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Protein homeostasis, or proteostasis, is fundamental to cellular and organismal health. Proteostasis collapse is linked to diverse diseases, including neurodegeneration and cancers. The proteostasis network (PN) comprises the intricately regulated interplay of signaling processes and molecular machines involved in the synthesis, folding, and clearance of the diverse spectrum of proteins comprising the folded, native proteome. Human disease biomarkers are important tools for early detection, individualized phenotyping, and patient stratification and for companion diagnostic use during therapy. With the increasing knowledge and understanding of PN disease alterations, various strategies, such as the modulation of chaperone levels or interference with proteasomal activity, for the therapeutic adjustment of proteostasis deregulation have been devised. To complement the tool kit of therapeutic strategies through chemical chaperones or proteostasis regulator drugs, context-specific biomarkers of PN deregulation will provide important guidance for precise pharmacological proteostasis regulation. Here, we summarize representative studies contributing to our understanding of proteostasis deregulation in age-onset neurodegeneration and cancers, with a focus on the chaperome. We call for a systematic mapping and assessment of the global PN interactome network as a resource for the elucidation of diagnostic and prognostic proteostasis biomarkers.

Prostate cancer (PCa) has a broad spectrum of clinical behaviour, hence biomarkers are urgently needed for risk stratification. We previously described the protective effect of STAT3 in a prostate cancer mouse model. By utilizing a gene co-expression network in addition to laser microdissected proteomics from human and murine prostate FFPE samples, we describe STAT3-induced downregulation of the TCA cycle/OXPHOS in PCa on transcriptomic and proteomic level. We identify pyruvate dehydrogenase kinase 4 (PDK4), a key regulator of the TCA cycle, as a promising independent prognostic marker in PCa. PDK4 predicts disease recurrence independent of diagnostic risk factors such as grading, staging and PSA level. Furthermore, PDK4 expression is causally linked to type 2 diabetes mellitus, which is known to have a protective effect on PCa. We conclude that this effect is related to PDK4 expression and that PDK4 loss could serve as a biomarker for PCa with dismal prognosis.

HSP90 action as a conserved chaperone is fundamental to the folding and maturation of a large fraction of structurally and functionally diverse proteins. Through its wide spectrum of clients and their connectivity within the proteome, HSP90 is a key factor in the processes that maintain cellular proteostasis, referred to as the proteostasis network (PN). Besides HSP90, hundreds of additional molecular chaperones and co-chaperones act together in complexes and intricate networks to maintain the cellular native folding environment, avoid misfolding, and redirect non-native folding intermediates back to their native state or towards clearance. The ensemble of all cellular chaperones and co-chaperones constitute the chaperome, which acts to regulate and maintain proteome functionality. Recent insights derived from systematic studies have revealed vast imbalances to cellular proteostasis reflected by chaperome deregulation from aging, to neurodegenerative diseases, and cancers. Deregulation states along with specific chaperome connectivity can represent biomarkers for certain diseases. HSP90 is not acting in isolation but as a component of a comprehensive and dynamic chaperome interactome network. Therefore, a detailed understanding of systems-level alterations of chaperome biology is fundamental towards a better understanding of HSP90 action and its therapeutic targeting in health and disease.

The interplay between drugs and cell metabolism is a key factor in determining both compound potency and toxicity. In particular, how and to what extent transmembrane transporters affect drug uptake and disposition is currently only partially understood. Most transporter proteins belong to two protein families: the ATP-Binding Cassette (ABC) transporter family, whose members are often involved in xenobiotic efflux and drug resistance, and the large and heterogeneous family of Solute carriers (SLCs). We recently argued that SLCs are collectively a rather neglected gene group, with most of its members still poorly characterized, and thus likely to include many yet-to-be-discovered associations with drugs. We searched publicly available resources and literature to define the currently known set of drugs transported by ABCs or SLCs, which involved ~500 drugs and more than 100 transporters. In order to extend this set, we then mined the largest publicly available pharmacogenomics dataset, which involves approximately 1000 molecularly annotated cancer cell lines and their response to 265 chemical compounds, and used regularized linear regression models (Elastic Net, LASSO) to predict drug responses based on SLC and ABC data (expression levels, SNVs, CNVs). The most predictive models included both known and previously unidentified associations between drugs and transporters. To our knowledge, this represents the first application of regularized linear regression to this set of genes, providing an extensive prioritization of potentially pharmacologically interesting interactions.

