SubCellBarCode: Proteome-wide Mapping of Protein Localization and Relocalization.

Subcellular localization is a main determinant of protein function; however, a global view of cellular proteome organization remains relatively unexplored. We have developed a robust mass spectrometry-based analysis pipeline to generate a proteome-wide view of subcellular localization for proteins mapping to 12,418 individual genes across five cell lines. Based on more than 83,000 unique classifications and correlation profiling, we investigate the effect of alternative splicing and protein domains on localization, complex member co-localization, cell-type-specific localization, as well as protein relocalization after growth factor inhibition. Our analysis provides information about the cellular architecture and complexity of the spatial organization of the proteome; we show that the majority of proteins have a single main subcellular location, that alternative splicing rarely affects subcellular location, and that cell types are best distinguished by expression of proteins exposed to the surrounding environment. The resource is freely accessible via www.subcellbarcode.org.

GLI1-induced mammary gland tumours are transplantable and maintain major molecular features.

Increased expression of GLI1, the main Hedgehog signalling pathway effector, is related to unfavourable prognosis and progressive disease of certain breast cancer subtypes. We used conditional transgenic mice induced to overexpress GLI1 in the mammary epithelium either alone or in combination with deletion of one Trp53 allele to address the role of elevated GLI1 expression in breast tumour initiation and progression. Induced GLI1 expression facilitates mammary gland tumour formation and this was further increased upon heterozygous deletion of Trp53. The GLI1-induced primary tumours were of different murine molecular subtypes, including Normal-likeEx , Class8Ex , Claudin-LowEx and Erbb2-likeEx . The gene expression profiles of some of the tumours correlated well with the PAM50 subtypes for human breast cancer. Whole-exome sequencing revealed somatic mutation profiles with only little overlap between the primary tumours. Orthotopically serially transplanted GLI1-induced tumours maintained the main morphological characteristics of the primary tumours for ≥10 generations. Independent of Trp53 status and molecular subtype, the serially transplanted GLI1-induced tumours were able to grow both in the absence of transgenic GLI1 expression and in the presence of the GLI1 inhibitor GANT61. These data suggest that elevated GLI1 expression has a determinant role in tumour initiation; however, additional genetic events are required for tumour progression.

Stroma-regulated HMGA2 is an independent prognostic marker in PDAC and AAC.

BACKGROUND: The HMGA2 protein has experimentally been linked to EMT and cancer stemness. Recent studies imply that tumour-stroma interactions regulate these features and thereby contribute to tumour aggressiveness. METHODS: We analysed 253 cases of pancreatic ductal adenocarcinoma (PDAC) and 155 cases of ampullary adenocarcinoma (AAC) for HMGA2 expression by IHC. The data were correlated with stroma abundance and supplemented by experimental studies. RESULTS: HMGA2 acts as an independent prognostic marker associated with a significantly shorter overall survival in both tumour types. Overall, HMGA2-positivity was more frequent in patients with PDAC than with AAC. The HMGA2 status in tumour cells significantly correlated with the abundance of PDGFRß-defined stroma cells. In vivo co-injection of Panc-1 cancer cells with pancreatic stellate cells increased tumour growth in a manner associated with increased HMGA2 expression. Furthermore, in vitro treatment of Panc-1 with conditioned media from PDGF-BB-activated stellate cells increased their ability to form tumour spheroids. CONCLUSIONS: This study identifies HMGA2 expression in tumour cells as an independent prognostic marker in PDAC and AAC. Correlative data analysis gives novel tissue-based evidence for a heterotypic cross-talk with stroma cells as a possible mechanism for HMGA2 induction, which is further supported by experimental models.

Prognostic significance in breast cancer of a gene signature capturing stromal PDGF signaling.

In this study, we describe a novel gene expression signature of platelet-derived growth factor (PDGF)-activated fibroblasts, which is able to identify breast cancers with a PDGF-stimulated fibroblast stroma and displays an independent and strong prognostic significance. Global gene expression was compared between PDGF-stimulated human fibroblasts and cultured resting fibroblasts. The most differentially expressed genes were reduced to a gene expression signature of 113 genes. The biological significance and prognostic capacity of this signature were investigated using four independent clinical breast cancer data sets. Concomitant high expression of PDGFß receptor and its cognate ligands is associated with a high PDGF signature score. This supports the notion that the signature detects tumors with PDGF-activated stroma. Subsequent analyses indicated significant associations between high PDGF signature score and clinical characteristics, including human epidermal growth factor receptor 2 positivity, estrogen receptor negativity, high tumor grade, and large tumor size. A high PDGF signature score is associated with shorter survival in univariate analysis. Furthermore, the high PDGF signature score acts as a significant marker of poor prognosis in multivariate survival analyses, including classic prognostic markers, Ki-67 status, a proliferation gene signature, or other recently described stroma-derived gene expression signatures.

