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Abstract Background With the current technological advances in high-throughput biology, the necessity to develop tools that help to analyse the massive amount of data being generated is evident. A powerful method of inspecting large-scale data sets is gene set enrichment analysis (GSEA) and investigation of protein structural features can guide determining the function of individual genes. However, a convenient tool that combines these two features to aid in high-throughput data analysis has not been developed yet. In order to fill this niche, we developed the user-friendly, web-based application, PhenoFam. Results PhenoFam performs gene set enrichment analysis by employing structural and functional information on families of protein domains as annotation terms. Our tool is designed to analyse complete sets of results from quantitative high-throughput studies (gene expression microarrays, functional RNAi screens, etc.) without prior pre-filtering or hits-selection steps. PhenoFam utilizes Ensembl databases to link a list of user-provided identifiers with protein features from the InterPro database, and assesses whether results associated with individual domains differ significantly from the overall population. To demonstrate the utility of PhenoFam we analysed a genome-wide RNA interference screen and discovered a novel function of plexins containing the cytoplasmic RasGAP domain. Furthermore, a PhenoFam analysis of breast cancer gene expression profiles revealed a link between breast carcinoma and altered expression of PX domain containing proteins. Conclusions PhenoFam provides a user-friendly, easily accessible web interface to perform GSEA based on high-throughput data sets and structural-functional protein information, and therefore aids in functional annotation of genes.

Burkitt lymphoma (BL) is an aggressive lymphoma type that is currently treated by intensive chemoimmunotherapy. Despite the favorable clinical outcome for most patients with BL, chemotherapy-related toxicity and disease relapse remain major clinical challenges, emphasizing the need for innovative therapies. Using genome-scale CRISPR-Cas9 screens, we identified B-cell receptor (BCR) signaling, specific transcriptional regulators, and one-carbon metabolism as vulnerabilities in BL. We focused on serine hydroxymethyltransferase 2 (SHMT2), a key enzyme in one-carbon metabolism. Inhibition of SHMT2 by either knockdown or pharmacological compounds induced anti-BL effects in vitro and in vivo. Mechanistically, SHMT2 inhibition led to a significant reduction of intracellular glycine and formate levels, which inhibited the mTOR pathway and thereby triggered autophagic degradation of the oncogenic transcription factor TCF3. Consequently, this led to a collapse of tonic BCR signaling, which is controlled by TCF3 and is essential for BL cell survival. In terms of clinical translation, we also identified drugs such as methotrexate that synergized with SHMT inhibitors. Overall, our study has uncovered the dependency landscape in BL, identified and validated SHMT2 as a drug target, and revealed a mechanistic link between SHMT2 and the transcriptional master regulator TCF3, opening up new perspectives for innovative therapies., (© 2022 by The American Society of Hematology.)

We successfully repurpose the DNA repair protein methylguanine methyltransferase (MGMT) as an inducible degron for protein fusions. MGMT is a suicide protein that removes alkyl groups from the O 6 position of guanine (O 6 G) and is thereafter quickly degraded by the ubiquitin proteasome pathway (UPP). Starting with MGMT pseudosubstrates (benzylguanine and lomeguatrib), we first demonstrate that these lead to potent MGMT depletion while affecting little else in the proteome. We then show that fusion proteins of MGMT undergo rapid UPP-dependent degradation in response to pseudosubstrates. Mechanistic studies confirm the involvement of the UPP, while revealing that at least two E3 ligase classes can degrade MGMT depending on cell-line and expression type (native or ectopic). We also demonstrate the technique's versatility with two clinically relevant examples: degradation of KRAS G12C and a chimeric antigen receptor.