Proteome balance is safeguarded by the proteostasis network (PN), an intricately regulated network of conserved processes that evolved to maintain native function of the diverse ensemble of protein species, ensuring cellular and organismal health. Proteostasis imbalances and collapse are implicated in a spectrum of human diseases, from neurodegeneration to cancer. The characteristics of PN disease alterations however have not been assessed in a systematic way. Since the chaperome is among the central components of the PN, we focused on the chaperome in our study by utilizing a curated functional ontology of the human chaperome that we connect in a high-confidence physical protein-protein interaction network. Challenged by the lack of a systems-level understanding of proteostasis alterations in the heterogeneous spectrum of human cancers, we assessed gene expression across more than 10,000 patient biopsies covering 22 solid cancers. We derived a novel customized Meta-PCA dimension reduction approach yielding M-scores as quantitative indicators of disease expression changes to condense the complexity of cancer transcriptomics datasets into quantitative functional network topographies. We confirm upregulation of the HSP90 family and also highlight HSP60s, Prefoldins, HSP100s, ER- and mitochondria-specific chaperones as pan-cancer enriched. Our analysis also reveals a surprisingly consistent strong downregulation of small heat shock proteins (sHSPs) and we stratify two cancer groups based on the preferential upregulation of ATP-dependent chaperones. Strikingly, our analyses highlight similarities between stem cell and cancer proteostasis, and diametrically opposed chaperome deregulation between cancers and neurodegenerative diseases. We developed a web-based Proteostasis Profiler tool (Pro2) enabling intuitive analysis and visual exploration of proteostasis disease alterations using gene expression data. Our study showcases a comprehensive profiling of chaperome shifts in human cancers and sets the stage for a systematic global analysis of PN alterations across the human diseasome towards novel hypotheses for therapeutic network re-adjustment in proteostasis disorders., Author summary Protein homeostasis, or proteostasis, is maintained by the proteostasis network (PN), an intricately regulated modular network of interacting processes that evolved to balance the native proteome, supporting cellular and organismal health throughout lifespan. Imbalances and collapse of cellular proteostasis capacity, the capacity to buffer against cytotoxic damage and stress, is increasingly implicated in some of the most challenging diseases of our time, including neurodegeneration and cancers. The systems-level PN alterations in these diseases are not understood to date. Here, we address this challenge, focussing on the human chaperome, the ensemble of chaperones and co-chaperones, which represents a central conserved PN functional arm. We devised a novel data dimensionality reduction approach enabling quantitative contextual visualization of chaperome alterations in the heterogeneous spectrum of cancers based on gene expression data from thousands of patient biopsies. We developed Proteostasis Profiler (Pro2), a new web-tool enabling intuitive visualisation of cancer chaperome deregulation maps. We stratify two cancer groups based on diverging chaperome deregulation and highlight similarities between cancer and stem cell proteostasis. Our study also exposes drastically opposed shifts between cancers and neurodegenerative diseases. Collectively, this study sets the stage for a systematic global analysis of PN alterations across the human diseasome.

SummaryChaperones are central to the proteostasis network (PN) and safeguard the proteome from misfolding, aggregation, and proteotoxicity. We categorized the human chaperome of 332 genes into network communities using function, localization, interactome, and expression data sets. During human brain aging, expression of 32% of the chaperome, corresponding to ATP-dependent chaperone machines, is repressed, whereas 19.5%, corresponding to ATP-independent chaperones and co-chaperones, are induced. These repression and induction clusters are enhanced in the brains of those with Alzheimer’s, Huntington’s, or Parkinson’s disease. Functional properties of the chaperome were assessed by perturbation in C. elegans and human cell models expressing Aβ, polyglutamine, and Huntingtin. Of 219 C. elegans orthologs, knockdown of 16 enhanced both Aβ and polyQ-associated toxicity. These correspond to 28 human orthologs, of which 52% and 41% are repressed, respectively, in brain aging and disease and 37.5% affected Huntingtin aggregation in human cells. These results identify a critical chaperome subnetwork that functions in aging and disease.

