Jörg Menche

A combinatorial screen of the CLOUD uncovers a synergy targeting the androgen receptor

Approved drugs are invaluable tools to study biochemical pathways, and further characterization of these compounds may lead to repurposing of single drugs or combinations. Here we describe a collection of 308 small molecules representing the diversity of structures and molecular targets of all FDA-approved chemical entities. The CeMM Library of Unique Drugs (CLOUD) covers prodrugs and active forms at pharmacologically relevant concentrations and is ideally suited for combinatorial studies. We screened pairwise combinations of CLOUD drugs for impairment of cancer cell viability and discovered a synergistic interaction between flutamide and phenprocoumon (PPC). The combination of these drugs modulates the stability of the androgen receptor (AR) and resensitizes AR-mutant prostate cancer cells to flutamide. Mechanistically, we show that the AR is a substrate for γ-carboxylation, a post-translational modification inhibited by PPC. Collectively, our data suggest that PPC could be repurposed to tackle resistance to antiandrogens in prostate cancer patients.

The immune system as a social network

The immune system employs a multitude of molecules, cells and organs that act together throughout the entire body to guard human health. Much like in a social network, immune cells can exert full functionality only through effective collaboration and communication.

Parallel genome-wide screens identify synthetic viable interactions between the BLM helicase complex and Fanconi anemia

Maintenance of genome integrity via repair of DNA damage is a key biological process required to suppress diseases, including Fanconi anemia (FA). We generated loss-of-function human haploid cells for FA complementation group C (FANCC), a gene encoding a component of the FA core complex, and used genome-wide CRISPR libraries as well as insertional mutagenesis to identify synthetic viable (genetic suppressor) interactions for FA. Here we show that loss of the BLM helicase complex suppresses FANCC phenotypes and we confirm this interaction in cells deficient for FA complementation group I and D2 (FANCI and FANCD2) that function as part of the FA I-D2 complex, indicating that this interaction is not limited to the FA core complex, hence demonstrating that systematic genome-wide screening approaches can be used to reveal genetic viable interactions for DNA repair defects.Fanconi anemia is a complex disease affecting multiple DNA repair proteins that resolve DNA crosslinks which can block vital processes. Here the authors use parallel genome-wide screens that identify the BLM helicase complex as a suppressor of Fanconi anemia phenotypes.

Characterization of host proteins interacting with the lymphocytic choriomeningitis virus L protein

RNA-dependent RNA polymerases (RdRps) play a key role in the life cycle of RNA viruses and impact their immunobiology. The arenavirus lymphocytic choriomeningitis virus (LCMV) strain Clone 13 provides a benchmark model for studying chronic infection. A major genetic determinant for its ability to persist maps to a single amino acid exchange in the viral L protein, which exhibits RdRp activity, yet its functional consequences remain elusive. To unravel the L protein interactions with the host proteome, we engineered infectious L protein-tagged LCMV virions by reverse genetics. A subsequent mass-spectrometric analysis of L protein pulldowns from infected human cells revealed a comprehensive network of interacting host proteins. The obtained LCMV L protein interactome was bioinformatically integrated with known host protein interactors of RdRps from other RNA viruses, emphasizing interconnected modules of human proteins. Functional characterization of selected interactors highlighted proviral (DDX3X) as well as antiviral (NKRF, TRIM21) host factors. To corroborate these findings, we infected Trim21-/- mice with LCMV and found impaired virus control in chronic infection. These results provide insights into the complex interactions of the arenavirus LCMV and other viral RdRps with the host proteome and contribute to a better molecular understanding of how chronic viruses interact with their host.