The use of Bluetooth Low Energy (BLE) in the Internet-of-Things (IoT) applications has become widespread and popular. This has resulted in the increased number of deployed BLE devices. To ensure energy efficiency, applications use connectionless communication where nodes broadcast information using advertisement messages. As the BLE devices compete for access to spectrum, collisions are inevitable and methods that improve device coexistence are required. This paper proposes a connectionless communication scheme for BLE that improves communication efficiency in IoT applications where a large number of BLE nodes operate in the same area and communicate simultaneously to a central server. The proposed scheme is based on an active scanning mode and is compared with a typical application where passive scanning mode is used. The evaluation is based on numerical simulations and real-life evaluation of a network containing 150 devices. The presented scheme significantly reduces the number of messages transmitted by each node and decreases packet loss ratio. It also improves the energy efficiency and preserves the battery of BLE nodes as they transmit fewer radio messages and effectively spent less time actively communicating. The proposed connectionless BLE communication scheme can be applied to a large variety of IoT applications improving their performance and coexistence with other devices operating in the 2.4 GHz band. Additionally, the implementation complexity and costs of the proposed communication scheme are negligible.

Myxoid liposarcomas (MLS), malignant tumors of adipocyte origin, are driven by the FUS-DDIT3 fusion gene encoding an aberrant transcription factor. The mechanisms whereby FUS-DDIT3 mediates sarcomagenesis are incompletely understood, and strategies to selectively target MLS cells remain elusive. Here we show, using an unbiased functional genomic approach, that FUS-DDIT3-expressing mesenchymal stem cells and MLS cell lines are dependent on YAP1, a transcriptional co-activator and central effector of the Hippo pathway involved in tissue growth and tumorigenesis, and that increased YAP1 activity is a hallmark of human MLS Mechanistically, FUS-DDIT3 promotes YAP1 expression, nuclear localization, and transcriptional activity and physically associates with YAP1 in the nucleus of MLS cells. Pharmacologic inhibition of YAP1 activity impairs the growth of MLS cells in vitro and in vivo These findings identify overactive YAP1 signaling as unifying feature of MLS development that could represent a novel target for therapeutic intervention., (© 2019 The Authors. Published under the terms of the CC BY 4.0 license.)

Downregulation of CD20, a molecular target for monoclonal antibodies (mAbs), is a clinical problem leading to decreased efficacy of anti-CD20-based therapeutic regimens. The epigenetic modulation of CD20 coding gene ( MS4A1 ) has been proposed as a mechanism for the reduced therapeutic efficacy of anti-CD20 antibodies and confirmed with nonselective histone deacetylase inhibitors (HDACis). Because the use of pan-HDACis is associated with substantial adverse effects, the identification of particular HDAC isoforms involved in CD20 regulation seems to be of paramount importance. In this study, we demonstrate for the first time the role of HDAC6 in the regulation of CD20 levels. We show that inhibition of HDAC6 activity significantly increases CD20 levels in established B-cell tumor cell lines and primary malignant cells. Using pharmacologic and genetic approaches, we confirm that HDAC6 inhibition augments in vitro efficacy of anti-CD20 mAbs and improves survival of mice treated with rituximab. Mechanistically, we demonstrate that HDAC6 influences synthesis of CD20 protein independently of the regulation of MS4A1 transcription. We further demonstrate that translation of CD20 mRNA is significantly enhanced after HDAC6 inhibition, as shown by the increase of CD20 mRNA within the polysomal fraction, indicating a new role of HDAC6 in the posttranscriptional mechanism of CD20 regulation. Collectively, our findings suggest HDAC6 inhibition is a rational therapeutic strategy to be implemented in combination therapies with anti-CD20 monoclonal antibodies and open up novel avenues for the clinical use of HDAC6 inhibitors., (© 2017 by The American Society of Hematology.)

Burkitt's lymphoma (BL) is a highly proliferative B-cell neoplasm and is treated with intensive chemotherapy that, because of its toxicity, is often not suitable for the elderly or for patients with endemic BL in developing countries. BL cell survival relies on signals transduced by B-cell antigen receptors (BCRs). However, tonic as well as activated BCR signaling networks and their relevance for targeted therapies in BL remain elusive. We have systematically characterized and compared tonic and activated BCR signaling in BL by quantitative phosphoproteomics to identify novel BCR effectors and potential drug targets. We identified and quantified ∼16,000 phospho-sites in BL cells. Among these sites, 909 were related to tonic BCR signaling, whereas 984 phospho-sites were regulated upon BCR engagement. The majority of the identified BCR signaling effectors have not been described in the context of B cells or lymphomas yet. Most of these newly identified BCR effectors are predicted to be involved in the regulation of kinases, transcription, and cytoskeleton dynamics. Although tonic and activated BCR signaling shared a considerable number of effector proteins, we identified distinct phosphorylation events in tonic BCR signaling. We investigated the functional relevance of some newly identified BCR effectors and show that ACTN4 and ARFGEF2, which have been described as regulators of membrane-trafficking and cytoskeleton-related processes, respectively, are crucial for BL cell survival. Thus, this study provides a comprehensive dataset for tonic and activated BCR signaling and identifies effector proteins that may be relevant for BL cell survival and thus may help to develop new BL treatments.

