TNFR2 is required for RIP1-dependent cell death in human leukemia.

Despite major advances in the treatment of patients with acute lymphoblastic leukemia in the last decades, refractory and/or relapsed disease remains a clinical challenge, and relapsed leukemia patients have an exceedingly dismal prognosis. Dysregulation of apoptotic cell death pathways is a leading cause of drug resistance; thus, alternative cell death mechanisms, such as necroptosis, represent an appealing target for the treatment of high-risk malignancies. We and other investigators have shown that activation of receptor interacting protein kinase 1 (RIP1)-dependent apoptosis and necroptosis by second mitochondria derived activator of caspase mimetics (SMs) is an attractive antileukemic strategy not currently exploited by standard chemotherapy. However, the underlying molecular mechanisms that determine sensitivity to SMs have remained elusive. We show that tumor necrosis factor receptor 2 (TNFR2) messenger RNA expression correlates with sensitivity to SMs in primary human leukemia. Functional genetic experiments using clustered regularly interspaced short palindromic repeats/Cas9 demonstrate that TNFR2 and TNFR1, but not the ligand TNF-α, are essential for the response to SMs, revealing a ligand-independent interplay between TNFR1 and TNFR2 in the induction of RIP1-dependent cell death. Further potential TNFR ligands, such as lymphotoxins, were not required for SM sensitivity. Instead, TNFR2 promotes the formation of a RIP1/TNFR1-containing death signaling complex that induces RIP1 phosphorylation and RIP1-dependent apoptosis and necroptosis. Our data reveal an alternative paradigm for TNFR2 function in cell death signaling and provide a rationale to develop strategies for the identification of leukemias with vulnerability to RIP1-dependent cell death for tailored therapeutic interventions.

The Leukemogenic TCF3-HLF Complex Rewires Enhancers Driving Cellular Identity and Self-Renewal Conferring EP300 Vulnerability.

The chimeric transcription factor TCF3-HLF defines an incurable acute lymphoblastic leukemia subtype. Here we decipher the regulome of endogenous TCF3-HLF and dissect its essential transcriptional components and targets by functional genomics. We demonstrate that TCF3-HLF recruits HLF binding sites at hematopoietic stem cell/myeloid lineage associated (super-) enhancers to drive lineage identity and self-renewal. Among direct targets, hijacking an HLF binding site in a MYC enhancer cluster by TCF3-HLF activates a conserved MYC-driven transformation program crucial for leukemia propagation in vivo. TCF3-HLF pioneers the cooperation with ERG and recruits histone acetyltransferase p300 (EP300), conferring susceptibility to EP300 inhibition. Our study provides a framework for targeting driving transcriptional dependencies in this fatal leukemia.

Efficient apoptosis requires feedback amplification of upstream apoptotic signals by effector caspase-3 or -7.

Apoptosis is a complex multi-step process driven by caspase-dependent proteolytic cleavage cascades. Dysregulation of apoptosis promotes tumorigenesis and limits the efficacy of chemotherapy. To assess the complex interactions among caspases during apoptosis, we disrupted caspase-8, -9, -3, -7, or -6 and combinations thereof, using CRISPR-based genome editing in living human leukemia cells. While loss of apical initiator caspase-8 or -9 partially blocked extrinsic or intrinsic apoptosis, respectively, only combined loss of caspase-3 and -7 fully inhibited both apoptotic pathways, with no discernible effect of caspase-6 deficiency alone or in combination. Caspase-3/7 double knockout cells exhibited almost complete inhibition of caspase-8 or -9 activation. Furthermore, deletion of caspase-3 and -7 decreased mitochondrial depolarization and cytochrome c release upon apoptosis activation. Thus, activation of effector caspase-3 or -7 sets off explosive feedback amplification of upstream apoptotic events, which is a key feature of apoptotic signaling essential for efficient apoptotic cell death.

