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.

CC-90009, a novel cereblon E3 ligase modulator, targets acute myeloid leukemia blasts and leukemia stem cells.

A number of clinically validated drugs have been developed by repurposing the CUL4-DDB1-CRBN-RBX1 (CRL4CRBN) E3 ubiquitin ligase complex with molecular glue degraders to eliminate disease-driving proteins. Here, we present the identification of a first-in-class GSPT1-selective cereblon E3 ligase modulator, CC-90009. Biochemical, structural, and molecular characterization demonstrates that CC-90009 coopts the CRL4CRBN to selectively target GSPT1 for ubiquitination and proteasomal degradation. Depletion of GSPT1 by CC-90009 rapidly induces acute myeloid leukemia (AML) apoptosis, reducing leukemia engraftment and leukemia stem cells (LSCs) in large-scale primary patient xenografting of 35 independent AML samples, including those with adverse risk features. Using a genome-wide CRISPR-Cas9 screen for effectors of CC-90009 response, we uncovered the ILF2 and ILF3 heterodimeric complex as a novel regulator of cereblon expression. Knockout of ILF2/ILF3 decreases the production of full-length cereblon protein via modulating CRBN messenger RNA alternative splicing, leading to diminished response to CC-90009. The screen also revealed that the mTOR signaling and the integrated stress response specifically regulate the response to CC-90009 in contrast to other cereblon modulators. Hyperactivation of the mTOR pathway by inactivation of TSC1 and TSC2 protected against the growth inhibitory effect of CC-90009 by reducing CC-90009-induced binding of GSPT1 to cereblon and subsequent GSPT1 degradation. On the other hand, GSPT1 degradation promoted the activation of the GCN1/GCN2/ATF4 pathway and subsequent apoptosis in AML cells. Collectively, CC-90009 activity is mediated by multiple layers of signaling networks and pathways within AML blasts and LSCs, whose elucidation gives insight into further assessment of CC-90009s clinical utility. These trials were registered at www.clinicaltrials.gov as #NCT02848001 and #NCT04336982).

Leveraging gene expression subgroups to classify DLBCL patients and select for clinical benefit from a novel agent.

Diffuse large B-cell lymphoma (DLBCL) is a heterogeneous disease, commonly described by cell-of-origin (COO) molecular subtypes. We sought to identify novel patient subgroups through an unsupervised analysis of a large public dataset of gene expression profiles from newly diagnosed de novo DLBCL patients, yielding 2 biologically distinct subgroups characterized by differences in the tumor microenvironment. Pathway analysis and immune deconvolution algorithms identified higher B-cell content and a strong proliferative signal in subgroup A and enriched T-cell, macrophage, and immune/inflammatory signals in subgroup B, reflecting similar biology to published DLBCL stratification research. A gene expression classifier, featuring 26 gene expression scores, was derived from the public dataset to discriminate subgroup A (classifier-negative, immune-low) and subgroup B (classifier-positive, immune-high) patients. Subsequent application to an independent series of diagnostic biopsies replicated the subgroups, with immune cell composition confirmed via immunohistochemistry. Avadomide, a CRL4CRBN E3 ubiquitin ligase modulator, demonstrated clinical activity in relapsed/refractory DLBCL patients, independent of COO subtypes. Given the immunomodulatory activity of avadomide and the need for a patient-selection strategy, we applied the gene expression classifier to pretreatment biopsies from relapsed/refractory DLBCL patients receiving avadomide (NCT01421524). Classifier-positive patients exhibited an enrichment in response rate and progression-free survival of 44% and 6.2 months vs 19% and 1.6 months for classifier-negative patients (hazard ratio, 0.49; 95% confidence interval, 0.280-0.86; P = .0096). The classifier was not prognostic for rituximab, cyclophosphamide, doxorubicin, vincristine, prednisone or salvage immunochemotherapy. The classifier described here discriminates DLBCL tumors based on tumor and nontumor composition and has potential utility to enrich for clinical response to immunomodulatory agents, including avadomide.

