Definition of a novel breast tumor-specific classifier based on secretome analysis.

BACKGROUND: During cancer development, the normal tissue microenvironment is shaped by tumorigenic events. Inflammatory mediators and immune cells play a key role during this process. However, which molecular features most specifically characterize the malignant tissue remains poorly explored. METHODS: Within our institutional tumor microenvironment global analysis (T-MEGA) program, we set a prospective cohort of 422 untreated breast cancer patients. We established a dedicated pipeline to generate supernatants from tumor and juxta-tumor tissue explants and quantify 55 soluble molecules using Luminex or MSD. Those analytes belonged to five molecular families: chemokines, cytokines, growth factors, metalloproteinases, and adipokines. RESULTS: When looking at tissue specificity, our dataset revealed some breast tumor-specific characteristics, as IL-16, as well as some juxta-tumor-specific secreted molecules, as IL-33. Unsupervised clustering analysis identified groups of molecules that were specific to the breast tumor tissue and displayed a similar secretion behavior. We identified a tumor-specific cluster composed of nine molecules that were secreted fourteen times more in the tumor supernatants than the corresponding juxta-tumor supernatants. This cluster contained, among others, CCL17, CCL22, and CXCL9 and TGF-ß1, 2, and 3. The systematic comparison of tumor and juxta-tumor secretome data allowed us to mathematically formalize a novel breast cancer signature composed of 14 molecules that segregated tumors from juxta-tumors, with a sensitivity of 96.8% and a specificity of 96%. CONCLUSIONS: Our study provides the first breast tumor-specific classifier computed on breast tissue-derived secretome data. Moreover, our T-MEGA cohort dataset is a freely accessible resource to the biomedical community to help advancing scientific knowledge on breast cancer.

RNF43 G659fs is an oncogenic colorectal cancer mutation and sensitizes tumor cells to PI3K/mTOR inhibition.

The RNF43_p.G659fs mutation occurs frequently in colorectal cancer, but its function remains poorly understood and there are no specific therapies directed against this alteration. In this study, we find that RNF43_p.G659fs promotes cell growth independent of Wnt signaling. We perform a drug repurposing library screen and discover that cells with RNF43_p.G659 mutations are selectively killed by inhibition of PI3K signaling. PI3K/mTOR inhibitors yield promising antitumor activity in RNF43659mut isogenic cell lines and xenograft models, as well as in patient-derived organoids harboring RNF43_p.G659fs mutations. We find that RNF43659mut binds p85 leading to increased PI3K signaling through p85 ubiquitination and degradation. Additionally, RNA-sequencing of RNF43659mut isogenic cells reveals decreased interferon response gene expression, that is reversed by PI3K/mTOR inhibition, suggesting that RNF43659mut may alter tumor immunity. Our findings suggest a therapeutic application for PI3K/mTOR inhibitors in treating RNF43_p.G659fs mutant cancers.

PD-L1 and ICOSL discriminate human Secretory and Helper dendritic cells in cancer, allergy and autoimmunity.

Dendritic cells (DC) are traditionally classified according to their ontogeny and their ability to induce T cell response to antigens, however, the phenotypic and functional state of these cells in cancer does not necessarily align to the conventional categories. Here we show, by using 16 different stimuli in vitro that activated DCs in human blood are phenotypically and functionally dichotomous, and pure cultures of type 2 conventional dendritic cells acquire these states (termed Secretory and Helper) upon appropriate stimuli. PD-L1highICOSLlow Secretory DCs produce large amounts of inflammatory cytokines and chemokines but induce very low levels of T helper (Th) cytokines following co-culturing with T cells. Conversely, PD-L1lowICOSLhigh Helper DCs produce low levels of secreted factors but induce high levels and a broad range of Th cytokines. Secretory DCs bear a single-cell transcriptomic signature indicative of mature migratory LAMP3+ DCs associated with cancer and inflammation. Secretory DCs are linked to good prognosis in head and neck squamous cell carcinoma, and to response to checkpoint blockade in Melanoma. Hence, the functional dichotomy of DCs we describe has both fundamental and translational implications in inflammation and immunotherapy.

The PD-L1/4-1BB Bispecific Antibody-Anticalin Fusion Protein PRS-344/S095012 Elicits Strong T-Cell Stimulation in a Tumor-Localized Manner.

