PDE3A Is a Highly Expressed Therapy Target in Myxoid Liposarcoma.

Liposarcomas (LPSs) are a heterogeneous group of malignancies that arise from adipose tissue. Although LPSs are among the most common soft-tissue sarcoma subtypes, precision medicine treatments are not currently available. To discover LPS-subtype-specific therapy targets, we investigated RNA sequenced transcriptomes of 131 clinical LPS tissue samples and compared the data with a transcriptome database that contained 20,218 samples from 95 healthy tissues and 106 cancerous tissue types. The identified genes were referred to the NCATS BioPlanet library with Enrichr to analyze upregulated signaling pathways. PDE3A protein expression was investigated with immunohistochemistry in 181 LPS samples, and PDE3A and SLFN12 mRNA expression with RT-qPCR were investigated in 63 LPS samples. Immunoblotting and cell viability assays were used to study LPS cell lines and their sensitivity to PDE3A modulators. We identified 97, 247, and 37 subtype-specific, highly expressed genes in dedifferentiated, myxoid, and pleomorphic LPS subtypes, respectively. Signaling pathway analysis revealed a highly activated hedgehog signaling pathway in dedifferentiated LPS, phospholipase c mediated cascade and insulin signaling in myxoid LPS, and pathways associated with cell proliferation in pleomorphic LPS. We discovered a strong association between high PDE3A expression and myxoid LPS, particularly in high-grade tumors. Moreover, myxoid LPS samples showed elevated expression levels of SLFN12 mRNA. In addition, PDE3A- and SLFN12-coexpressing LPS cell lines SA4 and GOT3 were sensitive to PDE3A modulators. Our results indicate that PDE3A modulators are promising drugs to treat myxoid LPS. Further studies are required to develop these drugs for clinical use.

Range of chromatin accessibility configurations are permissive of GABAergic fate acquisition in developing mouse brain.

In recent single-cell -omics studies, both the differential activity of transcription factors regulating cell fate determination and differential genome activation have been tested for utility as descriptors of cell types. Naturally, genome accessibility and gene expression are interlinked. To understand the variability in genomic feature activation in the GABAergic neurons of different spatial origins, we have mapped accessible chromatin regions and mRNA expression in single cells derived from the developing mouse central nervous system (CNS). We first defined a reference set of open chromatin regions for scATAC-seq read quantitation across samples, allowing comparison of chromatin accessibility between brain regions and cell types directly. Second, we integrated the scATAC-seq and scRNA-seq data to form a unified resource of transcriptome and chromatin accessibility landscape for the cell types in di- and telencephalon, midbrain and anterior hindbrain of E14.5 mouse embryo. Importantly, we implemented resolution optimization at the clustering, and automatized the cell typing step. We show high level of concordance between the cell clustering based on the chromatin accessibility and the transcriptome in analyzed neuronal lineages, indicating that both genome and transcriptome features can be used for cell type definition. Hierarchical clustering by the similarity in accessible chromatin reveals that the genomic feature activation correlates with neurotransmitter phenotype, selector gene expression, cell differentiation stage and neuromere origins.

Tumor-independent Detection of Inherited Mismatch Repair Deficiency for the Diagnosis of Lynch Syndrome with High Specificity and Sensitivity.