CC-122, a pleiotropic pathway modifier, mimics an interferon response and has antitumor activity in DLBCL.

Cereblon (CRBN), a substrate receptor of the Cullin 4 RING E3 ubiquitin ligase complex, is the target of the immunomodulatory drugs lenalidomide and pomalidomide. Recently, it was demonstrated that binding of these drugs to CRBN promotes the ubiquitination and subsequent degradation of 2 common substrates, transcription factors Aiolos and Ikaros. Here we report that CC-122, a new chemical entity termed pleiotropic pathway modifier, binds CRBN and promotes degradation of Aiolos and Ikaros in diffuse large B-cell lymphoma (DLBCL) and T cells in vitro, in vivo, and in patients, resulting in both cell autonomous as well as immunostimulatory effects. In DLBCL cell lines, CC-122-induced degradation or short hairpin RNA-mediated knockdown of Aiolos and Ikaros correlates with increased transcription of interferon (IFN)-stimulated genes independent of IFN-α, -ß, and -γ production and/or secretion and results in apoptosis in both activated B-cell (ABC) and germinal center B-cell DLBCL cell lines. Our results provide mechanistic insight into the cell-of-origin independent antilymphoma activity of CC-122, in contrast to the ABC subtype selective activity of lenalidomide.

Functional Gene Networks: R/Bioc package to generate and analyse gene networks derived from functional enrichment and clustering.

Functional Gene Networks (FGNet) is an R/Bioconductor package that generates gene networks derived from the results of functional enrichment analysis (FEA) and annotation clustering. The sets of genes enriched with specific biological terms (obtained from a FEA platform) are transformed into a network by establishing links between genes based on common functional annotations and common clusters. The network provides a new view of FEA results revealing gene modules with similar functions and genes that are related to multiple functions. In addition to building the functional network, FGNet analyses the similarity between the groups of genes and provides a distance heatmap and a bipartite network of functionally overlapping genes. The application includes an interface to directly perform FEA queries using different external tools: DAVID, GeneTerm Linker, TopGO or GAGE; and a graphical interface to facilitate the use.

Analyse multiple disease subtypes and build associated gene networks using genome-wide expression profiles.

BACKGROUND: Despite the large increase of transcriptomic studies that look for gene signatures on diseases, there is still a need for integrative approaches that obtain separation of multiple pathological states providing robust selection of gene markers for each disease subtype and information about the possible links or relations between those genes. RESULTS: We present a network-oriented and data-driven bioinformatic approach that searches for association of genes and diseases based on the analysis of genome-wide expression data derived from microarrays or RNA-Seq studies. The approach aims to (i) identify gene sets associated to different pathological states analysed together; (ii) identify a minimum subset within these genes that unequivocally differentiates and classifies the compared disease subtypes; (iii) provide a measurement of the discriminant power of these genes and (iv) identify links between the genes that characterise each of the disease subtypes. This bioinformatic approach is implemented in an R package, named geNetClassifier, available as an open access tool in Bioconductor. To illustrate the performance of the tool, we applied it to two independent datasets: 250 samples from patients with four major leukemia subtypes analysed using expression arrays; another leukemia dataset analysed with RNA-Seq that includes a subtype also present in the previous set. The results show the selection of key deregulated genes recently reported in the literature and assigned to the leukemia subtypes studied. We also show, using these independent datasets, the selection of similar genes in a network built for the same disease subtype. CONCLUSIONS: The construction of gene networks related to specific disease subtypes that include parameters such as gene-to-gene association, gene disease specificity and gene discriminant power can be very useful to draw gene-disease maps and to unravel the molecular features that characterize specific pathological states. The application of the bioinformatic tool here presented shows a neat way to achieve such molecular characterization of the diseases using genome-wide expression data.

Identification of a characteristic copy number alteration profile by high-resolution single nucleotide polymorphism arrays associated with metastatic sporadic colorectal cancer.

