Recurrent chromosome breakpoints at 6q22.31, leading to truncation and potential loss-of-function of the NKAIN2 gene, in Chinese prostate cancer patients were previously identified. In this study we investigated genomic, methylation and expression changes of NKAIN2 in a large number of prostate cancer samples and determined its functional role in prostate cancer cells. Fluorescence in situ hybridization analysis confirmed that NKAIN2 truncation is specific to Chinese while deletion of the gene is frequent in both Chinese and UK prostate cancers. Significantly reduced expression of NKAIN2 was also detected at both RNA and protein levels. Somatic mutations of NKAIN2 in prostate cancer samples exist but at very low frequency, suggesting that it is a putative tumor suppressor gene (TSG) with haploid insufficiency. Our functional studies showed that overexpression of NKAIN2 in prostate cancer cells inhibits cellular growth by promoting cell apoptosis, and decreasing cell migration and invasion. Conversely, knockdown of NKAIN2 promotes prostate cancer cell growth by inhibiting cell apoptosis, and increasing cell migration and invasion. These data imply that NKAIN2 is a novel TSG whose activity is commonly reduced in prostate cancer. It may restrain the disease development and progression by inducing apoptosis and suppressing cancer cell growth, migration and invasion. This study provides new insights into prostate carcinogenesis and opportunities for development of novel therapies for prostate cancer.

Melanoma patients treated with oncogenic BRAF inhibitors can develop cutaneous squamous cell carcinoma (cSCC) within weeks of treatment, driven by paradoxical RAS/RAF/MAPK pathway activation. Here we identify frequent TGFBR1 and TGFBR2 mutations in human vemurafenib-induced skin lesions and in sporadic cSCC. Functional analysis reveals these mutations ablate canonical TGFβ Smad signalling, which is localized to bulge stem cells in both normal human and murine skin. MAPK pathway hyperactivation (through Braf(V600E) or Kras(G12D) knockin) and TGFβ signalling ablation (through Tgfbr1 deletion) in LGR5(+ve) stem cells enables rapid cSCC development in the mouse. Mutation of Tp53 (which is commonly mutated in sporadic cSCC) coupled with Tgfbr1 deletion in LGR5(+ve) cells also results in cSCC development. These findings indicate that LGR5(+ve) stem cells may act as cells of origin for cSCC, and that RAS/RAF/MAPK pathway hyperactivation or Tp53 mutation, coupled with loss of TGFβ signalling, are driving events of skin tumorigenesis.

The BioMart Community Portal (www.biomart.org) is a community-driven effort to provide a unified interface to biomedical databases that are distributed worldwide. The portal provides access to numerous database projects supported by 30 scientific organizations. It includes over 800 different biological datasets spanning genomics, proteomics, model organisms, cancer data, ontology information and more. All resources available through the portal are independently administered and funded by their host organizations. The BioMart data federation technology provides a unified interface to all the available data. The latest version of the portal comes with many new databases that have been created by our ever-growing community. It also comes with better support and extensibility for data analysis and visualization tools. A new addition to our toolbox, the enrichment analysis tool is now accessible through graphical and web service interface. The BioMart community portal averages over one million requests per day. Building on this level of service and the wealth of information that has become available, the BioMart Community Portal has introduced a new, more scalable and cheaper alternative to the large data stores maintained by specialized organizations.

Amiselimod (MT-1303) is a selective sphingosine 1-phosphate 1 (S1P1 ) receptor modulator which is currently being developed for the treatment of various autoimmune diseases. Unlike some other S1P receptor modulators, amiselimod seemed to show a favourable cardiac safety profile in preclinical, phase I and II studies. The aim of the current study was to characterize the cardiac effects of amiselimod by directly comparing it with fingolimod and placebo.

Amiselimod, an oral selective sphingosine-1-phosphate 1 receptor modulator, suppressed disease activity dose-dependently without clinically relevant bradyarrhythmia in a 24-week phase 2, placebo-controlled study in relapsing-remitting multiple sclerosis.