Optimized Protein-Protein Interaction Network Usage with Context Filtering.

Protein-protein interaction networks (PPIs) collect information on physical-and in some cases-functional interactions between proteins. Most PPIs are annotated with confidence scores, which reflect the probability that a reported interaction is a true interaction. These scores, however, do not allow users to isolate interactions relevant in a particular biological context. Here, we describe solutions for performing context filtering on PPIs to allow biological data interpretation and functional inference in two publicly available PPIs resources (HIPPIE and STRING) and in the proprietary pathway analysis tool and knowledge base Ingenuity Pathway Analysis.

Phosphoproteomic-based kinase profiling early in influenza virus infection identifies GRK2 as antiviral drug target.

Although annual influenza epidemics affect around 10% of the global population, current treatment options are limited and development of new antivirals is needed. Here, using quantitative phosphoproteomics, we reveal the unique phosphoproteome dynamics that occur in the host cell within minutes of influenza A virus (IAV) infection. We uncover cellular kinases required for the observed signaling pattern and find that inhibition of selected candidates, such as the G protein-coupled receptor kinase 2 (GRK2), leads to decreased IAV replication. As GRK2 has emerged as drug target in heart disease, we focus on its role in IAV infection and show that it is required for viral uncoating. Replication of seasonal and pandemic IAVs is severely decreased by specific GRK2 inhibitors in primary human airway cultures and in mice. Our study reveals the IAV-induced changes to the cellular phosphoproteome and identifies GRK2 as crucial node of the kinase network that enables IAV replication.

Context-based retrieval of functional modules in protein-protein interaction networks.

Various techniques have been developed for identifying the most probable interactants of a protein under a given biological context. In this article, we dissect the effects of the choice of the protein-protein interaction network (PPI) and the manipulation of PPI settings on the network neighborhood of the influenza A virus (IAV) network, as well as hits in genome-wide small interfering RNA screen results for IAV host factors. We investigate the potential of context filtering, which uses text mining evidence linked to PPI edges, as a complement to the edge confidence scores typically provided in PPIs for filtering, for obtaining more biologically relevant network neighborhoods. Here, we estimate the maximum performance of context filtering to isolate a Kyoto Encyclopedia of Genes and Genomes (KEGG) network Ki from a union of KEGG networks and its network neighborhood. The work gives insights on the use of human PPIs in network neighborhood approaches for functional inference.

Ex vivo drug response profiling detects recurrent sensitivity patterns in drug-resistant acute lymphoblastic leukemia.

Drug sensitivity and resistance testing on diagnostic leukemia samples should provide important functional information to guide actionable target and biomarker discovery. We provide proof of concept data by profiling 60 drugs on 68 acute lymphoblastic leukemia (ALL) samples mostly from resistant disease in cocultures of bone marrow stromal cells. Patient-derived xenografts retained the original pattern of mutations found in the matched patient material. Stromal coculture did not prevent leukemia cell cycle activity, but a specific sensitivity profile to cell cycle-related drugs identified samples with higher cell proliferation both in vitro and in vivo as leukemia xenografts. In patients with refractory relapses, individual patterns of marked drug resistance and exceptional responses to new agents of immediate clinical relevance were detected. The BCL2-inhibitor venetoclax was highly active below 10 nM in B-cell precursor ALL (BCP-ALL) subsets, including MLL-AF4 and TCF3-HLF ALL, and in some T-cell ALLs (T-ALLs), predicting in vivo activity as a single agent and in combination with dexamethasone and vincristine. Unexpected sensitivity to dasatinib with half maximal inhibitory concentration values below 20 nM was detected in 2 independent T-ALL cohorts, which correlated with similar cytotoxic activity of the SRC inhibitor KX2-391 and inhibition of SRC phosphorylation. A patient with refractory T-ALL was treated with dasatinib on the basis of drug profiling information and achieved a 5-month remission. Thus, drug profiling captures disease-relevant features and unexpected sensitivity to relevant drugs, which warrants further exploration of this functional assay in the context of clinical trials to develop drug repurposing strategies for patients with urgent medical needs.