Clinical trials with SRC family kinases (SFKs) inhibitors used alone or in a combination with anti-CD20 monoclonal antibodies (mAbs) are currently underway in the treatment of B-cell tumors. However, molecular interactions between these therapeutics have not been studied so far. A transcriptional profiling of tumor cells incubated with SFKs inhibitors revealed strong downregulation of MS4A1 gene encoding CD20 antigen. In a panel of primary and established B-cell tumors we observed that SFKs inhibitors strongly affect CD20 expression at the transcriptional level, leading to inhibition of anti-CD20 mAbs binding and increased resistance of tumor cells to complement-dependent cytotoxicity. Activation of the AKT signaling pathway significantly protected cells from dasatinib-triggered CD20 downregulation. Additionally, SFKs inhibitors suppressed antibody-dependent cell-mediated cytotoxicity by direct inhibition of natural killer cells. Abrogation of antitumor activity of rituximab was also observed in vivo in a mouse model. Noteworthy, the effects of SFKs inhibitors on NK cell function are largely reversible. The results of our studies indicate that development of optimal combinations of novel treatment modalities with anti-CD20 mAbs should be preceded by detailed preclinical evaluation of their effects on target cells.

Affinity purification of protein complexes and identification of co-purified proteins by mass spectrometry is a powerful method to discover novel protein-protein interactions. Application of this method to the study of biological systems often requires the ability to process a large number of samples. Hence, there is great need to generate proteomic workflows compatible with large-scale studies. The major goal of this protocol is to present a fast, reliable, and scalable method to characterize protein complexes by mass spectrometry to overcome the limitations of conventional geLC-MS/MS or MudPIT protocols. This method was successfully employed for the discovery and characterization of novel protein complexes in cultured yeast, mammalian cells, and mice.

TP53 (tumour protein 53) is one of the most frequently mutated genes in human cancer and its role during cellular transformation has been studied extensively. However, the homeostatic functions of p53 are less well understood. Here, we explore the molecular dependency network of TP53 through an RNAi-mediated synthetic interaction screen employing two HCT116 isogenic cell lines and a genome-scale endoribonuclease-prepared short interfering RNA library. We identify a variety of TP53 synthetic interactions unmasking the complex connections of p53 to cellular physiology and growth control. Molecular dissection of the TP53 synthetic interaction with UNRIP indicates an enhanced dependency of TP53-negative cells on small nucleolar ribonucleoprotein (snoRNP) assembly. This dependency is mediated by the snoRNP chaperone gene NOLC1 (also known as NOPP140), which we identify as a physiological p53 target gene. This unanticipated function of TP53 in snoRNP assembly highlights the potential of RNAi-mediated synthetic interaction screens to dissect molecular pathways of tumour suppressor genes.