Lynch syndrome (LS) is the most common hereditary cancer syndrome. Early diagnosis improves prognosis and reduces health care costs, through existing cancer surveillance methods. The problem is finding and diagnosing the cancer predisposing genetic condition. The current workup involves a complex array of tests that combines family cancer history and clinical phenotypes with tumor characteristics and sequencing data, followed by a challenging task to interpret the found variant(s). On the basis of the knowledge that an inherited mismatch repair (MMR) deficiency is a hallmark of LS, we have developed and validated a functional MMR test, DiagMMR, that detects inherited MMR deficiency directly from healthy tissue without need of tumor and variant information. The validation included 119 skin biopsies collected from clinically pathogenic MMR variant carriers (MSH2, MSH6) and controls, and was followed by a small clinical pilot study. The repair reaction was performed on proteins extracted from primary fibroblasts and the interpretation was based on the MMR capability of the sample in relation to cutoff, which distinguishes MMR proficient (non-LS) from MMR deficient (LS) function. The results were compared with the reference standard (germline NGS). The test was shown to have exceptional specificity (100%) with high sensitivity (89%) and accuracy (97%). The ability to efficiently distinguish LS carriers from controls was further shown with a high area under the receiving operating characteristic (AUROC) value (0.97). This test offers an excellent tool for detecting inherited MMR deficiency linked to MSH2 or MSH6 and can be used alone or with conventional tests to recognize genetically predisposed individuals. Significance: Clinical validation of DiagMMR shows high accuracy in distinguishing individuals with hereditary MSH2 or MSH6 MMR deficiency (i.e., LS). The method presented overcomes challenges faced by the complexity of current methods and can be used alone or with conventional tests to improve the ability to recognize genetically predisposed individuals.

Transcriptomic analyses reveal three distinct molecular subgroups of Merkel cell carcinoma with differing prognoses.

Merkel cell carcinoma (MCC) is a cutaneous neuroendocrine malignancy with a poor prognosis and an unknown cell of origin. Proffered cells of origin include epithelial stem cells of the hair follicle or interfollicular epidermis, dermal stem cells and pro/pre- or pre-B cells. MCC has also been proposed to have more than one cell of origin and indeed to represent more than one type of carcinoma, currently grouped together due to phenotypic similarities. We explored the heterogeneous nature of MCC by studying the most variably expressed genes with the goal of identifying gene expression patterns that are either clinically relevant or have implications regarding the cell(s) of origin. We performed RNA sequencing on primary tumor samples from 102 patients and identified the top 200 most variably expressed genes. These genes and the tumor samples were hierarchically clustered based on their expression. The functions of three gene clusters exhibiting clearly divergent expression between samples were studied by cross-referencing the lists of genes with online databases. High expression of a gene cluster related to embryonic developmental processes and low expression of a gene cluster related to neuroendocrine processes distinguished Merkel cell polyomavirus (MCPyV)-negative tumors from MCPyV-positive tumors. Furthermore, two prognostically relevant subgroups of MCPyV-positive MCC were identified based on dichotomic expression of genes related to epidermal structures and processes. We identified three distinct molecular subgroups of MCC with prognostic relevance. We propose that the dichotomic expression of epidermis-related genes might reflect both an epidermal and a nonepidermal origin for MCPyV-positive MCC.

Activation of Oncogenic and Immune-Response Pathways Is Linked to Disease-Specific Survival in Merkel Cell Carcinoma.

BACKGROUND: Merkel cell carcinoma (MCC) is a rare but highly aggressive neuroendocrine carcinoma of the skin with a poor prognosis. Improving the prognosis of MCC by means of targeted therapies requires further understanding of the mechanisms that drive tumor progression. In this study, we aimed to identify the genes, processes, and pathways that play the most crucial roles in determining MCC outcomes. METHODS: We investigated transcriptomes generated by RNA sequencing of formalin-fixed paraffin-embedded tissue samples of 102 MCC patients and identified the genes that were upregulated among survivors and in patients who died from MCC. We subsequently cross-referenced these genes with online databases to investigate the functions and pathways they represent. We further investigated differential gene expression based on viral status in patients who died from MCC. RESULTS: We found several novel genes associated with MCC-specific survival. Genes upregulated in patients who died from MCC were most notably associated with angiogenesis and the PI3K-Akt and MAPK pathways; their expression predominantly had no association with viral status in patients who died from MCC. Genes upregulated among survivors were largely associated with antigen presentation and immune response. CONCLUSION: This outcome-based discrepancy in gene expression suggests that these pathways and processes likely play crucial roles in determining MCC outcomes.