BACKGROUND: Metastatic dissemination is the most frequent cause of death in patients with sporadic colorectal cancer (sCRC). It is believed that the metastatic process is related at least in part to a specific background of genetic alterations accumulated in cells from primary tumors, and the ability to detect such alterations is critical for the identification of patients with sCRC who are at risk of developing metastases. METHODS: The authors used high-resolution, 500-K single nucleotide polymorphism arrays to identify copy number alteration profiles present at diagnosis in primary tumors from patients with metastatic (n = 23) versus nonmetastatic (n = 26) sCRC. RESULTS: The results revealed a characteristic pattern of copy number alterations in metastatic sCRC tumors that involved losses of 23 regions at chromosomes 1p, 17p, and 18q, together with gains of 35 regions at chromosomes 7 and 13q. CONCLUSIONS: In line with expectations, the copy number profile investigated involved multiple genes that were associated previously with sCRC (ie, SMAD2) and/or the metastatic process (ie, podocalyxin-like [PODXL]), and it also was associated with a poorer outcome.

Combined analysis of genome-wide expression and copy number profiles to identify key altered genomic regions in cancer.

BACKGROUND: Analysis of DNA copy number alterations and gene expression changes in human samples have been used to find potential target genes in complex diseases. Recent studies have combined these two types of data using different strategies, but focusing on finding gene-based relationships. However, it has been proposed that these data can be used to identify key genomic regions, which may enclose causal genes under the assumption that disease-associated gene expression changes are caused by genomic alterations.

Unique genetic profile of sporadic colorectal cancer liver metastasis versus primary tumors as defined by high-density single-nucleotide polymorphism arrays.

Most genetic studies in colorectal carcinomas have focused on those abnormalities that are acquired by primary tumors, particularly in the transition from adenoma to carcinoma, whereas few studies have compared the genetic abnormalities of primary versus paired metastatic samples. In this study, we used high-density 500K single-nucleotide polymorphism arrays to map the overall genetic changes present in liver metastases (n=20) from untreated colorectal carcinoma patients studied at diagnosis versus their paired primary tumors (n=20). MLH1, MSH2 and MSH6 gene expression was measured in parallel by immunohistochemistry. Overall, metastatic tumors systematically contained those genetic abnormalities observed in the primary tumor sample from the same subject. However, liver metastases from many cases (up to 8 out of 20) showed acquisition of genetic aberrations that were not found in their paired primary tumors. These new metastatic aberrations mainly consisted of (1) an increased frequency of genetic lesions of chromosomes that have been associated with metastatic colorectal carcinoma (1p, 7p, 8q, 13q, 17p, 18q, 20q) and, more interestingly, (2) acquisition of new chromosomal abnormalities (eg, losses of chromosomes 4 and 10q and gains of chromosomes 5p and 6p). These genetic changes acquired by metastatic tumors may be associated with either the metastatic process and/or adaption of metastatic cells to the liver microenvironment. Further studies in larger series of patients are necessary to dissect the specific role of each of the altered genes and chromosomal regions in the metastatic spread of colorectal tumors.

Deciphering the mechanisms of CC-122 resistance in DLBCL via a genome-wide CRISPR screen.

CC-122 is a next-generation cereblon E3 ligase-modulating agent that has demonstrated promising clinical efficacy in patients with relapsed or refractory diffuse large B-cell lymphoma (R/R DLBCL). Mechanistically, CC-122 induces the degradation of IKZF1/3, leading to T-cell activation and robust cell-autonomous killing in DLBCL. We report a genome-wide CRISPR/Cas9 screening for CC-122 in a DLBCL cell line SU-DHL-4 with follow-up mechanistic characterization in 6 DLBCL cell lines to identify genes regulating the response to CC-122. Top-ranked CC-122 resistance genes encode, not only well-defined members or regulators of the CUL4/DDB1/RBX1/CRBN E3 ubiquitin ligase complex, but also key components of signaling and transcriptional networks that have not been shown to modulate the response to cereblon modulators. Ablation of CYLD, NFKBIA, TRAF2, or TRAF3 induces hyperactivation of the canonical and/or noncanonical NF-κB pathways and subsequently diminishes CC-122-induced apoptosis in 5 of 6 DLBCL cell lines. Depletion of KCTD5, the substrate adaptor of the CUL3/RBX1/KCTD5 ubiquitin ligase complex, promotes the stabilization of its cognate substrate, GNG5, resulting in CC-122 resistance in HT, SU-DHL-4, and WSU-DLCL2. Furthermore, knockout of AMBRA1 renders resistance to CC-122 in SU-DHL-4 and U-2932, whereas knockout of RFX7 leads to resistance specifically in SU-DHL-4. The ubiquitous and cell line-specific mechanisms of CC-122 resistance in DLBCL cell lines revealed in this work pinpoint genetic alternations that are potentially associated with clinical resistance in patients and facilitate the development of biomarker strategies for patient stratification, which may improve clinical outcomes of patients with R/R DLBCL.