Comparative interactomics with Funcoup 2.0.

FunCoup (http://FunCoup.sbc.su.se) is a database that maintains and visualizes global gene/protein networks of functional coupling that have been constructed by Bayesian integration of diverse high-throughput data. FunCoup achieves high coverage by orthology-based integration of data sources from different model organisms and from different platforms. We here present release 2.0 in which the data sources have been updated and the methodology has been refined. It contains a new data type Genetic Interaction, and three new species: chicken, dog and zebra fish. As FunCoup extensively transfers functional coupling information between species, the new input datasets have considerably improved both coverage and quality of the networks. The number of high-confidence network links has increased dramatically. For instance, the human network has more than eight times as many links above confidence 0.5 as the previous release. FunCoup provides facilities for analysing the conservation of subnetworks in multiple species. We here explain how to do comparative interactomics on the FunCoup website.

InParanoid 7: new algorithms and tools for eukaryotic orthology analysis.

The InParanoid project gathers proteomes of completely sequenced eukaryotic species plus Escherichia coli and calculates pairwise ortholog relationships among them. The new release 7.0 of the database has grown by an order of magnitude over the previous version and now includes 100 species and their collective 1.3 million proteins organized into 42.7 million pairwise ortholog groups. The InParanoid algorithm itself has been revised and is now both more specific and sensitive. Based on results from our recent benchmarking of low-complexity filters in homology assignment, a two-pass BLAST approach was developed that makes use of high-precision compositional score matrix adjustment, but avoids the alignment truncation that sometimes follows. We have also updated the InParanoid web site (http://InParanoid.sbc.su.se). Several features have been added, the response times have been improved and the site now sports a new, clearer look. As the number of ortholog databases has grown, it has become difficult to compare among these resources due to a lack of standardized source data and incompatible representations of ortholog relationships. To facilitate data exchange and comparisons among ortholog databases, we have developed and are making available two XML schemas: SeqXML for the input sequences and OrthoXML for the output ortholog clusters.

Network analysis of functional genomics data: application to avian sex-biased gene expression.

Gene expression analysis is often used to investigate the molecular and functional underpinnings of a phenotype. However, differential expression of individual genes is limited in that it does not consider how the genes interact with each other in networks. To address this shortcoming we propose a number of network-based analyses that give additional functional insights into the studied process. These were applied to a dataset of sex-specific gene expression in the chicken gonad and brain at different developmental stages. We first constructed a global chicken interaction network. Combining the network with the expression data showed that most sex-biased genes tend to have lower network connectivity, that is, act within local network environments, although some interesting exceptions were found. Genes of the same sex bias were generally more strongly connected with each other than expected. We further studied the fates of duplicated sex-biased genes and found that there is a significant trend to keep the same pattern of sex bias after duplication. We also identified sex-biased modules in the network, which reveal pathways or complexes involved in sex-specific processes. Altogether, this work integrates evolutionary genomics with systems biology in a novel way, offering new insights into the modular nature of sex-biased genes.

Kalign2: high-performance multiple alignment of protein and nucleotide sequences allowing external features.

In the growing field of genomics, multiple alignment programs are confronted with ever increasing amounts of data. To address this growing issue we have dramatically improved the running time and memory requirement of Kalign, while maintaining its high alignment accuracy. Kalign version 2 also supports nucleotide alignment, and a newly introduced extension allows for external sequence annotation to be included into the alignment procedure. We demonstrate that Kalign2 is exceptionally fast and memory-efficient, permitting accurate alignment of very large numbers of sequences. The accuracy of Kalign2 compares well to the best methods in the case of protein alignments while its accuracy on nucleotide alignments is generally superior. In addition, we demonstrate the potential of using known or predicted sequence annotation to improve the alignment accuracy. Kalign2 is freely available for download from the Kalign web site (http://msa.sbc.su.se/).

PTEN and DNA-PK determine sensitivity and recovery in response to WEE1 inhibition in human breast cancer.

Inhibition of WEE1 kinase by AZD1775 has shown promising results in clinical cancer trials, but markers predicting AZD1775 response are lacking. Here we analysed AZD1775 response in a panel of human breast cancer (BC) cell lines by global proteome/transcriptome profiling and identified two groups of basal-like BC (BLBCs): 'PTEN low' BLBCs were highly sensitive to AZD1775 and failed to recover following removal of AZD1775, while 'PTEN high' BLBCs recovered. AZD1775 induced phosphorylation of DNA-PK, protecting cells from replication-associated DNA damage and promoting cellular recovery. Deletion of DNA-PK or PTEN, or inhibition of DNA-PK sensitized recovering BLBCs to AZD1775 by abrogating replication arrest, allowing replication despite DNA damage. This was linked to reduced CHK1 activation, increased cyclin E levels and apoptosis. In conclusion, we identified PTEN and DNA-PK as essential regulators of replication checkpoint arrest in response to AZD1775 and defined PTEN as a promising biomarker for efficient WEE1 cancer therapy.