Gata2, Nkx2-2 and Skor2 form a transcription factor network regulating development of a midbrain GABAergic neuron subtype with characteristics of REM-sleep regulatory neurons.

The midbrain reticular formation (MRF) is a mosaic of diverse GABAergic and glutamatergic neurons that have been associated with a variety of functions, including sleep regulation. However, the molecular characteristics and development of MRF neurons are poorly understood. As the transcription factor, Gata2 is required for the development of all GABAergic neurons derived from the embryonic mouse midbrain, we hypothesized that the genes expressed downstream of Gata2 could contribute to the diversification of GABAergic neuron subtypes in this brain region. Here, we show that Gata2 is required for the expression of several GABAergic lineage-specific transcription factors, including Nkx2-2 and Skor2, which are co-expressed in a restricted group of post-mitotic GABAergic precursors in the MRF. Both Gata2 and Nkx2-2 function is required for Skor2 expression in GABAergic precursors. In the adult mouse and rat midbrain, Nkx2-2-and Skor2-expressing GABAergic neurons locate at the boundary of the ventrolateral periaqueductal gray and the MRF, an area containing REM-off neurons regulating REM sleep. In addition to the characteristic localization, Skor2+ cells increase their activity upon REM-sleep inhibition, send projections to the dorsolateral pons, a region associated with sleep control, and are responsive to orexins, consistent with the known properties of midbrain REM-off neurons.

A novel transcript, VNN1-AB, as a biomarker for colorectal cancer.

Colorectal cancer is a global health challenge with high incidence rate and mortality. The patients' prognosis is strongly associated with disease stage and currently there is a need for improved prognostic and predictive biomarkers. In this study, novel colorectal cancer-specific transcript structures were nominated from whole transcriptome sequencing of seven colorectal cancer cell lines, two primary colorectal carcinomas with corresponding normal colonic mucosa and 16 normal tissues. The nominated transcripts were combined with gene level outlier expression analyses in a cohort of 505 colorectal cancers to identify biomarkers with capacity to stratify colorectal cancer subgroups. The transcriptome sequencing data and outlier expression analysis revealed 11 novel colorectal cancer-specific exon-exon junctions, of which 3 were located in the gene VNN1. The junctions within VNN1 were further characterized using rapid amplification of cDNA ends (RACE) and the prevalence of the subsequently characterized novel transcript, VNN1-AB, was investigated by real-time RT-PCR in 291 samples of miscellaneous origins. VNN1-AB was not present in any of the 43 normal colorectal tissue samples investigated, but in 5 of the 6 polyps, and 102 of the 136 (75%) colorectal cancers. We have identified a novel transcript of the VNN1 gene, with an organ-confined complete specificity for colorectal neoplasia.

Biclustering methods: biological relevance and application in gene expression analysis.

DNA microarray technologies are used extensively to profile the expression levels of thousands of genes under various conditions, yielding extremely large data-matrices. Thus, analyzing this information and extracting biologically relevant knowledge becomes a considerable challenge. A classical approach for tackling this challenge is to use clustering (also known as one-way clustering) methods where genes (or respectively samples) are grouped together based on the similarity of their expression profiles across the set of all samples (or respectively genes). An alternative approach is to develop biclustering methods to identify local patterns in the data. These methods extract subgroups of genes that are co-expressed across only a subset of samples and may feature important biological or medical implications. In this study we evaluate 13 biclustering and 2 clustering (k-means and hierarchical) methods. We use several approaches to compare their performance on two real gene expression data sets. For this purpose we apply four evaluation measures in our analysis: (1) we examine how well the considered (bi)clustering methods differentiate various sample types; (2) we evaluate how well the groups of genes discovered by the (bi)clustering methods are annotated with similar Gene Ontology categories; (3) we evaluate the capability of the methods to differentiate genes that are known to be specific to the particular sample types we study and (4) we compare the running time of the algorithms. In the end, we conclude that as long as the samples are well defined and annotated, the contamination of the samples is limited, and the samples are well replicated, biclustering methods such as Plaid and SAMBA are useful for discovering relevant subsets of genes and samples.