GATExplorer: genomic and transcriptomic explorer; mapping expression probes to gene loci, transcripts, exons and ncRNAs.

BACKGROUND: Genome-wide expression studies have developed exponentially in recent years as a result of extensive use of microarray technology. However, expression signals are typically calculated using the assignment of "probesets" to genes, without addressing the problem of "gene" definition or proper consideration of the location of the measuring probes in the context of the currently known genomes and transcriptomes. Moreover, as our knowledge of metazoan genomes improves, the number of both protein-coding and noncoding genes, as well as their associated isoforms, continues to increase. Consequently, there is a need for new databases that combine genomic and transcriptomic information and provide updated mapping of expression probes to current genomic annotations. RESULTS: GATExplorer (Genomic and Transcriptomic Explorer) is a database and web platform that integrates a gene loci browser with nucleotide level mappings of oligo probes from expression microarrays. It allows interactive exploration of gene loci, transcripts and exons of human, mouse and rat genomes, and shows the specific location of all mappable Affymetrix microarray probes and their respective expression levels in a broad set of biological samples. The web site allows visualization of probes in their genomic context together with any associated protein-coding or noncoding transcripts. In the case of all-exon arrays, this provides a means by which the expression of the individual exons within a gene can be compared, thereby facilitating the identification and analysis of alternatively spliced exons. The application integrates data from four major source databases: Ensembl, RNAdb, Affymetrix and GeneAtlas; and it provides the users with a series of files and packages (R CDFs) to analyze particular query expression datasets. The maps cover both the widely used Affymetrix GeneChip microarrays based on 3' expression (e.g. human HG U133 series) and the all-exon expression microarrays (Gene 1.0 and Exon 1.0). CONCLUSIONS: GATExplorer is an integrated database that combines genomic/transcriptomic visualization with nucleotide-level probe mapping. By considering expression at the nucleotide level rather than the gene level, it shows that the arrays detect expression signals from entities that most researchers do not contemplate or discriminate. This approach provides the means to undertake a higher resolution analysis of microarray data and potentially extract considerably more detailed and biologically accurate information from existing and future microarray experiments.

A high number of losses in 13q14 chromosome band is associated with a worse outcome and biological differences in patients with B-cell chronic lymphoid leukemia.

BACKGROUND: Among patients with B-cell chronic lymphoid leukemia, those with 13q14 deletion have a favorable outcome. However, whether the percentage of cells with 13q- influences the prognosis or the biological characteristics of this disease is unknown. We analyzed the clinico-biological characteristics and outcome of patients with B-cell chronic lymphoid leukemia with loss of 13q as the sole cytogenetic aberration. DESIGN AND METHODS: Three hundred and fifty patients with B-cell chronic lymphoid leukemia were studied. Clinical data were collected and fluorescence in situ hybridization and molecular studies were carried out. In addition, a gene expression profile was obtained by microarray-based analysis. RESULTS: In 109 out of the 350 cases (31.1%) loss of 13q was the sole cytogenetic aberration at diagnosis. In the subgroup of patients with 80% or more of cells with loss of 13q (18 cases), the overall survival was 56 months compared with not reached in the 91 cases in whom less than 80% of cells had loss of 13q (p< 0.0001). The variables included in the multivariate analysis for overall survival were the percentage of losses of 13q14 (p=0.001) and B symptoms (p=0.007). The time to first therapy in the group with 80% or more vs. less than 80% of losses was 38 months vs. 87 months, respectively (p=0.05). In the multivariate analysis the variables selected were unmutated status of IgV(H) (p=0.001) and a high level of beta(2)microglobulin (p=0.003). Interestingly, these differences regarding overall survival and time to first therapy were also present when other cut-offs were considered. The gene expression profile of patients with a high number of losses in 13q14 showed a high proliferation rate, downregulation of apoptosis-related genes, and dysregulation of genes related to mitochondrial functions. CONCLUSIONS: Patients with B-cell chronic lymphoid leukemia with a high number of losses in 13q14 as the sole cytogenetic aberration at diagnosis display different clinical and biological features: short overall survival and time to first therapy as well as more proliferation and less apoptosis. A quantification of the number of cells showing a genetic abnormality should, therefore, be included in the study of the prognostic factors of B-cell chronic lymphoid leukemia.