PURPOSE: While patients responding to checkpoint blockade often achieve remarkable clinical responses, there is still significant unmet need due to resistant or refractory tumors. A combination of checkpoint blockade with further T-cell stimulation mediated by 4-1BB agonism may increase response rates and durability of response. A bispecific molecule that blocks the programmed cell death 1 (PD-1)/programmed cell death 1 ligand 1 (PD-L1) axis and localizes 4-1BB costimulation to a PD-L1-positive (PD-L1+) tumor microenvironment (TME) or tumor draining lymph nodes could maximize antitumor immunity and increase the therapeutic window beyond what has been reported for anti-4-1BB mAbs. EXPERIMENTAL DESIGN: We generated and characterized the PD-L1/4-1BB bispecific molecule PRS-344/S095012 for target binding and functional activity in multiple relevant in vitro assays. Transgenic mice expressing human 4-1BB were transplanted with human PD-L1-expressing murine MC38 cells to assess in vivo antitumoral activity. RESULTS: PRS-344/S095012 bound to its targets with high affinity and efficiently blocked the PD-1/PD-L1 pathway, and PRS-344/S095012-mediated 4-1BB costimulation was strictly PD-L1 dependent. We demonstrated a synergistic effect of both pathways on T-cell stimulation with the bispecific PRS-344/S095012 being more potent than the combination of mAbs. PRS-344/S095012 augmented CD4-positive (CD4+) and CD8-positive (CD8+) T-cell effector functions and enhanced antigen-specific T-cell stimulation. Finally, PRS-344/S095012 demonstrated strong antitumoral efficacy in an anti-PD-L1-resistant mouse model in which soluble 4-1BB was detected as an early marker for 4-1BB agonist activity. CONCLUSIONS: The PD-L1/4-1BB bispecific PRS-344/S095012 efficiently combines checkpoint blockade with a tumor-localized 4-1BB-mediated stimulation burst to antigen-specific T cells, more potent than the combination of mAbs, supporting the advancement of PRS-344/S095012 toward clinical development. See related commentary by Shu et al., p. 3182.

A multivariate modeling framework to quantify immune checkpoint context-dependent stimulation on T cells.

Cells receive, and adjust to, various stimuli, which function as part of complex microenvironments forming their "context". The possibility that a given context impacts the response to a given stimulus defines "context-dependency" and it explains large parts of the functional variability of physiopathological and pharmacological stimuli. Currently, there is no framework to analyze and quantify context-dependency over multiple contexts and cellular response outputs. We established an experimental system including a stimulus of interest, applied to an immune cell type in several contexts. We studied the function of OX40 ligand (OX40L) on T helper (Th) cell differentiation, in 4 molecular (Th0, Th1, Th2, and Th17) and 11 dendritic cell (DC) contexts (monocyte-derived DC and cDC2 conditions). We measured 17 Th output cytokines in 302 observations, and developed a statistical modeling strategy to quantify OX40L context-dependency. This revealed highly variable context-dependency, depending on the output cytokine and context type itself. Among molecular contexts, Th2 was the most influential on OX40L function. Among DC contexts, the DC type rather than the activating stimuli was dominant in controlling OX40L context-dependency. This work mathematically formalizes the complex determinants of OX40L functionality, and provides a unique framework to decipher and quantify the context-dependent variability of any biomolecule or drug function.

YAP1 and PRDM14 converge to promote cell survival and tumorigenesis.

The transcriptional co-activator YAP1 oncogene is the downstream effector of the Hippo pathway, which regulates tissue homeostasis, organ size, regeneration, and tumorigenesis. Multiple cancers are dependent on sustained expression of YAP1 for cell proliferation, survival, and tumorigenesis, but the molecular basis of this oncogene dependency is not well understood. To identify genes that can functionally substitute for YAP1, we performed a genome-scale genetic rescue screen in YAP1-dependent colon cancer cells expressing an inducible YAP1-specific shRNA. We found that the transcription factor PRDM14 rescued cell proliferation and tumorigenesis upon YAP1 suppression in YAP1-dependent cells, xenografts, and colon cancer organoids. YAP1 and PRDM14 individually activated the transcription of calmodulin 2 (CALM2) and a glucose transporter SLC2A1 upon YAP1 suppression, and CALM2 or SLC2A1 expression was required for the rescue of YAP1 suppression. Together, these findings implicate PRDM14-mediated transcriptional upregulation of CALM2 and SLC2A1 as key components of oncogenic YAP1 signaling and dependency.

