High-throughput identification of repurposable neuroactive drugs with potent anti-glioblastoma activity.

Glioblastoma, the most aggressive primary brain cancer, has a dismal prognosis, yet systemic treatment is limited to DNA-alkylating chemotherapies. New therapeutic strategies may emerge from exploring neurodevelopmental and neurophysiological vulnerabilities of glioblastoma. To this end, we systematically screened repurposable neuroactive drugs in glioblastoma patient surgery material using a clinically concordant and single-cell resolved platform.

Simultaneous targeted and discovery-driven clinical proteotyping using hybrid-PRM/DIA.

Background: Clinical samples are irreplaceable, and their transformation into searchable and reusable digital biobanks is critical for conducting statistically empowered retrospective and integrative research studies. Currently, mainly data-independent acquisition strategies are employed to digitize clinical sample cohorts comprehensively. However, the sensitivity of DIA is limited, which is why selected marker candidates are often additionally measured targeted by parallel reaction monitoring.

Proteogenetic drug response profiling elucidates targetable vulnerabilities of myelofibrosis.

Myelofibrosis is a hematopoietic stem cell disorder belonging to the myeloproliferative neoplasms. Myelofibrosis patients frequently carry driver mutations in either JAK2 or Calreticulin (CALR) and have limited therapeutic options. Here, we integrate ex vivo drug response and proteotype analyses across myelofibrosis patient cohorts to discover targetable vulnerabilities and associated therapeutic strategies.

Ex vivo drug response heterogeneity reveals personalized therapeutic strategies for patients with multiple myeloma.

Multiple myeloma (MM) is a plasma cell malignancy defined by complex genetics and extensive patient heterogeneity. Despite a growing arsenal of approved therapies, MM remains incurable and in need of guidelines to identify effective personalized treatments. Here, we survey the ex vivo drug and immunotherapy sensitivities across 101 bone marrow samples from 70 patients with MM using multiplexed immunofluorescence, automated microscopy and deep-learning-based single-cell phenotyping.

Integrated multi-omics reveals anaplerotic rewiring in methylmalonyl-CoA mutase deficiency.

Methylmalonic aciduria (MMA) is an inborn error of metabolism with multiple monogenic causes and a poorly understood pathogenesis, leading to the absence of effective causal treatments. Here we employ multi-layered omics profiling combined with biochemical and clinical features of individuals with MMA to reveal a molecular diagnosis for 177 out of 210 (84%) cases, the majority (148) of whom display pathogenic variants in methylmalonyl-CoA mutase (MMUT). Stratification of these data layers by disease severity shows dysregulation of the tricarboxylic acid cycle and its replenishment (anaplerosis) by glutamine.

Kinase Interaction Network Expands Functional and Disease Roles of Human Kinases.

Protein kinases are essential for signal transduction and control of most cellular processes, including metabolism, membrane transport, motility, and cell cycle. Despite the critical role of kinases in cells and their strong association with diseases, good coverage of their interactions is available for only a fraction of the 535 human kinases. Here, we present a comprehensive mass-spectrometry-based analysis of a human kinase interaction network covering more than 300 kinases.

Complex-centric proteome profiling by SEC-SWATH-MS for the parallel detection of hundreds of protein complexes.

Most catalytic, structural and regulatory functions of the cell are carried out by functional modules, typically complexes containing or consisting of proteins. The composition and abundance of these complexes and the quantitative distribution of specific proteins across different modules are therefore of major significance in basic and translational biology. However, detection and quantification of protein complexes on a proteome-wide scale is technically challenging.

Multi-layered proteomic analyses decode compositional and functional effects of cancer mutations on kinase complexes.

Rapidly increasing availability of genomic data and ensuing identification of disease associated mutations allows for an unbiased insight into genetic drivers of disease development. However, determination of molecular mechanisms by which individual genomic changes affect biochemical processes remains a major challenge. Here, we develop a multilayered proteomic workflow to explore how genetic lesions modulate the proteome and are translated into molecular phenotypes.

Multi-omic measurements of heterogeneity in HeLa cells across laboratories.

Reproducibility in research can be compromised by both biological and technical variation, but most of the focus is on removing the latter. Here we investigate the effects of biological variation in HeLa cell lines using a systems-wide approach. We determine the degree of molecular and phenotypic variability across 14 stock HeLa samples from 13 international laboratories.

ASPP proteins discriminate between PP1 catalytic subunits through their SH3 domain and the PP1 C-tail.

Serine/threonine phosphatases such as PP1 lack substrate specificity and associate with a large array of targeting subunits to achieve the requisite selectivity. The tumour suppressor ASPP (apoptosis-stimulating protein of p53) proteins associate with PP1 catalytic subunits and are implicated in multiple functions from transcriptional regulation to cell junction remodelling. Here we show that Drosophila ASPP is part of a multiprotein PP1 complex and that PP1 association is necessary for several in vivo functions of Drosophila ASPP.

Complex-centric proteome profiling by SEC-SWATH-MS.

Proteins are major effectors and regulators of biological processes that can elicit multiple functions depending on their interaction with other proteins. The organization of proteins into macromolecular complexes and their quantitative distribution across these complexes is, therefore, of great biological and clinical significance. In this paper, we describe an integrated experimental and computational technique to quantify hundreds of protein complexes in a single operation.

Systematic Analysis of Human Protein Phosphatase Interactions and Dynamics.

Coordinated activities of protein kinases and phosphatases ensure phosphorylation homeostasis, which, when perturbed, can instigate diseases, including cancer. Yet, in contrast to kinases, much less is known about protein phosphatase functions and their interactions and complexes. Here, we used quantitative affinity proteomics to assay protein-protein interactions for 54 phosphatases distributed across the three major protein phosphatase families, with additional analysis of their 12 co-factors.

Interaction proteome of human Hippo signaling: modular control of the co-activator YAP1.

Tissue homeostasis is controlled by signaling systems that coordinate cell proliferation, cell growth and cell shape upon changes in the cellular environment. Deregulation of these processes is associated with human cancer and can occur at multiple levels of the underlying signaling systems. To gain an integrated view on signaling modules controlling tissue growth, we analyzed the interaction proteome of the human Hippo pathway, an established growth regulatory signaling system.

The protein interaction landscape of the human CMGC kinase group.

Cellular information processing via reversible protein phosphorylation requires tight control of the localization, activity, and substrate specificity of protein kinases, which to a large extent is accomplished by complex formation with other proteins. Despite their critical role in cellular regulation and pathogenesis, protein interaction information is available for only a subset of the 518 human protein kinases. Here we present a global proteomic analysis of complexes of the human CMGC kinase group.

Interlaboratory reproducibility of large-scale human protein-complex analysis by standardized AP-MS.

The characterization of all protein complexes of human cells under defined physiological conditions using affinity purification-mass spectrometry (AP-MS) is a highly desirable step in the quest to understand the phenotypic effects of genomic information. However, such a challenging goal has not yet been achieved, as it requires reproducibility of the experimental workflow and high data consistency across different studies and laboratories. We systematically investigated the reproducibility of a standardized AP-MS workflow by performing a rigorous interlaboratory comparative analysis of the interactomes of 32 human kinases.