Type II enteropathy-associated T-cell lymphoma features a unique genomic profile with highly recurrent SETD2 alterations.

Enteropathy-associated T-cell lymphoma (EATL), a rare and aggressive intestinal malignancy of intraepithelial T lymphocytes, comprises two disease variants (EATL-I and EATL-II) differing in clinical characteristics and pathological features. Here we report findings derived from whole-exome sequencing of 15 EATL-II tumour-normal tissue pairs. The tumour suppressor gene SETD2 encoding a non-redundant H3K36-specific trimethyltransferase is altered in 14/15 cases (93%), mainly by loss-of-function mutations and/or loss of the corresponding locus (3p21.31). These alterations consistently correlate with defective H3K36 trimethylation. The JAK/STAT pathway comprises recurrent STAT5B (60%), JAK3 (46%) and SH2B3 (20%) mutations, including a STAT5B V712E activating variant. In addition, frequent mutations in TP53, BRAF and KRAS are observed. Conversely, in EATL-I, no SETD2, STAT5B or JAK3 mutations are found, and H3K36 trimethylation is preserved. This study describes SETD2 inactivation as EATL-II molecular hallmark, supports EATL-I and -II being two distinct entities, and defines potential new targets for therapeutic intervention.

Activating mutations in genes related to TCR signaling in angioimmunoblastic and other follicular helper T-cell-derived lymphomas.

Angioimmunoblastic T-cell lymphoma (AITL) and other lymphomas derived from follicular T-helper cells (TFH) represent a large proportion of peripheral T-cell lymphomas (PTCLs) with poorly understood pathogenesis and unfavorable treatment results. We investigated a series of 85 patients with AITL (n = 72) or other TFH-derived PTCL (n = 13) by targeted deep sequencing of a gene panel enriched in T-cell receptor (TCR) signaling elements. RHOA mutations were identified in 51 of 85 cases (60%) consisting of the highly recurrent dominant negative G17V variant in most cases and a novel K18N in 3 cases, the latter showing activating properties in in vitro assays. Moreover, half of the patients carried virtually mutually exclusive mutations in other TCR-related genes, most frequently in PLCG1 (14.1%), CD28 (9.4%, exclusively in AITL), PI3K elements (7%), CTNNB1 (6%), and GTF2I (6%). Using in vitro assays in transfected cells, we demonstrated that 9 of 10 PLCG1 and 3 of 3 CARD11 variants induced MALT1 protease activity and increased transcription from NFAT or NF-κB response element reporters, respectively. Collectively, the vast majority of variants in TCR-related genes could be classified as gain-of-function. Accordingly, the samples with mutations in TCR-related genes other than RHOA had transcriptomic profiles enriched in signatures reflecting higher T-cell activation. Although no correlation with presenting clinical features nor significant impact on survival was observed, the presence of TCR-related mutations correlated with early disease progression. Thus, targeting of TCR-related events may hold promise for the treatment of TFH-derived lymphomas.

Genomics and drug profiling of fatal TCF3-HLF-positive acute lymphoblastic leukemia identifies recurrent mutation patterns and therapeutic options.

TCF3-HLF-positive acute lymphoblastic leukemia (ALL) is currently incurable. Using an integrated approach, we uncovered distinct mutation, gene expression and drug response profiles in TCF3-HLF-positive and treatment-responsive TCF3-PBX1-positive ALL. We identified recurrent intragenic deletions of PAX5 or VPREB1 in constellation with the fusion of TCF3 and HLF. Moreover somatic mutations in the non-translocated allele of TCF3 and a reduction of PAX5 gene dosage in TCF3-HLF ALL suggest cooperation within a restricted genetic context. The enrichment for stem cell and myeloid features in the TCF3-HLF signature may reflect reprogramming by TCF3-HLF of a lymphoid-committed cell of origin toward a hybrid, drug-resistant hematopoietic state. Drug response profiling of matched patient-derived xenografts revealed a distinct profile for TCF3-HLF ALL with resistance to conventional chemotherapeutics but sensitivity to glucocorticoids, anthracyclines and agents in clinical development. Striking on-target sensitivity was achieved with the BCL2-specific inhibitor venetoclax (ABT-199). This integrated approach thus provides alternative treatment options for this deadly disease.