Dissection of intercellular communication using the transcriptome-based framework ICELLNET.

Cell-to-cell communication can be inferred from ligand-receptor expression in cell transcriptomic datasets. However, important challenges remain: global integration of cell-to-cell communication; biological interpretation; and application to individual cell population transcriptomic profiles. We develop ICELLNET, a transcriptomic-based framework integrating: 1) an original expert-curated database of ligand-receptor interactions accounting for multiple subunits expression; 2) quantification of communication scores; 3) the possibility to connect a cell population of interest with 31 reference human cell types; and 4) three visualization modes to facilitate biological interpretation. We apply ICELLNET to three datasets generated through RNA-seq, single-cell RNA-seq, and microarray. ICELLNET reveals autocrine IL-10 control of human dendritic cell communication with up to 12 cell types. Four of them (T cells, keratinocytes, neutrophils, pDC) are further tested and experimentally validated. In summary, ICELLNET is a global, versatile, biologically validated, and easy-to-use framework to dissect cell communication from individual or multiple cell-based transcriptomic profiles.

Interplay between SMAD2 and STAT5A is a critical determinant of IL-17A/IL-17F differential expression.

Interleukins (IL)-17A and F are critical cytokines in anti-microbial immunity but also contribute to auto-immune pathologies. Recent evidence suggests that they may be differentially produced by T-helper (Th) cells, but the underlying mechanisms remain unknown. To address this question, we built a regulatory graph integrating all reported upstream regulators of IL-17A and F, completed by ChIP-seq data analyses. The resulting regulatory graph encompasses 82 components and 136 regulatory links. The graph was then supplemented by logical rules calibrated with original flow cytometry data using naive CD4+ T cells, in conditions inducing IL-17A or IL-17F. The model displays specific stable states corresponding to virtual phenotypes explaining IL-17A and IL-17F differential regulation across eight cytokine stimulatory conditions. Our model analysis points to the transcription factors NFAT2A, STAT5A and SMAD2 as key regulators of the differential expression of IL-17A and IL-17F, with STAT5A controlling IL-17F expression, and an interplay of NFAT2A, STAT5A and SMAD2 controlling IL-17A expression. We experimentally observed that the production of IL-17A was correlated with an increase of SMAD2 transcription, and the expression of IL-17F correlated with an increase of BLIMP-1 transcription, together with an increase of STAT5A expression (mRNA), as predicted by our model. Interestingly, RORγt presumably plays a more determinant role in IL-17A expression as compared to IL-17F expression. In conclusion, we propose the first mechanistic model accounting for the differential expression of IL-17A and F in Th cells, providing a basis to design novel therapeutic interventions in auto-immune and inflammatory diseases.

A Quantitative Multivariate Model of Human Dendritic Cell-T Helper Cell Communication.

Cell-cell communication involves a large number of molecular signals that function as words of a complex language whose grammar remains mostly unknown. Here, we describe an integrative approach involving (1) protein-level measurement of multiple communication signals coupled to output responses in receiving cells and (2) mathematical modeling to uncover input-output relationships and interactions between signals. Using human dendritic cell (DC)-T helper (Th) cell communication as a model, we measured 36 DC-derived signals and 17 Th cytokines broadly covering Th diversity in 428 observations. We developed a data-driven, computationally validated model capturing 56 already described and 290 potentially novel mechanisms of Th cell specification. By predicting context-dependent behaviors, we demonstrate a new function for IL-12p70 as an inducer of Th17 in an IL-1 signaling context. This work provides a unique resource to decipher the complex combinatorial rules governing DC-Th cell communication and guide their manipulation for vaccine design and immunotherapies.

TSLP-activated dendritic cells induce human T follicular helper cell differentiation through OX40-ligand.