Network medicine: a new paradigm for cardiovascular disease research and beyond

In June 2017, the European Society of Cardiology invited around 70 young scientists, mostly at the early stage of their PhD studies, to a 5-day summer school at the Côte d’Azur in France. Numerous presentations by around 30 invited worldwide experts, poster sessions and discussion rounds covered a broad spectrum of cardiovascular disease research and clinical practice: From basic research on molecular disease mechanisms to drug target development, from novel imaging approaches to patient stratification, to name but a few of the many topics. The school also addressed important practical aspects of a successful PhD and career thereafter, such as paper writing or how collaborations between academia and the pharma industry work. Perhaps most importantly, the collegial atmosphere of the school enabled and encouraged numerous informal interactions between students and faculty. The diversity in topics and speakers reflects the daunting diversity of challenges that cardiovascular disease research faces today: Cardiovascular diseases are the most common cause of death worldwide, with numbers rising, rather than falling. The Medical Subject Headings (MeSH) thesaurus contains over 600 distinct cardiovascular diseases, covering the full spectrum of disease etiology, from rare Mendelian diseases with precise and well known genetic cause to common, largely lifestyle-induced diseases and everything inbetween. The database DisGeNet currently lists over 1000 genes involved in the patho-biology of one or several cardiovascular diseases, collectively representing almost all known biological pathways. Nevertheless, for most cardiovascular diseases the detailed underlying molecular mechanisms remain only poorly understood and novel, more effective and more targeted therapies are sorely needed. In recent years, sophisticated technologies have emerged that allow us to investigate the molecular mechanisms of disease at an unprecedented level of detail. Both healthy and disease states can now be quantified at molecular resolution through diverse omics technologies, such as genome sequencing, transcriptome mapping, proteomics, metabolomics, etc. At the same time, it is becoming increasingly clear that a deeper understanding of these (patho-) physiological states requires not only a detailed characterization of its individual components (genes, proteins, metabolites, etc.), but also of their interactions. Indeed, biomolecules do not act in isolation, but are part of an intricate and tightly coordinated machinery of complex interactions, such as protein-protein, gene regulatory or signalling interactions. The exquisitely complex and highly dynamic nature of these networks poses a fundamental challenge to the traditional reductionist approach of biomedical research: Most likely, many disease phenomena cannot be fully understood by simple mechanistic models and also not be reversed by a single therapeutic target. To unravel the emergent properties resulting from the complex interplay of many individual components, a more holistic, systems-oriented perspective is needed. The ambition of the young field of ‘network medicine’ is to provide such a perspective. Over the last decade, tools and concepts from network theory have successfully been applied to a broad range of diseases, from rare Mendelian disorders, cancer, or metabolic diseases, to J. M. received his basic training in theoretical and computational physics in Germany (Leipzig, Berlin) and Brazil (Recife). During his PhD at the Max-Planck-Institute for Colloids and Interfaces in Potsdam (Germany) he specialized in network science and afterwards went to work with one of the world’s leading experts in this field, Albert-L aszl o Barab asi at Northeastern University in Boston (USA). Collaborating closely with Joseph Loscalzo from Harvard Medical School and Marc Vidal from Dana Farber Cancer Institute, he tried to lay out the basic theoretical framework for how molecular networks can be used as maps to study human disease. He is now a principal investigator at the CeMM Research Center for Molecular Medicine of the Austrian Academy of Sciences in Vienna (Austria). His current research interests include network approaches to rare diseases and drug interactions.

A diseasome cluster-based drug repurposing of soluble guanylate cyclase activators from smooth muscle relaxation to direct neuroprotection

Network medicine utilizes common genetic origins, markers and co-morbidities to uncover mechanistic links between diseases. These links can be summarized in the diseasome, a comprehensive network of disease–disease relationships and clusters. The diseasome has been influential during the past decade, although most of its links are not followed up experimentally. Here, we investigate a high prevalence unmet medical need cluster of disease phenotypes linked to cyclic GMP. Hitherto, the central cGMP-forming enzyme, soluble guanylate cyclase (sGC), has been targeted pharmacologically exclusively for smooth muscle modulation in cardiology and pulmonology. Here, we examine the disease associations of sGC in a non-hypothesis based manner in order to identify possibly previously unrecognized clinical indications. Surprisingly, we find that sGC, is closest linked to neurological disorders, an application that has so far not been explored clinically. Indeed, when investigating the neurological indication of this cluster with the highest unmet medical need, ischemic stroke, pre-clinically we find that sGC activity is virtually absent post-stroke. Conversely, a heme-free form of sGC, apo-sGC, was now the predominant isoform suggesting it may be a mechanism-based target in stroke. Indeed, this repurposing hypothesis could be validated experimentally in vivo as specific activators of apo-sGC were directly neuroprotective, reduced infarct size and increased survival. Thus, common mechanism clusters of the diseasome allow direct drug repurposing across previously unrelated disease phenotypes redefining them in a mechanism-based manner. Specifically, our example of repurposing apo-sGC activators for ischemic stroke should be urgently validated clinically as a possible first-in-class neuroprotective therapy.Systems based pharmacology: drug repurposing by diseasomeSystems medicine utilizes common genetic origins and co-morbidities to uncover mechanistic links between diseases, which are summarized in the diseasome. Shared pathomechanisms may also allow for drug repurposing within these disease clusters. Here, Schmidt and co-workers show indeed that, based on this principle, a cardio-pulmonary drug can be surprisingly repurposed for a previously not recognised application as a direct neuroprotectant. They find that the cyclic GMP forming soluble guanylate cyclase becomes dysfunctional upon stroke but regains catalytic activity in the presence of specific activator compounds. This new mechanism-based therapy should be urgently validated clinically as a possible first-in-class treatment in stroke.