A calcium- and calpain-dependent pathway determines the response to lenalidomide in myelodysplastic syndromes.

Despite the high response rates of individuals with myelodysplastic syndrome (MDS) with deletion of chromosome 5q (del(5q)) to treatment with lenalidomide (LEN) and the recent identification of cereblon (CRBN) as the molecular target of LEN, the cellular mechanism by which LEN eliminates MDS clones remains elusive. Here we performed an RNA interference screen to delineate gene regulatory networks that mediate LEN responsiveness in an MDS cell line, MDSL. We identified GPR68, which encodes a G-protein-coupled receptor that has been implicated in calcium metabolism, as the top candidate gene for modulating sensitivity to LEN. LEN induced GPR68 expression via IKAROS family zinc finger 1 (IKZF1), resulting in increased cytosolic calcium levels and activation of a calcium-dependent calpain, CAPN1, which were requisite steps for induction of apoptosis in MDS cells and in acute myeloid leukemia (AML) cells. In contrast, deletion of GPR68 or inhibition of calcium and calpain activation suppressed LEN-induced cytotoxicity. Moreover, expression of calpastatin (CAST), an endogenous CAPN1 inhibitor that is encoded by a gene (CAST) deleted in del(5q) MDS, correlated with LEN responsiveness in patients with del(5q) MDS. Depletion of CAST restored responsiveness of LEN-resistant non-del(5q) MDS cells and AML cells, providing an explanation for the superior responses of patients with del(5q) MDS to LEN treatment. Our study describes a cellular mechanism by which LEN, acting through CRBN and IKZF1, has cytotoxic effects in MDS and AML that depend on a calcium- and calpain-dependent pathway.

Deregulation of genes related to iron and mitochondrial metabolism in refractory anemia with ring sideroblasts.

The presence of SF3B1 gene mutations is a hallmark of refractory anemia with ring sideroblasts (RARS). However, the mechanisms responsible for iron accumulation that characterize the Myelodysplastic Syndrome with ring sideroblasts (MDS-RS) are not completely understood. In order to gain insight in the molecular basis of MDS-RS, an integrative study of the expression and mutational status of genes related to iron and mitochondrial metabolism was carried out. A total of 231 low-risk MDS patients and 81 controls were studied. Gene expression analysis revealed that iron metabolism and mitochondrial function had the highest number of genes deregulated in RARS patients compared to controls and the refractory cytopenias with unilineage dysplasia (RCUD). Thus mitochondrial transporters SLC25 (SLC25A37 and SLC25A38) and ALAD genes were over-expressed in RARS. Moreover, significant differences were observed between patients with SF3B1 mutations and patients without the mutations. The deregulation of genes involved in iron and mitochondrial metabolism provides new insights in our knowledge of MDS-RS. New variants that could be involved in the pathogenesis of these diseases have been identified.

Protein-protein interaction networks: unraveling the wiring of molecular machines within the cell.

