protein-protein binding interactions, we assumed that this type of reaction were under equilibrium and solved the steady-state level of protein complex analytically in the model, false[ AB false] = 1 ( 1 + K ( [ T A ] + [ T B ] ) ) - false( 1 + K false( false[ T A false] + false[ T B false] false) false) 2 - 4 K 2 [ T A ] [ T B ] 2 K where [TA] and [TB] stand for the total concentration of protein species A and B respectively, [AB] represents the concentration of the protein complex, K is the inverse of the dissociation constant Kd. For kinase catalyzed reactions, we adopted the classic Michaelis-Menten kinetics, j 1 d P d t = 1 k cat [ E ] [ S ] K m + [ S ] where 1dPdt is the rate of catalytic product formation, kcat is the turnover rate, Km is the Michaelis-Menten constant, [E] and [S] are concentration of enzyme and substrate respectively. Each interaction in the BCR signaling network was depicted by corresponding terms according to above rules. The full kinetic model consists of 28 state...