canSAR: an updated cancer research and drug discovery knowledgebase.

canSAR (http://cansar.icr.ac.uk) is a publicly available, multidisciplinary, cancer-focused knowledgebase developed to support cancer translational research and drug discovery. canSAR integrates genomic, protein, pharmacological, drug and chemical data with structural biology, protein networks and druggability data. canSAR is widely used to rapidly access information and help interpret experimental data in a translational and drug discovery context. Here we describe major enhancements to canSAR including new data, improved search and browsing capabilities, new disease and cancer cell line summaries and new and enhanced batch analysis tools

Fishes of the Cocos (Keeling) Islands: new records, community composition and biogeographic significance

The Cocos (Keeling) Islands comprise the most isolated oceanic atoll in the tropical Indian Ocean and are situated 1000 km south-west of Indonesia. The remoteness of the islands has shaped the composition of marine communities but also limited scientific research. This study summarises field research on the marine fishes of the Cocos (Keeling) Islands over the last 14 years (2001–2014). Sixty-seven new records (from 28 families) are described and raise the total number of known fishes to 602 species from 84 families. New records span a variety of body sizes (3 cm TL Gobiodon unicolor to 500 cm TL Rhincodon typus), were observed in all major habitats,and found at both the Southern Atoll and at North Keeling Island. Notable new records include first records for the families Alopiidae, Coryphaenidae, Eleotridae, Gempylidae, Istiophoridae, Molidae, Polymixiidae, Rhincodontidae, Sillaginidae and Xiphiidae. Sampling from pelagic and deepwater (60–300 m) reef environments significantly increased the number of species described from these habitats. New records include species that have dispersed more than 2500 km (Centropyge acanthops) and dispersal ability appears to explain the lack of syngnathids and the high representation of acanthurids and holocentrids in the community. Some of the Indian Ocean species that have colonised the Cocos (Keeling) Islands now co-occur with their Pacific Ocean sister species, increasing the potential for hybridisation. Although the fish community of the Cocos (Keeling) Island resembles that of the Indo-West Pacific, the isolation and co-occurrence of Indian and Pacific Ocean species distinguishes it from all other locations

Checklist and new records of Christmas Island fishes: the influence of isolation, biogeography and habitat availability on species abundance and community composition

Christmas Island (Indian Ocean) is an oceanic high island that is situated 300 km southwest of Java, Indonesia. From 2010 to 2014, the fish community of Christmas Island was surveyed using underwater visual surveys for shallow water (0–60 m) fishes, and line fishing (bottom fishing and trolling) for deepwater (60–300 m) and pelagic fishes. Forty-seven new records (from 22 families) were identified, thereby increasing the total number of fishes described from Christmas Island to 681 (from 91 families). Notable new records include the first records for the families Alopiidae, Anomalopidae, Muraenesocidae, Tetrarogidae and Trichonotidae, and the first reports of Pacific Ocean species Plectranthias yamakawai, and Polylepion russelli in the Indian Ocean. The ten most species-rich families accounted for 58% of the community and included: Labridae (13%), Pomacentridae (8%), Epinephelidae (6%), Acanthuridae (5%), Chaetodontidae (5%), Muraenidae (5%), Gobiidae (5%), Blenniidae (4%), Apogonidae (4%) and Scorpaenidae (3%). The majority (89%) of species inhabit shallow coral reefs, with deep reefs (60–300 m) and pelagic waters only accounting for 7% and 2% of fish community. Approximately 76% of thefishes are widespread Indo-Pacific species, 12% are Pacific Ocean species, 5% are circumtropical, 4% are Indian Ocean species and approximately 1% are endemic. Abundance surveys revealed that endemic species, and species at the edge of their geographic range, do not conform to terrestrial-based predictions of low abundance. The structure and composition of the Christmas Island fish community is influenced by three main factors. Firstly, the isolation of the island means that fishes with poor dispersal abilities (e.g., syngnathids) are underrepresented. Secondly, thebiogeographic position of the island results in a unique mixing of Indian and Pacific Ocean species. Thirdly, the lack of lagoonal habitats means that fishes that use these habitats (e.g., ophichthids, lethrinids, epinephelids) are underrepresented or have low abundance

canSAR: update to the cancer translational research and drug discovery knowledgebase.