Extracellular membrane vesicles from umbilical cord blood-derived MSC protect against ischemic acute kidney injury, a feature that is lost after inflammatory conditioning.

BACKGROUND: Mesenchymal stromal cells (MSC) are shown to have a great therapeutic potential in many immunological disorders. Currently the therapeutic effect of MSCs is considered to be mediated via paracrine interactions with immune cells. Umbilical cord blood is an attractive but still less studied source of MSCs. We investigated the production of extracellular membrane vesicles (MVs) from human umbilical cord blood derived MSCs (hUCBMSC) in the presence (MVstim) or absence (MVctrl) of inflammatory stimulus. METHODS: hUCBMSCs were cultured in serum free media with or without IFN-γ and MVs were collected from conditioned media by ultracentrifugation. The protein content of MVs were analyzed by mass spectrometry. Hypoxia induced acute kidney injury rat model was used to analyze the in vivo therapeutic potential of MVs and T-cell proliferation and induction of regulatory T cells were analyzed by co-culture assays. RESULTS: Both MVstim and MVctrl showed similar T-cell modulation activity in vitro, but only MVctrls were able to protect rat kidneys from reperfusion injury in vivo. To clarify this difference in functionality we made a comparative mass spectrometric analysis of the MV protein contents. The IFN-γ stimulation induced dramatic changes in the protein content of the MVs. Complement factors (C3, C4A, C5) and lipid binding proteins (i.e apolipoproteins) were only found in the MVctrls, whereas the MVstim contained tetraspanins (CD9, CD63, CD81) and more complete proteasome complex accompanied with MHCI. We further discovered that differently produced MV pools contained specific Rab proteins suggesting that same cells, depending on external signals, produce vesicles originating from different intracellular locations. CONCLUSIONS: We demonstrate by both in vitro and in vivo models accompanied with a detailed analysis of molecular characteristics that inflammatory conditioning of MSCs influence on the protein content and functional properties of MVs revealing the complexity of the MSC paracrine regulation.

Facilitates chromatin transcription complex is an "accelerator" of tumor transformation and potential marker and target of aggressive cancers.

The facilitates chromatin transcription (FACT) complex is involved in chromatin remodeling during transcription, replication, and DNA repair. FACT was previously considered to be ubiquitously expressed and not associated with any disease. However, we discovered that FACT is the target of a class of anticancer compounds and is not expressed in normal cells of adult mammalian tissues, except for undifferentiated and stem-like cells. Here, we show that FACT expression is strongly associated with poorly differentiated aggressive cancers with low overall survival. In addition, FACT was found to be upregulated during in vitro transformation and to be necessary, but not sufficient, for driving transformation. FACT also promoted survival and growth of established tumor cells. Genome-wide mapping of chromatin-bound FACT indicated that FACT's role in cancer most likely involves selective chromatin remodeling of genes that stimulate proliferation, inhibit cell death and differentiation, and regulate cellular stress responses.

Characterization of non-specific cytotoxic cell receptor protein 1: a new member of the lectin-type subfamily of F-box proteins.