Background: With the current technological advances in high-throughput biology, the necessity to develop tools that help to analyse the massive amount of data being generated is evident. A powerful method of inspecting large-scale data sets is gene set enrichment analysis (GSEA) and investigation of protein structural features can guide determining the function of individual genes. However, a convenient tool that combines these two features to aid in high-throughput data analysis has not been developed yet. In order to fill this niche, we developed the user-friendly, web-based application, PhenoFam., Results: PhenoFam performs gene set enrichment analysis by employing structural and functional information on families of protein domains as annotation terms. Our tool is designed to analyse complete sets of results from quantitative high-throughput studies (gene expression microarrays, functional RNAi screens, etc.) without prior pre-filtering or hits-selection steps. PhenoFam utilizes Ensembl databases to link a list of user-provided identifiers with protein features from the InterPro database, and assesses whether results associated with individual domains differ significantly from the overall population. To demonstrate the utility of PhenoFam we analysed a genome-wide RNA interference screen and discovered a novel function of plexins containing the cytoplasmic RasGAP domain. Furthermore, a PhenoFam analysis of breast cancer gene expression profiles revealed a link between breast carcinoma and altered expression of PX domain containing proteins., Conclusions: PhenoFam provides a user-friendly, easily accessible web interface to perform GSEA based on high-throughput data sets and structural-functional protein information, and therefore aids in functional annotation of genes.

Proliferation of mammalian cells requires the coordinated function of many proteins to accurately divide a cell into two daughter cells. Several RNAi screens have identified previously uncharacterised genes that are implicated in mammalian cell division. The molecular function for these genes needs to be investigated to place them into pathways. Phenotypic profiling is a useful method to assign putative functions to uncharacterised genes. Here, we show that the analysis of protein localisation is useful to refine a phenotypic profile. We show the utility of this approach by defining a function of the previously uncharacterised gene C13orf3 during cell division. C13orf3 localises to centrosomes, the mitotic spindle, kinetochores, spindle midzone, and the cleavage furrow during cell division and is specifically phosphorylated during mitosis. Furthermore, C13orf3 is required for centrosome integrity and anaphase onset. Depletion by RNAi leads to mitotic arrest in metaphase with an activation of the spindle assembly checkpoint and loss of sister chromatid cohesion. Proteomic analyses identify C13orf3 (Ska3) as a new component of the Ska complex and show a direct interaction with a regulatory subunit of the protein phosphatase PP2A. All together, these data identify C13orf3 as an important factor for metaphase to anaphase progression and highlight the potential of combined RNAi screening and protein localisation analyses.

Cell division is fundamental for all organisms. Here we report a genome-scale RNA-mediated interference screen in HeLa cells designed to identify human genes that are important for cell division. We have used a library of endoribonuclease-prepared short interfering RNAs for gene silencing and have used DNA content analysis to identify genes that induced cell cycle arrest or altered ploidy on silencing. Validation and secondary assays were performed to generate a nine-parameter loss-of-function phenoprint for each of the genes. These phenotypic signatures allowed the assignment of genes to specific functional classes by combining hierarchical clustering, cross-species analysis and proteomic data mining. We highlight the richness of our dataset by ascribing novel functions to genes in mitosis and cytokinesis. In particular, we identify two evolutionarily conserved transcriptional regulatory networks that govern cytokinesis. Our work provides an experimental framework from which the systematic analysis of novel genes necessary for cell division in human cells can begin.

RNA interference (RNAi) has become an important technique for loss-of-gene-function studies in mammalian cells. To achieve reliable results in an RNAi experiment, efficient and specific silencing triggers are required. Here we present genome-wide data sets for the production of endoribonuclease-prepared short interfering RNAs (esiRNAs) for human, mouse and rat. We used an algorithm to predict the optimal region for esiRNA synthesis for every protein-coding gene of these three species. We created a database, RiDDLE, for retrieval of target sequences and primer information. To test this in silico resource experimentally, we generated 16,242 esiRNAs that can be used for RNAi screening in human cells. Comparative analyses with chemically synthesized siRNAs demonstrated a high silencing efficacy of esiRNAs and a 12-fold reduction of downregulated off-target transcripts as detected by microarray analysis. Hence, the presented esiRNA libraries offer an efficient, cost-effective and specific alternative to presently available mammalian RNAi resources.

Large-scale RNA interference (RNAi) screens in mammalian cells have mainly used synthetic small interfering RNA (siRNA) or short hairpin RNA (shRNA) libraries. The RNAi triggers for both of these approaches were designed with algorithm-based predictions to identify single sequences for mRNA knockdown. Alternatives to these approaches have recently been developed using enzymatic methods. Here we describe the concepts of enzymatically prepared shRNA and siRNA libraries, and discuss their strengths and limitations.