A proteome-scale map of the human interactome network.

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.

STAT3-dependent analysis reveals PDK4 as independent predictor of recurrence in prostate cancer.

Prostate cancer (PCa) has a broad spectrum of clinical behavior; hence, biomarkers are urgently needed for risk stratification. Here, we aim to find potential biomarkers for risk stratification, by utilizing a gene co-expression network of transcriptomics data in addition to laser-microdissected proteomics from human and murine prostate FFPE samples. We show up-regulation of oxidative phosphorylation (OXPHOS) in PCa on the transcriptomic level and up-regulation of the TCA cycle/OXPHOS on the proteomic level, which is inversely correlated to STAT3 expression. We hereby identify gene expression of 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. Therefore, low PDK4 is a promising marker for PCa with dismal prognosis.

A systematic atlas of chaperome deregulation topologies across the human cancer landscape.

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.

Charting the molecular network of the drug target Bcr-Abl.

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.

In silico Prioritization of Transporter-Drug Relationships From Drug Sensitivity Screens.

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 1,000 molecularly annotated cancer cell lines and their response to 265 anti-cancer 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.

Model systems of protein-misfolding diseases reveal chaperone modifiers of proteotoxicity.

Chaperones and co-chaperones enable protein folding and degradation, safeguarding the proteome against proteotoxic stress. Chaperones display dynamic responses to exogenous and endogenous stressors and thus constitute a key component of the proteostasis network (PN), an intricately regulated network of quality control and repair pathways that cooperate to maintain cellular proteostasis. It has been hypothesized that aging leads to chronic stress on the proteome and that this could underlie many age-associated diseases such as neurodegeneration. Understanding the dynamics of chaperone function during aging and disease-related proteotoxic stress could reveal specific chaperone systems that fail to respond to protein misfolding. Through the use of suppressor and enhancer screens, key chaperones crucial for proteostasis maintenance have been identified in model organisms that express misfolded disease-related proteins. This review provides a literature-based analysis of these genetic studies and highlights prominent chaperone modifiers of proteotoxicity, which include the HSP70-HSP40 machine and small HSPs. Taken together, these studies in model systems can inform strategies for therapeutic regulation of chaperone functionality, to manage aging-related proteotoxic stress and to delay the onset of neurodegenerative diseases.

Combined Population Dynamics and Entropy Modelling Supports Patient Stratification in Chronic Myeloid Leukemia.

Modelling the parameters of multistep carcinogenesis is key for a better understanding of cancer progression, biomarker identification and the design of individualized therapies. Using chronic myeloid leukemia (CML) as a paradigm for hierarchical disease evolution we show that combined population dynamic modelling and CML patient biopsy genomic analysis enables patient stratification at unprecedented resolution. Linking CD34(+) similarity as a disease progression marker to patient-derived gene expression entropy separated established CML progression stages and uncovered additional heterogeneity within disease stages. Importantly, our patient data informed model enables quantitative approximation of individual patients' disease history within chronic phase (CP) and significantly separates "early" from "late" CP. Our findings provide a novel rationale for personalized and genome-informed disease progression risk assessment that is independent and complementary to conventional measures of CML disease burden and prognosis.

A chaperome subnetwork safeguards proteostasis in aging and neurodegenerative disease.

Chaperones 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 Aß, polyglutamine, and Huntingtin. Of 219 C. elegans orthologs, knockdown of 16 enhanced both Aß 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.

Intercell - accelerating innovation.

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

A core transcriptional network for early mesoderm development in Drosophila melanogaster.

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.

A genome-wide screen identifies the evolutionarily conserved KEOPS complex as a telomere regulator.

Telomere 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.