T follicular helper cells (Tfh) are important regulators of humoral responses. Human Tfh polarization pathways have been thus far associated with Th1 and Th17 polarization pathways. How human Tfh cells differentiate in Th2-skewed environments is unknown. We show that thymic stromal lymphopoietin (TSLP)-activated dendritic cells (DCs) promote human Tfh differentiation from naive CD4 T cells. We identified a novel population, distinct from Th2 cells, expressing IL-21 and TNF, suggestive of inflammatory cells. TSLP-induced T cells expressed CXCR5, CXCL13, ICOS, PD1, BCL6, BTLA, and SAP, among other Tfh markers. Functionally, TSLP-DC-polarized T cells induced IgE secretion by memory B cells, and this depended on IL-4Rα. TSLP-activated DCs stimulated circulating memory Tfh cells to produce IL-21 and CXCL13. Mechanistically, TSLP-induced Tfh differentiation depended on OX40-ligand, but not on ICOS-ligand. Our results delineate a pathway of human Tfh differentiation in Th2 environments.

Human blood BDCA-1 dendritic cells differentiate into Langerhans-like cells with thymic stromal lymphopoietin and TGF-ß.

The ontogeny of human Langerhans cells (LCs) remains poorly characterized, in particular the nature of LC precursors and the factors that may drive LC differentiation. Here we report that thymic stromal lymphopoietin (TSLP), a keratinocyte-derived cytokine involved in epithelial inflammation, cooperates with transforming growth factor (TGF)-ß for the generation of LCs. We show that primary human blood BDCA-1(+), but not BDCA-3(+), dendritic cells (DCs) stimulated with TSLP and TGF-ß harbor a typical CD1a(+)Langerin(+) LC phenotype. Electron microscopy established the presence of Birbeck granules, an intracellular organelle specific to LCs. LC differentiation was not observed from tonsil BDCA-1(+) and BDCA-3(+) subsets. TSLP + TGF-ß LCs had a mature phenotype with high surface levels of CD80, CD86, and CD40. They induced a potent CD4(+) T-helper (Th) cell expansion and differentiation into Th2 cells with increased production of tumor necrosis factor-α and interleukin-6 compared with CD34-derived LCs. Our findings establish a novel LC differentiation pathway from BDCA-1(+) blood DCs with potential implications in epithelial inflammation. Therapeutic targeting of TSLP may interfere with tissue LC repopulation from circulating precursors.

Combinatorial flexibility of cytokine function during human T helper cell differentiation.

In an inflammatory microenvironment, multiple cytokines may act on the same target cell, creating the possibility for combinatorial interactions. How these may influence the system-level function of a given cytokine is unknown. Here we show that a single cytokine, interferon (IFN)-alpha, can generate multiple transcriptional signatures, including distinct functional modules of variable flexibility, when acting in four cytokine environments driving distinct T helper cell differentiation programs (Th0, Th1, Th2 and Th17). We provide experimental validation of a chemokine, cytokine and antiviral modules differentially induced by IFN-α in Th1, Th2 and Th17 environments. Functional impact is demonstrated for the antiviral response, with a lesser IFN-α-induced protection to HIV-1 and HIV-2 infection in a Th17 context. Our results reveal that a single cytokine can induce multiple transcriptional and functional programs in different microenvironments. This combinatorial flexibility creates a previously unrecognized diversity of responses, with potential impact on disease physiopathology and cytokine therapy.

Model checking to assess T-helper cell plasticity.

Computational modeling constitutes a crucial step toward the functional understanding of complex cellular networks. In particular, logical modeling has proven suitable for the dynamical analysis of large signaling and transcriptional regulatory networks. In this context, signaling input components are generally meant to convey external stimuli, or environmental cues. In response to such external signals, cells acquire specific gene expression patterns modeled in terms of attractors (e.g., stable states). The capacity for cells to alter or reprogram their differentiated states upon changes in environmental conditions is referred to as cell plasticity. In this article, we present a multivalued logical framework along with computational methods recently developed to efficiently analyze large models. We mainly focus on a symbolic model checking approach to investigate switches between attractors subsequent to changes of input conditions. As a case study, we consider the cellular network regulating the differentiation of T-helper (Th) cells, which orchestrate many physiological and pathological immune responses. To account for novel cellular subtypes, we present an extended version of a published model of Th cell differentiation. We then use symbolic model checking to analyze reachability properties between Th subtypes upon changes of environmental cues. This allows for the construction of a synthetic view of Th cell plasticity in terms of a graph connecting subtypes with arcs labeled by input conditions. Finally, we explore novel strategies enabling specific Th cell polarizing or reprograming events.