The tyrosine kinase Bcr-Abl causes chronic myeloid leukemia and is the cognate target of tyrosine kinase inhibitors like imatinib. We have charted the protein–protein interaction network of Bcr-Abl by a 2-pronged approach. Using a monoclonal antibody we have first purified endogenous Bcr-Abl protein complexes from the CML K562 cell line and characterized the set of most tightly-associated interactors by MS. Nine interactors were subsequently subjected to tandem affinity purifications/MS analysis to obtain a molecular interaction network of some hundred cellular proteins. The resulting network revealed a high degree of interconnection of 7 “core” components around Bcr-Abl (Grb2, Shc1, Crk-I, c-Cbl, p85, Sts-1, and SHIP-2), and their links to different signaling pathways. Quantitative proteomics analysis showed that tyrosine kinase inhibitors lead to a disruption of this network. Certain components still appear to interact with Bcr-Abl in a phosphotyrosine-independent manner. We propose that Bcr-Abl and other drug targets, rather than being considered as single polypeptides, can be considered as complex protein assemblies that remodel upon drug action.

An interview with Alexander von Gabain, CSO of Intercell, one of the leading companies in the area of vaccine development.

PMCID: PMC4266588.-- et al., Just as reference genome sequences revolutionized human genetics, reference maps of interactome networks will be critical to fully understand genotype-phenotype relationships. Here, we describe a systematic map of ∼14,000 high-quality human binary protein-protein interactions. At equal quality, this map is ∼30% larger than what is available from small-scale studies published in the literature in the last few decades. While currently available information is highly biased and only covers a relatively small portion of the proteome, our systematic map appears strikingly more homogeneous, revealing a >broader> human interactome network than currently appreciated. The map also uncovers significant interconnectivity between known and candidate cancer gene products, providing unbiased evidence for an expanded functional cancer landscape, while demonstrating how high-quality interactome models will help >connect the dots> of the genomic revolution., This work was supported primarily by NHGRI grant R01/U01HG001715 awarded to M.V., D.E.H., F.P.R., and J.T. and in part by the following grants and agencies: NHGRI P50HG004233 to M.V., F.P.R., and A.-L.B.; NHLBI U01HL098166 subaward to M.V.; NHLBI U01HL108630 subaward to A.-L.B.; NCI U54CA112962 subaward to M.V.; NCI R33CA132073 to M.V.; NIH RC4HG006066 to M.V., D.E.H., and T.H.; NICHD ARRA R01HD065288, R21MH104766, and R01MH105524 to L.M.I.; NIMH R01MH091350 to L.M.I. and T.H.; NSF CCF-1219007 and NSERC RGPIN-2014-03892 to Y.X.; Canada Excellence Research Chair, Krembil Foundation, Ontario Research Fund–Research Excellence Award, Avon Foundation, grant CSI07A09 from Junta de Castilla y Leon (Valladolid, Spain), grant PI12/00624 from Ministerio de Economia y Competitividad (AES 2012, ISCiii, Madrid, Spain), and grant i-Link0398 from Consejo Superior de Investigaciones Científicas (CSIC, Madrid, Spain) to J.D.L.R.; Spanish Ministerio de Ciencia e Innovación (BIO2010-22073) and the European Commission through the FP7 project SyStemAge grant agreement n: 306240 to P.A.; Group-ID Multidisciplinary Research Partnerships of Ghent University, grant FWO-V G.0864.10 from the Fund for Scientific Research-Flanders and ERC Advanced Grant N° 340941 to J.T.; EMBO long-term fellowship to A.K.; Institute Sponsored Research funds from the Dana-Farber Cancer Institute Strategic Initiative to M.V. I.L. is a postdoctoral fellow with the FWO-V. M.V. is a “Chercheur Qualifié Honoraire” from the Fonds de la Recherche Scientifique (FRS-FNRS, Wallonia-Brussels Federation, Belgium). Since performing the work described, C. Fontanillo has become an employee of Celgene Research SL, part of the Celgene Corporation.