A Novel ACKR2-Dependent Role of Fibroblast-Derived CXCL14 in Epithelial-to-Mesenchymal Transition and Metastasis of Breast Cancer.

PURPOSE: Fibroblasts expressing the orphan chemokine CXCL14 have been previously shown to associate with poor breast cancer prognosis and promote cancer growth. This study explores the mechanism underlying the poor survival associations of stromal CXCL14. EXPERIMENTAL DESIGN: Tumor cell epithelial-to-mesenchymal transition (EMT), invasion, and metastasis were studied in in vitro and in vivo models together with fibroblasts overexpressing CXCL14. An approach for CXCL14 receptor identification included loss-of-function studies followed by molecular and functional endpoints. The clinical relevance was further explored in publicly available gene expression datasets. RESULTS: CXCL14 fibroblasts stimulated breast cancer EMT, migration, and invasion in breast cancer cells and in a xenograft model. Furthermore, tumor cells primed by CXCL14 fibroblasts displayed enhanced lung colonization after tail-vein injection. By loss-of function experiments, the atypical G-protein-coupled receptor ACKR2 was identified to mediate CXCL14-stimulated responses. Downregulation of ACKR2, or CXCL14-induced NOS1, attenuated the pro-EMT and migratory capacity. CXCL14/ACKR2 expression correlated with EMT and survival in gene expression datasets. CONCLUSIONS: Collectively, the findings imply an autocrine fibroblast CXCL14/ACKR2 pathway as a clinically relevant stimulator of EMT, tumor cell invasion, and metastasis. The study also identifies ACKR2 as a novel mediator for CXCL14 function and thereby defines a pathway with drug target potential.See related commentary by Zhang et al., p. 3476.

High expression of stromal PDGFRß is associated with reduced benefit of tamoxifen in breast cancer.

Cancer-associated fibroblasts (CAFs) regulate tumour growth, metastasis and response to treatment. Recent studies indicate the existence of functionally distinct CAF subsets. Suggested mechanisms whereby CAFs can impact on treatment response include paracrine signalling affecting cancer cell drug sensitivity and effects on tumour drug uptake. PDGFRß is an important regulator of fibroblasts. Experimental studies have linked PDGFRß-positive fibroblasts to metastasis and also to reduced tumour drug uptake. This study has investigated the potential role of PDGFRß-positive fibroblasts in response to adjuvant tamoxifen treatment of breast cancer. Analyses of two breast cancer collections from randomised studies analysing adjuvant tamoxifen treatment in early breast cancer demonstrated significant benefit of tamoxifen in the group with low stromal PDGFRß, which was not observed in the group with high stromal PDGFRß. In general terms these findings provide novel evidence, derived from analyses of randomised clinical studies, of response-predictive capacity of a marker-defined subset of CAFs and, more specifically, identify stromal PDGFRß as a marker related to tamoxifen benefit in early breast cancer.

Interferon-γ-induced p27KIP1 binds to and targets MYC for proteasome-mediated degradation.

The Myc oncoprotein is tightly regulated at multiple levels including ubiquitin-mediated protein turnover. We recently demonstrated that inhibition of Cdk2-mediated phosphorylation of Myc at Ser-62 pharmacologically or through interferon (IFN)-γ-induced expression of p27(Kip1) (p27) repressed Myc's activity to suppress cellular senescence and differentiation. In this study we identified an additional activity of p27 to interfere with Myc independent of Ser-62 phosphorylation. p27 is required and sufficient for IFN-γ-induced turnover of Myc. p27 interacted with Myc in the nucleus involving the C-termini of the two proteins, including Myc box 4 of Myc. The C-terminus but not the Cdk2 binding fragment of p27 was sufficient for inducing Myc degradation. Protein expression data of The Cancer Genome Atlas breast invasive carcinoma set revealed significantly lower Myc protein levels in tumors with highly expressed p27 lacking phosphorylation at Thr-157--a marker for active p27 localized in the nucleus. Further, these conditions correlated with favorable tumor stage and patient outcome. This novel regulation of Myc by IFN-γ/p27(KIP1) potentially offers new possibilities for therapeutic intervention in tumors with deregulated Myc.

Stromal Hedgehog signalling is downregulated in colon cancer and its restoration restrains tumour growth.