Our previous microarray study showed that the non-specific cytotoxic cell receptor protein 1 (Nccrp1) transcript is significantly upregulated in the gastric mucosa of carbonic anhydrase IX (CA IX)-deficient (Car9(-/-)) mice. In this paper, we aimed to characterize human NCCRP1 and to elucidate its relationship to CA IX. Recombinant NCCRP1 protein was expressed in Escherichia coli, and a novel polyclonal antiserum was raised against the purified full-length protein. Immunocytochemistry showed that NCCRP1 is expressed intracellularly, even though it has previously been described as a transmembrane protein. Using bioinformatic analyses, we identified orthologs of NCCRP1 in 35 vertebrate genomes, and up to five paralogs per genome. These paralogs are FBXO genes whose protein products are components of the E3 ubiquitin ligase complexes. NCCRP1 proteins have no signal peptides or transmembrane domains. NCCRP1 has mainly been studied in fish and was thought to be responsible for the cytolytic function of nonspecific cytotoxic cells (NCCs). Our analyses showed that in humans, NCCRP1 mRNA is expressed in tissues containing squamous epithelium, whereas it shows a more ubiquitous tissue expression pattern in mice. Neither human nor mouse NCCRP1 expression is specific to immune tissues. Silencing CA9 using siRNAs did not affect NCCRP1 levels, indicating that its expression is not directly regulated by CA9. Interestingly, silencing NCCRP1 caused a statistically significant decrease in the growth of HeLa cells. These studies provide ample evidence that the current name, "non-specific cytotoxic cell receptor protein 1," is not appropriate. We therefore propose that the gene name be changed to FBXO50.

Classification of unknown primary tumors with a data-driven method based on a large microarray reference database.

We present a new method to analyze cancer of unknown primary origin (CUP) samples. Our method achieves good results with classification accuracy (88% leave-one-out cross validation for primary tumors from 56 categories, 78% for CUP samples), and can also be used to study CUP samples on a gene-by-gene basis. It is not tied to any a priori defined gene set as many previous methods, and is adaptable to emerging new information.

LGI2 truncation causes a remitting focal epilepsy in dogs.

One quadrillion synapses are laid in the first two years of postnatal construction of the human brain, which are then pruned until age 10 to 500 trillion synapses composing the final network. Genetic epilepsies are the most common neurological diseases with onset during pruning, affecting 0.5% of 2-10-year-old children, and these epilepsies are often characterized by spontaneous remission. We previously described a remitting epilepsy in the Lagotto romagnolo canine breed. Here, we identify the gene defect and affected neurochemical pathway. We reconstructed a large Lagotto pedigree of around 34 affected animals. Using genome-wide association in 11 discordant sib-pairs from this pedigree, we mapped the disease locus to a 1.7 Mb region of homozygosity in chromosome 3 where we identified a protein-truncating mutation in the Lgi2 gene, a homologue of the human epilepsy gene LGI1. We show that LGI2, like LGI1, is neuronally secreted and acts on metalloproteinase-lacking members of the ADAM family of neuronal receptors, which function in synapse remodeling, and that LGI2 truncation, like LGI1 truncations, prevents secretion and ADAM interaction. The resulting epilepsy onsets at around seven weeks (equivalent to human two years), and remits by four months (human eight years), versus onset after age eight in the majority of human patients with LGI1 mutations. Finally, we show that Lgi2 is expressed highly in the immediate post-natal period until halfway through pruning, unlike Lgi1, which is expressed in the latter part of pruning and beyond. LGI2 acts at least in part through the same ADAM receptors as LGI1, but earlier, ensuring electrical stability (absence of epilepsy) during pruning years, preceding this same function performed by LGI1 in later years. LGI2 should be considered a candidate gene for common remitting childhood epilepsies, and LGI2-to-LGI1 transition for mechanisms of childhood epilepsy remission.

SATB2 in combination with cytokeratin 20 identifies over 95% of all colorectal carcinomas.