Embryogenesis is controlled by large gene-regulatory networks, which generate spatially and temporally refined patterns of gene expression. Here, we report the characteristics of the regulatory network orchestrating early mesodermal development in the fruitfly Drosophila, where the transcription factor Twist is both necessary and sufficient to drive development. Through the integration of chromatin immunoprecipitation followed by microarray analysis (ChIP-on-chip) experiments during discrete time periods with computational approaches, we identified >2000 Twist-bound cis-regulatory modules (CRMs) and almost 500 direct target genes. Unexpectedly, Twist regulates an almost complete cassette of genes required for cell proliferation in addition to genes essential for morophogenesis and cell migration. Twist targets almost 25% of all annotated Drosophila transcription factors, which may represent the entire set of regulators necessary for the early development of this system. By combining in vivo binding data from Twist, Mef2, Tinman, and Dorsal we have constructed an initial transcriptional network of early mesoderm development. The network topology reveals extensive combinatorial binding, feed-forward regulation, and complex logical outputs as prevalent features. In addition to binary activation and repression, we suggest that Twist binds to almost all mesodermal CRMs to provide the competence to integrate inputs from more specialized transcription factors.

SummaryTelomere capping is the essential function of telomeres. To identify new genes involved in telomere capping, we carried out a genome-wide screen in Saccharomyces cerevisiae for suppressors of cdc13-1, an allele of the telomere-capping protein Cdc13. We report the identification of five novel suppressors, including the previously uncharacterized gene YML036W, which we name CGI121. Cgi121 is part of a conserved protein complex—the KEOPS complex—containing the protein kinase Bud32, the putative peptidase Kae1, and the uncharacterized protein Gon7. Deletion of CGI121 suppresses cdc13-1 via the dramatic reduction in ssDNA levels that accumulate in cdc13-1 cgi121 mutants. Deletion of BUD32 or other KEOPS components leads to short telomeres and a failure to add telomeres de novo to DNA double-strand breaks. Our results therefore indicate that the KEOPS complex promotes both telomere uncapping and telomere elongation.

Here, we report on the outcome of the 2nd International Danube Symposium on advanced biomarker development that was held in Vienna, Austria, in early 2018. During the meeting, cross-speciality participants assessed critical aspects of non-invasive, quantitative biomarker development in view of the need to expand our understanding of disease mechanisms and the definition of appropriate strategies both for molecular diagnostics and personalised therapies. More specifically, panelists addressed the main topics, including the current status of disease characterisation by means of non-invasive imaging, histopathology and liquid biopsies as well as strategies of gaining new understanding of disease formation, modulation and plasticity to large-scale molecular imaging as well as integrative multi-platform approaches. Highlights of the 2018 meeting included dedicated sessions on non-invasive disease characterisation, development of disease and therapeutic tailored biomarkers, standardisation and quality measures in biospecimens, new therapeutic approaches and socio-economic challenges of biomarker developments. The scientific programme was accompanied by a roundtable discussion on identification and implementation of sustainable strategies to address the educational needs in the rapidly evolving field of molecular diagnostics. The central theme that emanated from the 2nd Donau Symposium was the importance of the conceptualisation and implementation of a convergent approach towards a disease characterisation beyond lesion-counting “lumpology” for a cost-effective and patient-centric diagnosis, therapy planning, guidance and monitoring. This involves a judicious choice of diagnostic means, the adoption of clinical decision support systems and, above all, a new way of communication involving all stakeholders across modalities and specialities. Moreover, complex diseases require a comprehensive diagnosis by converging parameters from different disciplines, which will finally yield to a precise therapeutic guidance and outcome prediction. While it is attractive to focus on technical advances alone, it is important to develop a patient-centric approach, thus asking “What can we do with our expertise to help patients?” ISSN:1860-2002 ISSN:1536-1632