EGFR and PDGFRA co-expression and heterodimerization in glioblastoma tumor sphere lines.

Concurrent amplifications of EGFR and PDGFRA have been reported in up to 5% of glioblastoma (GBM) and it remains unclear why such independent amplification events, and associated receptor overexpression, would be adaptive during glioma evolution. Here, we document that EGFR and PDGFRA protein co-expression occurs in 37% of GBM. There is wide cell-to-cell variation in the expressions of these receptor tyrosine kinases (RTKs) in stable tumor sphere lines, frequently defining tumor cell subpopulations with distinct sensitivities to growth factors and RTK inhibitors. We also find evidence for functional transactivation of PDGFRA by EGFR and EGF-induced receptor heterodimerization, both of which are abolished by EGFR inhibitors. These results indicate that GBM growth responses to targeted therapies previously tested in clinical trials are strongly influenced by the balance of EGFR and PDGFRA activation in individual cells, which is heterogeneous at baseline.

T cells translate individual, quantal activation into collective, analog cytokine responses via time-integrated feedbacks.

Variability within isogenic T cell populations yields heterogeneous 'local' signaling responses to shared antigenic stimuli, but responding clones may communicate 'global' antigen load through paracrine messengers, such as cytokines. Such coordination of individual cell responses within multicellular populations is critical for accurate collective reactions to shared environmental cues. However, cytokine production may saturate as a function of antigen input, or be dominated by the precursor frequency of antigen-specific T cells. Surprisingly, we found that T cells scale their collective output of IL-2 to total antigen input over a large dynamic range, independently of population size. Through experimental quantitation and computational modeling, we demonstrate that this scaling is enforced by an inhibitory cross-talk between antigen and IL-2 signaling, and a nonlinear acceleration of IL-2 secretion per cell. Our study reveals how time-integration of these regulatory loops within individual cell signaling generates scaled collective responses and can be leveraged for immune monitoring. DOI: http://dx.doi.org/10.7554/eLife.01944.001.

Multidimensional single-cell analysis of BCR signaling reveals proximal activation defect as a hallmark of chronic lymphocytic leukemia B cells.

PURPOSE: Chronic Lymphocytic Leukemia (CLL) is defined by a perturbed B-cell receptor-mediated signaling machinery. We aimed to model differential signaling behavior between B cells from CLL and healthy individuals to pinpoint modes of dysregulation. EXPERIMENTAL DESIGN: We developed an experimental methodology combining immunophenotyping, multiplexed phosphospecific flow cytometry, and multifactorial statistical modeling. Utilizing patterns of signaling network covariance, we modeled BCR signaling in 67 CLL patients using Partial Least Squares Regression (PLSR). Results from multidimensional modeling were validated using an independent test cohort of 38 patients. RESULTS: We identified a dynamic and variable imbalance between proximal (pSYK, pBTK) and distal (pPLCγ2, pBLNK, ppERK) phosphoresponses. PLSR identified the relationship between upstream tyrosine kinase SYK and its target, PLCγ2, as maximally predictive and sufficient to distinguish CLL from healthy samples, pointing to this juncture in the signaling pathway as a hallmark of CLL B cells. Specific BCR pathway signaling signatures that correlate with the disease and its degree of aggressiveness were identified. Heterogeneity in the PLSR response variable within the B cell population is both a characteristic mark of healthy samples and predictive of disease aggressiveness. CONCLUSION: Single-cell multidimensional analysis of BCR signaling permitted focused analysis of the variability and heterogeneity of signaling behavior from patient-to-patient, and from cell-to-cell. Disruption of the pSYK/pPLCγ2 relationship is uncovered as a robust hallmark of CLL B cell signaling behavior. Together, these observations implicate novel elements of the BCR signal transduction as potential therapeutic targets.

The IL-6/JAK/Stat3 feed-forward loop drives tumorigenesis and metastasis.