The special AT-rich sequence-binding protein 2 (SATB2), a nuclear matrix-associated transcription factor and epigenetic regulator, was identified as a tissue type-specific protein when screening protein expression patterns in human normal and cancer tissues using an antibody-based proteomics approach. In this respect, the SATB2 protein shows a selective pattern of expression and, within cells of epithelial lineages, SATB2 expression is restricted to glandular cells lining the lower gastrointestinal tract. The expression of SATB2 protein is primarily preserved in cancer cells of colorectal origin, indicating that SATB2 could function as a clinically useful diagnostic marker to distinguish colorectal cancer (CRC) from other types of cancer. The aim of this study was to further explore and validate the specific expression pattern of SATB2 as a clinical biomarker and to compare SATB2 with the well-known cytokeratin 20 (CK20). Immunohistochemistry was used to analyze the extent of SATB2 expression in tissue microarrays with tumors from 9 independent cohorts of patients with primary and metastatic CRCs (n=1882). Our results show that SATB2 is a sensitive and highly specific marker for CRC with distinct positivity in 85% of all CRCs, and that SATB2 and/or CK20 was positive in 97% of CRCs. In conclusion, the specific expression of SATB2 in a large majority of CRCs suggests that SATB2 can be used as an important complementary tool for the differential diagnosis of carcinoma of unknown primary origin.

Alignment of gene expression profiles from test samples against a reference database: New method for context-specific interpretation of microarray data.

BACKGROUND: Gene expression microarray data have been organized and made available as public databases, but the utilization of such highly heterogeneous reference datasets in the interpretation of data from individual test samples is not as developed as e.g. in the field of nucleotide sequence comparisons. We have created a rapid and powerful approach for the alignment of microarray gene expression profiles (AGEP) from test samples with those contained in a large annotated public reference database and demonstrate here how this can facilitate interpretation of microarray data from individual samples. METHODS: AGEP is based on the calculation of kernel density distributions for the levels of expression of each gene in each reference tissue type and provides a quantitation of the similarity between the test sample and the reference tissue types as well as the identity of the typical and atypical genes in each comparison. As a reference database, we used 1654 samples from 44 normal tissues (extracted from the Genesapiens database). RESULTS: Using leave-one-out validation, AGEP correctly defined the tissue of origin for 1521 (93.6%) of all the 1654 samples in the original database. Independent validation of 195 external normal tissue samples resulted in 87% accuracy for the exact tissue type and 97% accuracy with related tissue types. AGEP analysis of 10 Duchenne muscular dystrophy (DMD) samples provided quantitative description of the key pathogenetic events, such as the extent of inflammation, in individual samples and pinpointed tissue-specific genes whose expression changed (SAMD4A) in DMD. AGEP analysis of microarray data from adipocytic differentiation of mesenchymal stem cells and from normal myeloid cell types and leukemias provided quantitative characterization of the transcriptomic changes during normal and abnormal cell differentiation. CONCLUSIONS: The AGEP method is a widely applicable method for the rapid comprehensive interpretation of microarray data, as proven here by the definition of tissue- and disease-specific changes in gene expression as well as during cellular differentiation. The capability to quantitatively compare data from individual samples against a large-scale annotated reference database represents a widely applicable paradigm for the analysis of all types of high-throughput data. AGEP enables systematic and quantitative comparison of gene expression data from test samples against a comprehensive collection of different cell/tissue types previously studied by the entire research community.

GTI: a novel algorithm for identifying outlier gene expression profiles from integrated microarray datasets.

BACKGROUND: Meta-analysis of gene expression microarray datasets presents significant challenges for statistical analysis. We developed and validated a new bioinformatic method for the identification of genes upregulated in subsets of samples of a given tumour type ('outlier genes'), a hallmark of potential oncogenes. METHODOLOGY: A new statistical method (the gene tissue index, GTI) was developed by modifying and adapting algorithms originally developed for statistical problems in economics. We compared the potential of the GTI to detect outlier genes in meta-datasets with four previously defined statistical methods, COPA, the OS statistic, the t-test and ORT, using simulated data. We demonstrated that the GTI performed equally well to existing methods in a single study simulation. Next, we evaluated the performance of the GTI in the analysis of combined Affymetrix gene expression data from several published studies covering 392 normal samples of tissue from the central nervous system, 74 astrocytomas, and 353 glioblastomas. According to the results, the GTI was better able than most of the previous methods to identify known oncogenic outlier genes. In addition, the GTI identified 29 novel outlier genes in glioblastomas, including TYMS and CDKN2A. The over-expression of these genes was validated in vivo by immunohistochemical staining data from clinical glioblastoma samples. Immunohistochemical data were available for 65% (19 of 29) of these genes, and 17 of these 19 genes (90%) showed a typical outlier staining pattern. Furthermore, raltitrexed, a specific inhibitor of TYMS used in the therapy of tumour types other than glioblastoma, also effectively blocked cell proliferation in glioblastoma cell lines, thus highlighting this outlier gene candidate as a potential therapeutic target. CONCLUSIONS/SIGNIFICANCE: Taken together, these results support the GTI as a novel approach to identify potential oncogene outliers and drug targets. The algorithm is implemented in an R package (Text S1).