Mapping the human kinome in response to DNA damage

We provide a catalog for the effects of the human kinome on cell survival in response to DNA damaging agents, selected to cover all major DNA repair pathways. By treating 313 kinase-deficient cell lines with ten diverse DNA damaging agents, including seven commonly used chemotherapeutics, we were able to identify kinase specific vulnerabilities and resistances. In order to identify novel synthetic lethal interactions, we investigate the cellular response to carmustine for 25 cell lines, by establishing a phenotypic FACS assay designed to mechanistically investigate and validate gene-drug interactions. We show apoptosis, cell cycle, DNA damage and proliferation after alkylation or crosslink-induced damage for selected cell lines and rescue the cellular sensitivity of DYRK4, EPHB6, MARK3, PNCK as a proof of principle for our study. Our data suggest that some cancers with inactivated DYRK4, EPHB6, MARK3 or PNCK gene could be particularly vulnerable to treatment by alkylating chemotherapeutic agents carmustine or temozolomide.

Targeting comorbid diseases via network endopharmacology

The traditional drug discovery paradigm has shaped around the idea of “one target, one disease”. Recently, it has become clear that not only it is hard to achieve single target specificity but also it is often more desirable to tinker the complex cellular network by targeting multiple proteins, causing a paradigm shift towards polypharmacology (multiple targets, one disease). Given the lack of clear-cut boundaries across disease (endo)phenotypes and genetic heterogeneity across patients, a natural extension to the current polypharmacology paradigm is targeting common biological pathways involved in diseases, giving rise to “endopharmacology” (multiple targets, multiple diseases). In this study, leveraging powerful network medicine tools, we describe a recipe for first, identifying common pathways pertaining to diseases and then, prioritizing drugs that target these pathways towards endopharmacology. We present proximal pathway enrichment analysis (PxEA) that uses the topology information of the network of interactions between disease genes, pathway genes, drug targets and other proteins to rank drugs for their interactome-based proximity to pathways shared across multiple diseases, providing unprecedented drug repurposing opportunities. As a proof of principle, we focus on nine autoimmune disorders and using PxEA, we show that many drugs indicated for these conditions are not necessarily specific to the condition of interest, but rather target the common biological pathways across these diseases. Finally, we provide the high scoring drug repurposing candidates that can target common mechanisms involved in type 2 diabetes and Alzheimer’s disease, two phenotypes that have recently gained attention due to the increased comorbidity among patients.

Map of synthetic rescue interactions for the Fanconi anemia DNA repair pathway identifies USP48

Defects in DNA repair can cause various genetic diseases with severe pathological phenotypes. Fanconi anemia (FA) is a rare disease characterized by bone marrow failure, developmental abnormalities, and increased cancer risk that is caused by defective repair of DNA interstrand crosslinks (ICLs). Here, we identify the deubiquitylating enzyme USP48 as synthetic viable for FA-gene deficiencies by performing genome-wide loss-of-function screens across a panel of human haploid isogenic FA-defective cells (FANCA, FANCC, FANCG, FANCI, FANCD2). Thus, as compared to FA-defective cells alone, FA-deficient cells additionally lacking USP48 are less sensitive to genotoxic stress induced by ICL agents and display enhanced, BRCA1-dependent, clearance of DNA damage. Consequently, USP48 inactivation reduces chromosomal instability of FA-defective cells. Our results highlight a role for USP48 in controlling DNA repair and suggest it as a potential target that could be therapeutically exploited for FA.Fanconi anemia is a rare disease caused by defective DNA interstrand crosslink repair. Here the authors observe that USP48 deficiencies reduce chromosomal instability in FA-defective cells, suggesting it might be a potential therapeutic target.

Non-classical monocytes as mediators of tissue destruction in arthritis

Objectives Bone destruction in rheumatoid arthritis is mediated by osteoclasts (OC), which are derived from precursor cells of the myeloid lineage. The role of the two monocyte subsets, classical monocytes (expressing CD115, Ly6C and CCR2) and non-classical monocytes (which are CD115 positive, but low in Ly6C and CCR2), in serving as precursors for OC in arthritis is still elusive. Methods We investigated CCR2−/− mice, which lack circulating classical monocytes, crossed into hTNFtg mice for the extent of joint damage. We analysed monocyte subsets in hTNFtg and K/BxN serum transfer arthritis by flow cytometry. We sorted monocyte subsets and analysed their potential to differentiate into OC and their transcriptional response in response to RANKL by RNA sequencing. With these data, we performed a gene ontology enrichment analysis and gene set enrichment analysis. Results We show that in hTNFtg arthritis local bone erosion and OC generation are even enhanced in the absence of CCR2. We further show the numbers of non-classical monocytes in blood are elevated and are significantly correlated with histological signs of joint destruction. Sorted non-classical monocytes display an increased capacity to differentiate into OCs. This is associated with an increased expression of signal transduction components of RANK, most importantly TRAF6, leading to an increased responsiveness to RANKL. Conclusion Therefore, non-classical monocytes are pivotal cells in arthritis tissue damage and a possible target for therapeutically intervention for the prevention of inflammatory joint damage.