We have investigated the importance of interleukin-6 (IL-6) in promoting tumor growth and metastasis. In human primary breast cancers, increased levels of IL-6 were found at the tumor leading edge and positively correlated with advanced stage, suggesting a mechanistic link between tumor cell production of IL-6 and invasion. In support of this hypothesis, we showed that the IL-6/Janus kinase (JAK)/signal transducer and activator of transcription 3 (Stat3) pathway drives tumor progression through the stroma and metastatic niche. Overexpression of IL-6 in tumor cell lines promoted myeloid cell recruitment, angiogenesis, and induced metastases. We demonstrated the therapeutic potential of interrupting this pathway with IL-6 receptor blockade or by inhibiting its downstream effectors JAK1/2 or Stat3. These clinically relevant interventions did not inhibit tumor cell proliferation in vitro but had profound effects in vivo on tumor progression, interfering broadly with tumor-supportive stromal functions, including angiogenesis, fibroblast infiltration, and myeloid suppressor cell recruitment in both the tumor and pre-metastatic niche. This study provides the first evidence for IL-6 expression at the leading edge of invasive human breast tumors and demonstrates mechanistically that IL-6/JAK/Stat3 signaling plays a critical and pharmacologically targetable role in orchestrating the composition of the tumor microenvironment that promotes growth, invasion, and metastasis.

Diversity training for signal transduction: leveraging cell-to-cell variability to dissect cellular signaling, differentiation and death.

Populations of 'identical' cells are rarely truly identical. Even when in the same state of differentiation, isogenic cells may vary in expression of key signaling regulators, activate signal transduction at different thresholds, and consequently respond heterogeneously to a given stimulus. Here, we review how new experimental and analytical techniques are suited to connect these different levels of variability, quantitatively mapping the effects of cell-to-cell variability on cellular decision-making. In particular, we summarize how this helps classify signaling regulators according to the impact of their variability on biological functions. We further discuss how variability can also be leveraged to shed light on the molecular mechanisms regulating cellular signaling, from the individual cell to the population of cells as a whole.

Cell-to-cell variability analysis dissects the plasticity of signaling of common γ chain cytokines in T cells.

Natural variability in the abundance of signaling regulators can lead to divergence in cell fate, even within genetically identical cells that share a common differentiation state. We introduce cell-to-cell variability analysis (CCVA), an experimental and computational methodology that quantifies the correlation between variability in signaling regulator abundance and variation in the sensitivity of cells to stimuli. With CCVA, we investigated the unexpected effects of the interleukin 2 (IL-2) receptor α chain (IL-2Rα) on the sensitivity of primary mouse T lymphocytes to cytokines that signal through receptors that have the common γ chain (γ(c)). Our work showed that increased IL-2Rα abundance decreased the concentration of IL-2 required for a half-maximal activation (EC(50)) of the downstream effector signal transducer and activator of transcription 5 (STAT5), but reduced the responsiveness to IL-7 or IL-15, without affecting the EC(50) values of other γ(c) cytokines. To investigate the mechanism of the effect of IL-2Rα on γ(c) cytokine signaling, we introduced a Bayesian-inference computational framework that models the formation of receptor signaling complexes with data from previous biophysical measurements. With this framework, we found that a model in which IL-2Rα drives γ(c) depletion through the assembly of functional IL-2R complexes was consistent with both the CCVA data and experimental measurements. The combination of CCVA and computational modeling produced quantitative understanding of the crosstalk between γ(c) cytokine receptor signaling in T lymphocytes.

Human Langerhans cells use an IL-15R-α/IL-15/pSTAT5-dependent mechanism to break T-cell tolerance against the self-differentiation tumor antigen WT1.

Human CD34(+) progenitor-derived Langerhans-type dendritic cells (LCs) are more potent stimulators of T-cell immunity against tumor and viral antigens in vitro than are monocyte-derived DCs (moDCs). The exact mechanisms have remained elusive until now, however. LCs synthesize the highest amounts of IL-15R-α mRNA and protein, which binds IL-15 for presentation to responder lymphocytes, thereby signaling the phosphorylation of signal transducer and activator of transcription 5 (pSTAT5). LCs electroporated with Wilms tumor 1 (WT1) mRNA achieve sufficiently sustained presentation of antigenic peptides, which together with IL-15R-α/IL-15, break tolerance against WT1 by stimulating robust autologous, WT1-specific cytolytic T-lymphocytes (CTLs). These CTLs develop from healthy persons after only 7 days' stimulation without exogenous cytokines and lyse MHC-restricted tumor targets, which include primary WT1(+) leukemic blasts. In contrast, moDCs require exogenous rhuIL-15 to phosphorylate STAT5 and attain stimulatory capacity comparable to LCs. LCs therefore provide a more potent costimulatory cytokine milieu for T-cell activation than do moDCs, thus accounting for their superior stimulation of MHC-restricted Ag-specific CTLs without need for exogenous cytokines. These data support the use of mRNA-electroporated LCs, or moDCs supplemented with exogenous rhuIL-15, as vaccines for cancer immunotherapy to break tolerance against self-differentiation antigens shared by tumors.