Immunohistochemistry as a valuable tool to assess CD30 expression in peripheral T-cell lymphomas: high correlation with mRNA levels.

The extended use of brentuximab-vedotin was reported for CD30(+) nonanaplastic peripheral T-cell lymphomas (PTCLs) with promising efficacy. CD30 status assessment is thus a critical factor for therapeutic decision, but the reliability of immunohistochemistry (IHC) in evaluating its expression remains to be defined. This prompted us to investigate the correlation between semiquantitative CD30 protein assessment by IHC and messenger RNA (mRNA) assessment by microarrays in a cohort of 376 noncutaneous PTCLs representative of the main entities. By IHC, CD30 expression was heterogeneous across and within entities and significantly associated with large tumor cell size. In addition to 100% anaplastic large-cell lymphomas, 57% of other PTCL entities were CD30-positive at a 5% threshold. CD30 protein expression was highly correlated to mRNA levels. mRNA levels were bimodal, separating high from low CD30-expressing PTCL cases. We conclude that IHC is a valuable tool in clinical practice to assess CD30 expression in PTCLs.

Cell type determines the light-induced endosomal escape kinetics of multifunctional mesoporous silica nanoparticles.

We investigated uptake and individual endosome lysis events in fibroblast, normal, and carcinoma cell lines using a colloidal mesoporous silica (CMS) nanoparticle (NP)-based reporter system with a covalently attached photosensitizer. Endosome lysis was induced through the activation of protoporphyrin IX (PpIX). Surprisingly, this release-on-demand system resulted in more broadly distributed lysis times than expected, particularly for Renca, a renal carcinoma cell line. An analysis of the NP load per endosome, endosome size, and uptake characteristics indicate that Renca cells not only take up a lower amount of NPs in comparison with the fibroblast cells but also have larger endosomes and a lower NP load per endosome. We then created a stochastic model detailing steps downstream of uptake to understand how much factors that cannot be directly measured, such as variations in the PpIX load per NP, affect the lysis time distributions. Model results indicate that the distributions are primarily determined by the endosome properties, rather than variations across NPs.

How many trimers? Modeling influenza virus fusion yields a minimum aggregate size of six trimers, three of which are fusogenic.

Conflicting reports in leading journals have indicated the minimum number of influenza hemagglutinin (HA) trimers required for fusion to be between one and eight. Interestingly, the data in these reports are either almost identical, or can be transformed to be directly comparable. Different statistical or phenomenological models, however, were used to analyze these data, resulting in the varied interpretations. In an attempt to resolve this contradiction, we use PABM, a brane calculus we recently introduced, enabling an algorithmic systems biology approach that allows the problem to be modeled in a manner following a biological logic. Since a scalable PABM executor is still under development, we sufficiently simplified the fusion model and analyzed it using the model checker, PRISM. We validated the model against older HA-expressing cell-to-cell fusion data using the same parameters with the exception of three, namely HA and sialic acid (SA) surface densities and the aggregation rate, which were expected to be different as a result of the difference in the experimental setup. Results are consistent with the interpretation that a minimum aggregate size of six HA trimers, of which three undergo a conformational change to become fusogenic, is required for fusion. Of these three, two are free, while one is bound. Finally, we determined the effects of varying the SA surface density and showed that only a limited range of densities permit fusion. Our results demonstrate the potential of modeling in providing more precise interpretations of data.