canSAR (https://cansar.ai) is the largest public cancer drug discovery and translational research knowledgebase. Now hosted in its new home at MD Anderson Cancer Center, canSAR integrates billions of experimental measurements from across molecular profiling, pharmacology, chemistry, structural and systems biology. Moreover, canSAR applies a unique suite of machine learning algorithms designed to inform drug discovery. Here, we describe the latest updates to the knowledgebase, including a focus on significant novel data. These include canSAR's ligandability assessment of AlphaFold; mapping of fragment-based screening data; and new chemical bioactivity data for novel targets. We also describe enhancements to the data and interface

canSAR: update to the cancer translational research and drug discovery knowledgebase.

canSAR (http://cansar.icr.ac.uk) is a public, freely available, integrative translational research and drug discovery knowlegebase. canSAR informs researchers to help solve key bottlenecks in cancer translation and drug discovery. It integrates genomic, protein, pharmacological, drug and chemical data with structural biology, protein networks and unique, comprehensive and orthogonal 'druggability' assessments. canSAR is widely used internationally by academia and industry. Here we describe major enhancements to canSAR including new and expanded data. We also describe the first components of canSARblack-an advanced, responsive, multi-device compatible redesign of canSAR with a question-led interface

Genomic distance entrained clustering and regression modelling highlights interacting genomic regions contributing to proliferation in breast cancer

<p>Abstract</p> <p>Background</p> <p>Genomic copy number changes and regional alterations in epigenetic states have been linked to grade in breast cancer. However, the relative contribution of specific alterations to the pathology of different breast cancer subtypes remains unclear. The heterogeneity and interplay of genomic and epigenetic variations means that large datasets and statistical data mining methods are required to uncover recurrent patterns that are likely to be important in cancer progression.</p> <p>Results</p> <p>We employed ridge regression to model the relationship between regional changes in gene expression and proliferation. Regional features were extracted from tumour gene expression data using a novel clustering method, called genomic distance entrained agglomerative (GDEC) clustering. Using gene expression data in this way provides a simple means of integrating the phenotypic effects of both copy number aberrations and alterations in chromatin state. We show that regional metagenes derived from GDEC clustering are representative of recurrent regions of epigenetic regulation or copy number aberrations in breast cancer. Furthermore, detected patterns of genomic alterations are conserved across independent oestrogen receptor positive breast cancer datasets. Sequential competitive metagene selection was used to reveal the relative importance of genomic regions in predicting proliferation rate. The predictive model suggested additive interactions between the most informative regions such as 8p22-12 and 8q13-22.</p> <p>Conclusions</p> <p>Data-mining of large-scale microarray gene expression datasets can reveal regional clusters of co-ordinate gene expression, independent of cause. By correlating these clusters with tumour proliferation we have identified a number of genomic regions that act together to promote proliferation in ER+ breast cancer. Identification of such regions should enable prioritisation of genomic regions for combinatorial functional studies to pinpoint the key genes and interactions contributing to tumourigenicity.</p

Sequencing of prostate cancers identifies new cancer genes, routes of progression and drug targets

Prostate cancer represents a substantial clinical challenge because it is difficult to predict outcome and advanced disease is often fatal. We sequenced the whole genomes of 112 primary and metastatic prostate cancer samples. From joint analysis of these cancers with those from previous studies (930 cancers in total), we found evidence for 22 previously unidentified putative driver genes harboring coding mutations, as well as evidence for NEAT1 and FOXA1 acting as drivers through noncoding mutations. Through the temporal dissection of aberrations, we identified driver mutations specifically associated with steps in the progression of prostate cancer, establishing, for example, loss of CHD1 and BRCA2 as early events in cancer development of ETS fusion-negative cancers. Computational chemogenomic (canSAR) analysis of prostate cancer mutations identified 11 targets of approved drugs, 7 targets of investigational drugs, and 62 targets of compounds that may be active and should be considered candidates for future clinical trials

Transcriptome analysis of embryonic mammary cells reveals insights into mammary lineage establishment