Breast cancer is commonest cancer in women worldwide. Elucidation of underlying biology and molecular pathways is necessary for improving therapeutic options and clinical outcomes. Molecular alterations in breast cancer are complex and involve cross-talk between multiple signaling pathways. The aim of this study is to extract a unique mRNA fingerprint of breast cancer in Lebanese women using microarray technologies. Gene-expression profiles of 94 fresh breast tissue samples (84 cancerous/10 non-tumor adjacent samples) were analyzed using GeneChip Human Genome U133 Plus 2.0 arrays. Quantitative real-time PCR was employed to validate candidate genes. Differentially expressed genes between breast cancer and non-tumor tissues were screened. Significant differences in gene expression were established for COL11A1/COL10A1/MMP1/COL6A6/DLK1/S100P/CXCL11/SOX11/LEP/ADIPOQ/OXTR/FOSL1/ACSBG1 and C21orf37. Pathways/diseases representing these genes were retrieved and linked using PANTHER®/Pathway Studio®. Many of the deregulated genes are associated with extracellular matrix, inflammation, angiogenesis, metastasis, differentiation, cell proliferation and tumorigenesis. Characteristics of breast cancers in Lebanese were compared to those of women from Western populations to explain why breast cancer is more aggressive and presents a decade earlier in Lebanese victims. Delineating molecular mechanisms of breast cancer in Lebanese women led to key genes which could serve as potential biomarkers and/or novel drug targets for breast cancer.

Widespread mammographic screening programs and improved self-monitoring allow for breast cancer to be detected earlier than ever before. Breast-conserving surgery is a successful treatment for select women. However, up to 40% of women develop local recurrence after surgery despite apparently tumor-free margins. This suggests that morphologically normal breast may harbor early alterations that contribute to increased risk of cancer recurrence. We conducted a comprehensive transcriptomic and proteomic analysis to characterize 57 fresh-frozen tissues from breast cancers and matched histologically normal tissues resected proximal to (<2 cm) and distant from (5-10 cm) the primary tumor, using tissues from cosmetic reduction mammoplasties as baseline. Four distinct transcriptomic subtypes are identified within matched normal tissues: metabolic; immune; matrisome/epithelial-mesenchymal transition, and non-coding enriched. Key components of the subtypes are supported by proteomic and tissue composition analyses. We find that the metabolic subtype is associated with poor prognosis (p < 0.001, HR6.1). Examination of genes representing the metabolic signature identifies several genes able to prognosticate outcome from histologically normal tissues. A subset of these have been reported for their predictive ability in cancer but, to the best of our knowledge, these have not been reported altered in matched normal tissues. This study takes an important first step toward characterizing matched normal tissues resected at pre-defined margins from the primary tumor. Unlocking the predictive potential of unexcised tissue could prove key to driving the realization of personalized medicine for breast cancer patients, allowing for more biologically-driven analyses of tissue margins than morphology alone.

High-throughput technologies have produced a large amount of experimental and biomedical data creating an urgent need for comprehensive and automated mining approaches. To meet this need, we developed SMAC (SMart Automatic Classification method): a tool to extract, prioritise, integrate and analyse biomedical and molecular data according to user-defined terms. The robust ranking step performed on Medical Subject Headings (MeSH) ensures that papers are prioritised based on specific user requirements. SMAC then retrieves any related molecular data from the Gene Expression Omnibus and performs a wide range of bioinformatics analyses to extract biological insights. These features make SMAC a robust tool to explore the literature around any biomedical topic. SMAC can easily be customised/expanded and is distributed as a Docker container ( https://hub.docker.com/r/hfx320/smac ) ready-to-use on Windows, Mac and Linux OS. SMAC's functionalities have already been adapted and integrated into the Breast Cancer Now Tissue Bank bioinformatics platform and the Pancreatic Expression Database.