A role for Hedgehog (Hh) signalling in the development of colorectal cancer (CRC) has been proposed. In CRC and other solid tumours, Hh ligands are upregulated; however, a specific Hh antagonist provided no benefit in a clinical trial. Here we use Hh reporter mice to show that downstream Hh activity is unexpectedly diminished in a mouse model of colitis-associated colon cancer, and that downstream Hh signalling is restricted to the stroma. Functionally, stroma-specific Hh activation in mice markedly reduces the tumour load and blocks progression of advanced neoplasms, partly via the modulation of BMP signalling and restriction of the colonic stem cell signature. By contrast, attenuated Hh signalling accelerates colonic tumourigenesis. In human CRC, downstream Hh activity is similarly reduced and canonical Hh signalling remains predominantly paracrine. Our results suggest that diminished downstream Hh signalling enhances CRC development, and that stromal Hh activation can act as a colonic tumour suppressor.

A genome-wide IR-induced RAD51 foci RNAi screen identifies CDC73 involved in chromatin remodeling for DNA repair.

To identify new regulators of homologous recombination repair, we carried out a genome-wide short-interfering RNA screen combined with ionizing irradiation using RAD51 foci formation as readout. All candidates were confirmed by independent short-interfering RNAs and validated in secondary assays like recombination repair activity and RPA foci formation. Network analysis of the top modifiers identified gene clusters involved in recombination repair as well as components of the ribosome, the proteasome and the spliceosome, which are known to be required for effective DNA repair. We identified and characterized the RNA polymerase II-associated protein CDC73/Parafibromin as a new player in recombination repair and show that it is critical for genomic stability. CDC73 interacts with components of the SCF/Cullin and INO80/NuA4 chromatin-remodeling complexes to promote Histone ubiquitination. Our findings indicate that CDC73 is involved in local chromatin decondensation at sites of DNA damage to promote DNA repair. This function of CDC73 is related to but independent of its role in transcriptional elongation.

Cancer-associated fibroblasts expressing CXCL14 rely upon NOS1-derived nitric oxide signaling for their tumor-supporting properties.

Cancer-associated fibroblasts (CAF) stimulate tumor growth and metastasis. Signals supporting CAF function are thus emerging as candidate therapeutic targets in the tumor microenvironment. The chemokine CXCL14 is a potent inducer of CAF protumorigenic functions. This study is aimed at learning how the protumoral functions of CXCL14-expressing CAF are maintained. We found that the nitric oxide synthase NOS1 is upregulated in CXCL14-expressing CAF and in fibroblasts stimulated with CXCL14. Induction of Nos1 was associated with oxidative stress and occurred together with activation of NRF2 and HIF1α signaling in CXCL14-expressing CAF. Genetic or pharmacologic inhibition of NOS1 reduced the growth of CXCL14-expressing fibroblasts along with their ability to promote tumor formation following coinjection with prostate or breast cancer cells. Tumor analysis revealed reduced macrophage infiltration, with NOS1 downregulation in CXCL14-expressing CAF and lymphangiogenesis as a novel component of CXCL14-promoted tumor growth. Collectively, our findings defined key components of a signaling network that maintains the protumoral functions of CXCL14-stimulated CAF, and they identified NOS1 as intervention target for CAF-directed cancer therapy.

MGclus: network clustering employing shared neighbors.

Network analysis is an important tool for functional annotation of genes and proteins. A common approach to discern structure in a global network is to infer network clusters, or modules, and assume a functional coherence within each module, which may represent a complex or a pathway. It is however not trivial to define optimal modules. Although many methods have been proposed, it is unclear which methods perform best in general. It seems that most methods produce far from optimal results but in different ways. MGclus is a new algorithm designed to detect modules with a strongly interconnected neighborhood in large scale biological interaction networks. In our benchmarks we found MGclus to outperform other methods when applied to random graphs with varying degree of noise, and to perform equally or better when applied to biological protein interaction networks. MGclus is implemented in Java and utilizes the JGraphT graph library. It has an easy to use command-line interface and is available for download from .

Statistical assessment of crosstalk enrichment between gene groups in biological networks.

MOTIVATION: Analyzing groups of functionally coupled genes or proteins in the context of global interaction networks has become an important aspect of bioinformatic investigations. Assessing the statistical significance of crosstalk enrichment between or within groups of genes can be a valuable tool for functional annotation of experimental gene sets. RESULTS: Here we present CrossTalkZ, a statistical method and software to assess the significance of crosstalk enrichment between pairs of gene or protein groups in large biological networks. We demonstrate that the standard z-score is generally an appropriate and unbiased statistic. We further evaluate the ability of four different methods to reliably recover crosstalk within known biological pathways. We conclude that the methods preserving the second-order topological network properties perform best. Finally, we show how CrossTalkZ can be used to annotate experimental gene sets using known pathway annotations and that its performance at this task is superior to gene enrichment analysis (GEA). AVAILABILITY AND IMPLEMENTATION: CrossTalkZ (available at http://sonnhammer.sbc.su.se/download/software/CrossTalkZ/) is implemented in C++, easy to use, fast, accepts various input file formats, and produces a number of statistics. These include z-score, p-value, false discovery rate, and a test of normality for the null distributions.