Analysis of kinase gene expression patterns across 5681 human tissue samples reveals functional genomic taxonomy of the kinome.

Kinases play key roles in cell signaling and represent major targets for drug development, but the regulation of their activation and their associations with health and disease have not been systematically analyzed. Here, we carried out a bioinformatic analysis of the expression levels of 459 human kinase genes in 5681 samples consisting of 44 healthy and 55 malignant human tissues. Defining the tissues where the kinase genes were transcriptionally active led to a functional genomic taxonomy of the kinome and a classification of human tissues and disease types based on the similarity of their kinome gene expression. The co-expression network around each of the kinase genes was defined in order to determine the functional context, i.e. the biological processes that were active in the cells and tissues where the kinase gene was expressed. Strong associations for individual kinases were found for mitosis (69 genes, including AURKA and BUB1), cell cycle control (73 genes, including PLK1 and AURKB), DNA repair (49 genes, including CHEK1 and ATR), immune response (72 genes, including MATK), neuronal (131 genes, including PRKCE) and muscular (72 genes, including MYLK2) functions. We then analyzed which kinase genes gain or lose transcriptional activity in the development of prostate and lung cancers and elucidated the functional associations of individual cancer associated kinase genes. In summary, we report here a systematic classification of kinases based on the bioinformatic analysis of their expression in human tissues and diseases, as well as grouping of tissues and tumor types according to the similarity of their kinome transcription.

Integrative functional genomics analysis of sustained polyploidy phenotypes in breast cancer cells identifies an oncogenic profile for GINS2.

Aneuploidy is among the most obvious differences between normal and cancer cells. However, mechanisms contributing to development and maintenance of aneuploid cell growth are diverse and incompletely understood. Functional genomics analyses have shown that aneuploidy in cancer cells is correlated with diffuse gene expression signatures and aneuploidy can arise by a variety of mechanisms, including cytokinesis failures, DNA endoreplication, and possibly through polyploid intermediate states. To identify molecular processes contributing to development of aneuploidy, we used a cell spot microarray technique to identify genes inducing polyploidy and/or allowing maintenance of polyploid cell growth in breast cancer cells. Of 5760 human genes screened, 177 were found to induce severe DNA content alterations on prolonged transient silencing. Association with response to DNA damage stimulus and DNA repair was found to be the most enriched cellular processes among the candidate genes. Functional validation analysis of these genes highlighted GINS2 as the highest ranking candidate inducing polyploidy, accumulation of endogenous DNA damage, and impairing cell proliferation on inhibition. The cell growth inhibition and induction of polyploidy by suppression of GINS2 was verified in a panel of breast cancer cell lines. Bioinformatic analysis of published gene expression and DNA copy number studies of clinical breast tumors suggested GINS2 to be associated with the aggressive characteristics of a subgroup of breast cancers in vivo. In addition, nuclear GINS2 protein levels distinguished actively proliferating cancer cells suggesting potential use of GINS2 staining as a biomarker of cell proliferation as well as a potential therapeutic target.

Fibroblast growth factor receptor 4 regulates tumor invasion by coupling fibroblast growth factor signaling to extracellular matrix degradation.