The DNA mismatch repair (MMR) pathway is responsible for the repair of base-base mismatches and insertion/deletion loops that arise during DNA replication. MMR deficiency is currently estimated to be present in 15-17% of colorectal cancer cases and 30% of endometrial cancers. MLH1 is one of the key proteins involved in the MMR pathway. Inhibition of a number of mitochondrial genes, including POLG and PINK1 can induce synthetic lethality in MLH1-deficient cells. Here we demonstrate for the first time that loss of MLH1 is associated with a deregulated mitochondrial metabolism, with reduced basal oxygen consumption rate and reduced spare respiratory capacity. Furthermore, MLH1-deficient cells display a significant reduction in activity of the respiratory chain Complex I. As a functional consequence of this perturbed mitochondrial metabolism, MLH1-deficient cells have a reduced anti-oxidant response and show increased sensitivity to reactive oxidative species (ROS)-inducing drugs. Taken together, our results provide evidence for an intrinsic mitochondrial dysfunction in MLH1-deficient cells and a requirement for MLH1 in the regulation of mitochondrial function.

Longitudinal patient biospecimens and data advance breast cancer research through enabling precision medicine approaches for identifying risk, early diagnosis, improved disease management and targeted therapy. Cancer biobanks must evolve to provide not only access to high-quality annotated biospecimens and rich associated data, but also the tools required to harness these data. We present the Breast Cancer Now Tissue Bank centre at the Barts Cancer Institute as an exemplar of a dynamic biobanking ecosystem that hosts and links longitudinal biospecimens and multimodal data including electronic health records, genomic and imaging data, offered alongside integrated data sharing and analytics tools. We demonstrate how such an ecosystem can inform precision medicine efforts in breast cancer research.

Pegylated arginine deiminase (ADI-PEG20; pegargiminase) depletes arginine and improves survival outcomes for patients with argininosuccinate synthetase 1 (ASS1)-deficient malignant pleural mesothelioma (MPM). Optimisation of ADI-PEG20-based therapy will require a deeper understanding of resistance mechanisms, including those mediated by the tumor microenvironment. Here, we sought to reverse translate increased tumoral macrophage infiltration in patients with ASS1-deficient MPM relapsing on pegargiminase therapy.

Breast cancer is the most common cancer in women worldwide. Elucidation of underlying biology and molecular pathways is necessary for improving therapeutic options and clinical outcomes. CLN3 protein (CLN3p), deficient in neurodegenerative CLN3 disease is anti-apoptotic, and defects in the CLN3 gene cause accelerated apoptosis of neurons in CLN3 disease and up-regulation of ceramide. Dysregulated apoptotic pathways are often implicated in the development of the oncogenic phenotype. Predictably, CLN3 mRNA expression and CLN3 protein were up-regulated in a number of human and murine breast cancer-cell lines. Here, we determine CLN3 expression in non-tumor vs. tumor samples from fresh and formalin-fixed/paraffin-embedded (FFPE) breast tissue and analyze the association between CLN3 overexpression and different clinicopathological characteristics of breast cancer patients. Additionally, gene expression of 28 enzymes involved in sphingolipid metabolism was determined. CLN3 mRNA is overexpressed in tumor vs. non-tumor breast tissue from FFPE and fresh samples, as well as in mouse MCF7 breast cancer compared to MCF10A normal cells. Of the clinicopathological characteristics of tumor grade, age, menopause status, estrogen receptor, progesterone receptor, and human epidermal growth factor receptor 2 (HER2), only absence of HER2 expression correlated with CLN3 overexpression. Sphingolipid genes for ceramide synthases 2 and 6 (CerS2; CerS6), delta(4)-desaturase sphingolipid 2 (DEGS2), and acidic sphingomyelinase (SMPD1) displayed higher expression levels in breast cancer vs. control tissue, whereas ceramide galactosyltransferase (UGT8) was underexpressed in breast cancer samples. CLN3 may be a novel molecular target for cancer drug discovery with the goal of modulation of ceramide pathways.