Introduction: The mammary primordium forms during embryogenesis as a result of inductive interactions between its constitutive tissues, the mesenchyme and epithelium, and represents the earliest evidence of commitment to the mammary lineage. Previous studies of embryonic mouse mammary epithelium indicated that, by mid-gestation, these cells are determined to a mammary cell fate and that a stem cell population has been delimited. Mammary mesenchyme can induce mammary development from simple epithelium even across species and classes, and can partially restore features of differentiated tissue to mouse mammary tumours in co-culture experiments. Despite these exciting properties, the molecular identity of embryonic mammary cells remains to be fully characterised. Methods: Here, we define the transcriptome of the mammary primordium and the two distinct cellular compartments that comprise it, the mammary primordial bud epithelium and mammary mesenchyme. Pathway and network analysis was performed and comparisons of embryonic mammary gene expression profiles to those of both postnatal mouse and human mammary epithelial cell sub-populations and stroma were made. Results: Several of the genes we have detected in our embryonic mammary cell signatures were previously shown to regulate mammary cell fate and development, but we also identified a large number of novel candidates. Additionally, we determined genes that were expressed by both embryonic and postnatal mammary cells, which represent candidate regulators of mammary cell fate, differentiation and progenitor cell function that could signal from mammary lineage inception during embryogenesis through postnatal development. Comparison of embryonic mammary cell signatures with those of human breast cells identified potential regulators of mammary progenitor cell functions conserved across species. Conclusions: These results provide new insights into genetic regulatory mechanisms of mammary development, particularly identification of novel potential regulators of mammary fate and mesenchymal-epithelial cross-talk. Since cancers may represent diseases of mesenchymal-epithelial communications, we anticipate these results will provide foundations for further studies into the fundamental links between developmental, stem cell and breast cancer biology

Comprehensive Genomic Analysis of a BRCA2 Deficient Human Pancreatic Cancer

Capan-1 is a well-characterised BRCA2-deficient human cell line isolated from a liver metastasis of a pancreatic adenocarcinoma. Here we report a genome-wide assessment of structural variations and high-depth exome characterization of single nucleotide variants and small insertion/deletions in Capan-1. To identify potential somatic and tumour-associated variations in the absence of a matched-normal cell line, we devised a novel method based on the analysis of HapMap samples. We demonstrate that Capan-1 has one of the most rearranged genomes sequenced to date. Furthermore, small insertions and deletions are detected more frequently in the context of short sequence repeats than in other genomes. We also identify a number of novel mutations that may represent genetic changes that have contributed to tumour progression. These data provide insight into the genomic effects of loss of BRCA2 function

Plasticity in dendroclimatic response across the distribution range of Aleppo pine (Pinus halepensis)

We investigated the variability of the climate-growth relationship of Aleppo pine across its distribution range in the Mediterranean Basin. We constructed a network of tree-ring index chronologies from 63 sites across the region. Correlation function analysis identified the relationships of tree-ring index to climate factors for each site. We also estimated the dominant climatic gradients of the region using principal component analysis of monthly, seasonal, and annual mean temperature and total precipitation from 1,068 climatic gridpoints. Variation in ring width index was primarily related to precipitation and secondarily to temperature. However, we found that the dendroclimatic relationship depended on the position of the site along the climatic gradient. In the southern part of the distribution range, where temperature was generally higher and precipitation lower than the regional average, reduced growth was also associated with warm and dry conditions. In the northern part, where the average temperature was lower and the precipitation more abundant than the regional average, reduced growth was associated with cool conditions. Thus, our study highlights the substantial plasticity of Aleppo pine in response to different climatic conditions. These results do not resolve the source of response variability as being due to either genetic variation in provenance, to phenotypic plasticity, or a combination of factors. However, as current growth responses to inter-annual climate variability vary spatially across existing climate gradients, future climate-growth relationships will also likely be determined by differential adaptation and/or acclimation responses to spatial climatic variation. The contribution of local adaptation and/or phenotypic plasticity across populations to the persistence of species under global warming could be decisive for prediction of climate change impacts across populations. In this sense, a more complex forest dynamics modeling approach that includes the contribution of genetic variation and phenotypic plasticity can improve the reliability of the ecological inferences derived from the climate-growth relationships.This work was partially supported by Spanish Ministry of Education and Science co-funded by FEDER program (CGL2012-31668), the European Union and the National Ministry of Education and Religion of Greece (EPEAEK- Environment – Archimedes), the Slovenian Research Agency (program P4-0015), and the USDA Forest Service. The cooperation among international partners was supported by the COST Action FP1106, STREeSS