Aberrant expression and polymorphism of fibroblast growth factor receptor 4 (FGFR4) has been linked to tumor progression and anticancer drug resistance. We describe here a novel mechanism of tumor progression by matrix degradation involving epithelial-to-mesenchymal transition in response to membrane-type 1 matrix metalloproteinase (MT1-MMP, MMP-14) induction at the edge of tumors expressing the FGFR4-R388 risk variant. Both FGFR4 and MT1-MMP were upregulated in tissue biopsies from several human cancer types including breast adenocarcinomas, where they were partially coexpressed at the tumor/stroma border and tumor invasion front. The strongest overall coexpression was found in prostate carcinoma. Studies with cultured prostate carcinoma cell lines showed that the FGFR4-R388 variant, which has previously been associated with poor cancer prognosis, increased MT1-MMP-dependent collagen invasion. In this experimental model, knockdown of FGFR4-R388 or MT1-MMP by RNA interference blocked tumor cell invasion and growth in collagen. This was coupled with impaired phosphorylation of FGFR substrate 2 and Src, upregulation of E-cadherin, and suppression of cadherin-11 and N-cadherin. These in vitro results were substantiated by reduced MT1-MMP content and in vivo growth of prostate carcinoma cells after the FGFR4-R388 gene silencing. In contrast, knockdown of the alternative FGFR4-G388 allele enhanced MT1-MMP and invasive tumor cell growth in vivo and within three-dimensional collagen. These results will help to explain the reported association of the FGFR4-R388 variant with the progression and poor prognosis of certain types of tumors.

Array-based gene expression, CGH and tissue data defines a 12q24 gain in neuroblastic tumors with prognostic implication.

BACKGROUND: Neuroblastoma has successfully served as a model system for the identification of neuroectoderm-derived oncogenes. However, in spite of various efforts, only a few clinically useful prognostic markers have been found. Here, we present a framework, which integrates DNA, RNA and tissue data to identify and prioritize genetic events that represent clinically relevant new therapeutic targets and prognostic biomarkers for neuroblastoma. METHODS: A single-gene resolution aCGH profiling was integrated with microarray-based gene expression profiling data to distinguish genetic copy number alterations that were strongly associated with transcriptional changes in two neuroblastoma cell lines. FISH analysis using a hotspot tumor tissue microarray of 37 paraffin-embedded neuroblastoma samples and in silico data mining for gene expression information obtained from previously published studies including up to 445 healthy nervous system samples and 123 neuroblastoma samples were used to evaluate the clinical significance and transcriptional consequences of the detected alterations and to identify subsequently activated gene(s). RESULTS: In addition to the anticipated high-level amplification and subsequent overexpression of MYCN, MEIS1, CDK4 and MDM2 oncogenes, the aCGH analysis revealed numerous other genetic alterations, including microamplifications at 2p and 12q24.11. Most interestingly, we identified and investigated the clinical relevance of a previously poorly characterized amplicon at 12q24.31. FISH analysis showed low-level gain of 12q24.31 in 14 of 33 (42%) neuroblastomas. Patients with the low-level gain had an intermediate prognosis in comparison to patients with MYCN amplification (poor prognosis) and to those with no MYCN amplification or 12q24.31 gain (good prognosis) (P = 0.001). Using the in silico data mining approach, we identified elevated expression of five genes located at the 12q24.31 amplicon in neuroblastoma (DIABLO, ZCCHC8, RSRC2, KNTC1 and MPHOSPH9). Among these, DIABLO showed the strongest activation suggesting a putative role in neuroblastoma progression. CONCLUSIONS: The presented systematic and rapid framework, which integrates aCGH, gene expression and tissue data to obtain novel targets and biomarkers for cancer, identified a low-level gain of the 12q24.31 as a potential new biomarker for neuroblastoma progression. Furthermore, results of in silico data mining suggest a new neuroblastoma target gene, DIABLO, within this region, whose functional and therapeutic role remains to be elucidated in follow-up studies.