The human genome sequence defines our inherent biological potential; the realization of the biology encoded therein requires knowledge of the function of each gene. Currently, our knowledge in this area is still limited. Several lines of investigation have been used to elucidate the structure and function of the genes in the human genome. Even so, gene prediction remains a difficult task, as the varieties of transcripts of a gene may vary to a great extent. We thus performed an exhaustive integrative characterization of 41,118 full-length cDNAs that capture the gene transcripts as complete functional cassettes, providing an unequivocal report of structural and functional diversity at the gene level. Our international collaboration has validated 21,037 human gene candidates by analysis of high-quality full-length cDNA clones through curation using unified criteria. This led to the identification of 5,155 new gene candidates. It also manifested the most reliable way to control the quality of the cDNA clones. We have developed a human gene database, called the H-Invitational Database (H-InvDB; http://www.h-invitational.jp/). It provides the following: integrative annotation of human genes, description of gene structures, details of novel alternative splicing isoforms, non-protein-coding RNAs, functional domains, subcellular localizations, metabolic pathways, predictions of protein three-dimensional structure, mapping of known single nucleotide polymorphisms (SNPs), identification of polymorphic microsatellite repeats within human genes, and comparative results with mouse full-length cDNAs. The H-InvDB analysis has shown that up to 4% of the human genome sequence (National Center for Biotechnology Information build 34 assembly) may contain misassembled or missing regions. We found that 6.5% of the human gene candidates (1,377 loci) did not have a good protein-coding open reading frame, of which 296 loci are strong candidates for non-protein-coding RNA genes. In addition, among 72,027 uniquely mapped SNPs and insertions/deletions localized within human genes, 13,215 nonsynonymous SNPs, 315 nonsense SNPs, and 452 indels occurred in coding regions. Together with 25 polymorphic microsatellite repeats present in coding regions, they may alter protein structure, causing phenotypic effects or resulting in disease. The H-InvDB platform represents a substantial contribution to resources needed for the exploration of human biology and pathology.

We describe the Pancreatic Expression Database (PED), the first cancer database originally designed based on the BioMart infrastructure. The PED portal brings together multidimensional pancreatic cancer data from the literature including genomic, proteomic, miRNA and gene expression profiles. Based on the BioMart 0.7 framework, the database is easily integrated with other BioMart-compliant resources, such as Ensembl and Reactome, to give access to a wide range of annotations alongside detailed experimental conditions. This article is intended to give an overview of PED, describe its data content and work through examples of how to successfully mine and integrate pancreatic cancer data sets and other BioMart resources.

Despite the increasing wealth of available data, the structure of cancer transcriptional space remains largely unknown. Analysis of this space would provide novel insights into the complexity of cancer, assess relative implications in complex biological processes and responses, evaluate the effectiveness of cancer models and help uncover vital facets of cancer biology not apparent from current small-scale studies. We conducted a comprehensive analysis of pancreatic cancer-expression space by integrating data from otherwise disparate studies. We found (i) a clear separation of profiles based on experimental type, with patient tissue samples, cell lines and xenograft models forming distinct groups; (ii) three subgroups within the normal samples adjacent to cancer showing disruptions to biofunctions previously linked to cancer; and (iii) that ectopic subcutaneous xenografts and cell line models do not effectively represent changes occurring in pancreatic cancer. All findings are available from our online resource for independent interrogation. Currently, the most comprehensive analysis of pancreatic cancer to date, our study primarily serves to highlight limitations inherent with a lack of raw data availability, insufficient clinical/histopathological information and ambiguous data processing. It stresses the importance of a global-systems approach to assess and maximise findings from expression profiling of malignant and non-malignant diseases.

Several S100 proteins are up-regulated in pancreatic ductal adenocarcinoma (PDAC), the most significant being S100P. We previously reported on S100PBP, a binding partner of S100P, that shows no homology to any described protein and whose functions are completely unknown. To determine S100PBP expression across human tissues and organs, immunohistochemistry was performed using both multiorgan- and in-house-constructed pancreatic tissue microarrays. To establish S100PBP functions, cell lines with either stably overexpressed or silenced S100PBP were generated and investigated using Affymetrix gene expression arrays and complementary functional assays. We show that S100PBP is differentially expressed in various healthy and tumor specimens, which is both cancer- and tissue-type dependent. In healthy pancreas, S100PBP is expressed in the nuclear/perinuclear region of both exocrine and endocrine compartments. In early precancerous lesions, S100PBP is translocated to the cytoplasm, whereas in PDAC and metastatic lesions, its expression is significantly diminished. The most pronounced phenotypic change after manipulation of S100PBP expression was seen in adhesion; this was significantly reduced after S100PBP up-regulation and increased after S100PBP silencing. Up-regulation or silencing of S100PBP also led to a concomitant change in the levels of the protease cathepsin Z, the silencing of which significantly reduced PDAC cell adhesion. We further demonstrate that the interaction of cathepsin Z with arginine-glycine-aspartic acid-binding integrins, specifically αvβ5, mediates the changes seen in adhesion of PDAC cells.