Mapping and understanding of the protein interaction networks with their key modules and hubs can provide deeper insights into the molecular machinery underlying complex phenotypes. In this article, we present the basic characteristics and definitions of protein networks, starting with a distinction of the different types of associations between proteins. We focus the review on protein-protein interactions (PPIs), a subset of associations defined as physical contacts between proteins that occur by selective molecular docking in a particular biological context. We present such definition as opposed to other types of protein associations derived from regulatory, genetic, structural or functional relations. To determine PPIs, a variety of binary and co-complex methods exist; however, not all the technologies provide the same information and data quality. A way of increasing confidence in a given protein interaction is to integrate orthogonal experimental evidences. The use of several complementary methods testing each single interaction assesses the accuracy of PPI data and tries to minimize the occurrence of false interactions. Following this approach there have been important efforts to unify primary databases of experimentally proven PPIs into integrated databases. These meta-databases provide a measure of the confidence of interactions based on the number of experimental proofs that report them. As a conclusion, we can state that integrated information allows the building of more reliable interaction networks. Identification of communities, cliques, modules and hubs by analysing the topological parameters and graph properties of the protein networks allows the discovery of central/critical nodes, which are candidates to regulate cellular flux and dynamics.

Prognostic Impact of del(17p) and del(22q) as assessed by interphase FISH in sporadic colorectal carcinomas.

BACKGROUND: Most sporadic colorectal cancer (sCRC) deaths are caused by metastatic dissemination of the primary tumor. New advances in genetic profiling of sCRC suggest that the primary tumor may contain a cell population with metastatic potential. Here we compare the cytogenetic profile of primary tumors from liver metastatic versus non-metastatic sCRC. METHODOLOGY/PRINCIPAL FINDINGS: We prospectively analyzed the frequency of numerical/structural abnormalities of chromosomes 1, 7, 8, 13, 14, 17, 18, 20, and 22 by iFISH in 58 sCRC patients: thirty-one non-metastatic (54%) vs. 27 metastatic (46%) disease. From a total of 18 probes, significant differences emerged only for the 17p11.2 and 22q11.2 chromosomal regions. Patients with liver metastatic sCRC showed an increased frequency of del(17p11.2) (10% vs. 67%;p<.001) and del(22q11.2) (0% vs. 22%;p = .02) versusnon-metastatic cases. Multivariate analysis of prognostic factors for overall survival (OS) showed that the only clinical and cytogenetic parameters that had an independent adverse impact on patient outcome were the presence of del(17p) with a 17p11.2 breakpoint and del(22q11.2). Based on these two cytogenetic variables, patients were classified into three groups: low- (no adverse features), intermediate- (one adverse feature) and high-risk (two adverse features)- with significantly different OS rates at 5-years (p<.001): 92%, 53% and 0%, respectively. CONCLUSIONS/SIGNIFICANCE: Our results unravel the potential implication of del(17p11.2) in sCRC patients with liver metastasis as this cytogenetic alteration appears to be intrinsically related to an increased metastatic potential and a poor outcome, providing additional prognostic information to that associated with other cytogenetic alterations such as del(22q11.2). Additional prospective studies in larger series of patients would be required to confirm the clinical utility of the new prognostic markers identified.

Functional analysis beyond enrichment: non-redundant reciprocal linkage of genes and biological terms.

Functional analysis of large sets of genes and proteins is becoming more and more necessary with the increase of experimental biomolecular data at omic-scale. Enrichment analysis is by far the most popular available methodology to derive functional implications of sets of cooperating genes. The problem with these techniques relies in the redundancy of resulting information, that in most cases generate lots of trivial results with high risk to mask the reality of key biological events. We present and describe a computational method, called GeneTerm Linker, that filters and links enriched output data identifying sets of associated genes and terms, producing metagroups of coherent biological significance. The method uses fuzzy reciprocal linkage between genes and terms to unravel their functional convergence and associations. The algorithm is tested with a small set of well known interacting proteins from yeast and with a large collection of reference sets from three heterogeneous resources: multiprotein complexes (CORUM), cellular pathways (SGD) and human diseases (OMIM). Statistical Precision, Recall and balanced F-score are calculated showing robust results, even when different levels of random noise are included in the test sets. Although we could not find an equivalent method, we present a comparative analysis with a widely used method that combines enrichment and functional annotation clustering. A web application to use the method here proposed is provided at http://gtlinker.cnb.csic.es.