BCCTBbp (http://bioinformatics.breastcancertissue bank.org) was initially developed as the data-mining portal of the Breast Cancer Campaign Tissue Bank (BCCTB), a vital resource of breast cancer tissue for researchers to support and promote cutting-edge research. BCCTBbp is dedicated to maximising research on patient tissues by initially storing genomics, methylomics, transcriptomics, proteomics and microRNA data that has been mined from the literature and linking to pathways and mechanisms involved in breast cancer. Currently, the portal holds 146 datasets comprising over 227,795 expression/genomic measurements from various breast tissues (e.g. normal, malignant or benign lesions), cell lines and body fluids. BCCTBbp can be used to build on breast cancer knowledge and maximise the value of existing research. By recording a large number of annotations on samples and studies, and linking to other databases, such as NCBI, Ensembl and Reactome, a wide variety of different investigations can be carried out. Additionally, BCCTBbp has a dedicated analytical layer allowing researchers to further analyse stored datasets. A future important role for BCCTBbp is to make available all data generated on BCCTB tissues thus building a valuable resource of information on the tissues in BCCTB that will save repetition of experiments and expand scientific knowledge.

With less than a 5% survival rate pancreatic adenocarcinoma (PDAC) is almost uniformly lethal. In order to make a significant impact on survival of patients with this malignancy, it is necessary to diagnose the disease early, when curative surgery is still possible. Detailed knowledge of the natural history of the disease and molecular events leading to its progression is therefore critical.

To identify novel effectors and processes regulated by PI3K pathway activation, we performed an unbiased phosphoproteomic screen comparing two common events of PI3K deregulation in cancer: oncogenic Pik3ca mutation (Pik3caH1047R) and deletion of Pten. Using mouse embryonic fibroblast (MEF) models that generate inducible, low-level pathway activation as observed in cancer, we quantified 7566 unique phosphopeptides from 3279 proteins. A number of proteins were found to be differentially-regulated by Pik3caH1047R and Pten loss, suggesting unique roles for these two events in processes such as vesicular trafficking, DNA damage repair and RNA splicing. We also identified novel PI3K effectors that were commonly-regulated, including putative AKT substrates. Validation of one of these hits, confirmed NT5C (5',3'-Nucleotidase, Cytosolic) as a novel AKT substrate, with an unexpected role in actin cytoskeleton regulation via an interaction with the ARP2/3 complex. This study has produced a comprehensive data resource and identified a new link between PI3K pathway activation and actin regulation.

Argininosuccinate synthase 1 (ASS1) is the rate-limiting enzyme for arginine biosynthesis. ASS1 expression is lost in a range of tumor types, including 50% of malignant pleural mesotheliomas. Starving ASS1-deficient cells of arginine with arginine blockers such as ADI-PEG20 can induce selective lethality and has shown great promise in the clinical setting. We have generated a model of ADI-PEG20 resistance in mesothelioma cells. This resistance is mediated through re-expression of ASS1 via demethylation of the ASS1 promoter. Through coordinated transcriptomic and metabolomic profiling, we have shown that ASS1-deficient cells have decreased levels of acetylated polyamine metabolites, together with a compensatory increase in the expression of polyamine biosynthetic enzymes. Upon arginine deprivation, polyamine metabolites are decreased in the ASS1-deficient cells and in plasma isolated from ASS1-deficient mesothelioma patients. We identify a synthetic lethal dependence between ASS1 deficiency and polyamine metabolism, which could potentially be exploited for the treatment of ASS1-negative cancers.