Mapping of genetic abnormalities of primary tumours from metastatic CRC by high-resolution SNP arrays.

BACKGROUND: For years, the genetics of metastatic colorectal cancer (CRC) have been studied using a variety of techniques. However, most of the approaches employed so far have a relatively limited resolution which hampers detailed characterization of the common recurrent chromosomal breakpoints as well as the identification of small regions carrying genetic changes and the genes involved in them. METHODOLOGY/PRINCIPAL FINDINGS: Here we applied 500K SNP arrays to map the most common chromosomal lesions present at diagnosis in a series of 23 primary tumours from sporadic CRC patients who had developed liver metastasis. Overall our results confirm that the genetic profile of metastatic CRC is defined by imbalanced gains of chromosomes 7, 8q, 11q, 13q, 20q and X together with losses of the 1p, 8p, 17p and 18q chromosome regions. In addition, SNP-array studies allowed the identification of small (<1.3 Mb) and extensive/large (>1.5 Mb) altered DNA sequences, many of which contain cancer genes known to be involved in CRC and the metastatic process. Detailed characterization of the breakpoint regions for the altered chromosomes showed four recurrent breakpoints at chromosomes 1p12, 8p12, 17p11.2 and 20p12.1; interestingly, the most frequently observed recurrent chromosomal breakpoint was localized at 17p11.2 and systematically targeted the FAM27L gene, whose role in CRC deserves further investigations. CONCLUSIONS/SIGNIFICANCE: In summary, in the present study we provide a detailed map of the genetic abnormalities of primary tumours from metastatic CRC patients, which confirm and extend on previous observations as regards the identification of genes potentially involved in development of CRC and the metastatic process.

Human gene coexpression landscape: confident network derived from tissue transcriptomic profiles.

BACKGROUND: Analysis of gene expression data using genome-wide microarrays is a technique often used in genomic studies to find coexpression patterns and locate groups of co-transcribed genes. However, most studies done at global "omic" scale are not focused on human samples and when they correspond to human very often include heterogeneous datasets, mixing normal with disease-altered samples. Moreover, the technical noise present in genome-wide expression microarrays is another well reported problem that many times is not addressed with robust statistical methods, and the estimation of errors in the data is not provided. METHODOLOGY/PRINCIPAL FINDINGS: Human genome-wide expression data from a controlled set of normal-healthy tissues is used to build a confident human gene coexpression network avoiding both pathological and technical noise. To achieve this we describe a new method that combines several statistical and computational strategies: robust normalization and expression signal calculation; correlation coefficients obtained by parametric and non-parametric methods; random cross-validations; and estimation of the statistical accuracy and coverage of the data. All these methods provide a series of coexpression datasets where the level of error is measured and can be tuned. To define the errors, the rates of true positives are calculated by assignment to biological pathways. The results provide a confident human gene coexpression network that includes 3327 gene-nodes and 15841 coexpression-links and a comparative analysis shows good improvement over previously published datasets. Further functional analysis of a subset core network, validated by two independent methods, shows coherent biological modules that share common transcription factors. The network reveals a map of coexpression clusters organized in well defined functional constellations. Two major regions in this network correspond to genes involved in nuclear and mitochondrial metabolism and investigations on their functional assignment indicate that more than 60% are house-keeping and essential genes. The network displays new non-described gene associations and it allows the placement in a functional context of some unknown non-assigned genes based on their interactions with known gene families. CONCLUSIONS/SIGNIFICANCE: The identification of stable and reliable human gene to gene coexpression networks is essential to unravel the interactions and functional correlations between human genes at an omic scale. This work contributes to this aim, and we are making available for the scientific community the validated human gene coexpression networks obtained, to allow further analyses on the network or on some specific gene associations. The data are available free online at http://bioinfow.dep.usal.es/coexpression/.