Text mining for contexts and relationships in cancer genomics literature.

MOTIVATION: Scientific advances build on the findings of existing research. The 2001 publication of the human genome has led to the production of huge volumes of literature exploring the context-specific functions and interactions of genes. Technology is needed to perform large-scale text mining of research papers to extract the reported actions of genes in specific experimental contexts and cell states, such as cancer, thereby facilitating the design of new therapeutic strategies. RESULTS: We present a new corpus and Text Mining methodology that can accurately identify and extract the most important details of cancer genomics experiments from biomedical texts. We build a Named Entity Recognition model that accurately extracts relevant experiment details from PubMed abstract text, and a second model that identifies the relationships between them. This system outperforms earlier models and enables the analysis of gene function in diverse and dynamically evolving experimental contexts. AVAILABILITY AND IMPLEMENTATION: Code and data are available here: https://github.com/cambridgeltl/functional-genomics-ie.

Crystalline silica particles induce DNA damage in respiratory epithelium by ATX secretion and Rac1 activation.

Autotaxin (ATX) and its product lysophosphatidic acid (LPA) have been implicated in lung fibrosis and cancer. We have studied their roles in DNA damage induced by carcinogenic crystalline silica particles (CSi). In an earlier study on bronchial epithelia, we concluded that ATX, via paracrine signaling, amplifies DNA damage. This effect was seen at 6-16 h. A succeeding study showed that CSi induced NLRP3 phosphorylation, mitochondrial depolarization, double strand breaks (DSBs), and NHEJ repair enzymes within minutes. In the current study we hypothesized a role for the ATX-LPA axis also in this rapid DNA damage. Using 16HBE human bronchial epithelial cells, we show ATX secretion at 3 min, and that ATX inhibitors (HA130 and PF8380) prevented both CSi-induced mitochondrial depolarization and DNA damage (detected by γH2AX and Comet assay analysis). Experiments with added LPA gave similar rapid effects as CSi. Furthermore, Rac1 was activated at 3 min, and a Rac1 inhibitor (NSC23766) prevented mitochondrial depolarization and genotoxicity. In mice the bronchial epithelia exhibited histological signs of ATX activation and signs of DSBs (53BP1 positive nuclei) minutes after a single inhalation of CSi. Our data indicate that CSi rapidly activate the ATX-LPA axis and within minutes this leads to DNA damage in bronchial epithelial cells. Thus, ATX mediates very rapid DNA damaging effects of inhaled particles.

LION LBD: a literature-based discovery system for cancer biology.

MOTIVATION: The overwhelming size and rapid growth of the biomedical literature make it impossible for scientists to read all studies related to their work, potentially leading to missed connections and wasted time and resources. Literature-based discovery (LBD) aims to alleviate these issues by identifying implicit links between disjoint parts of the literature. While LBD has been studied in depth since its introduction three decades ago, there has been limited work making use of recent advances in biomedical text processing methods in LBD. RESULTS: We present LION LBD, a literature-based discovery system that enables researchers to navigate published information and supports hypothesis generation and testing. The system is built with a particular focus on the molecular biology of cancer using state-of-the-art machine learning and natural language processing methods, including named entity recognition and grounding to domain ontologies covering a wide range of entity types and a novel approach to detecting references to the hallmarks of cancer in text. LION LBD implements a broad selection of co-occurrence based metrics for analyzing the strength of entity associations, and its design allows real-time search to discover indirect associations between entities in a database of tens of millions of publications while preserving the ability of users to explore each mention in its original context in the literature. Evaluations of the system demonstrate its ability to identify undiscovered links and rank relevant concepts highly among potential connections. AVAILABILITY AND IMPLEMENTATION: The LION LBD system is available via a web-based user interface and a programmable API, and all components of the system are made available under open licenses from the project home page http://lbd.lionproject.net. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Crystalline silica particles cause rapid NLRP3-dependent mitochondrial depolarization and DNA damage in airway epithelial cells.

BACKGROUND: Respirable crystalline silica causes lung carcinomas and many thousand future cancer cases are expected in e.g. Europe. Critical questions are how silica causes genotoxicity in the respiratory epithelium and if new cases can be avoided by lowered permissible exposure levels. In this study we investigate early DNA damaging effects of low doses of silica particles in respiratory epithelial cells in vitro and in vivo in an effort to understand low-dose carcinogenic effects of silica particles. RESULTS: We find DNA damage accumulation already after 5-10 min exposure to low doses (5 µg/cm2) of silica particles (Min-U-Sil 5) in vitro. DNA damage was documented as increased levels of γH2AX, pCHK2, by Comet assay, AIM2 induction, and by increased DNA repair (non-homologous end joining) signaling. The DNA damage response (DDR) was not related to increased ROS levels, but to a NLRP3-dependent mitochondrial depolarization. Particles in contact with the plasma membrane elicited a Ser198 phosphorylation of NLRP3, co-localization of NLRP3 to mitochondria and depolarization. FCCP, a mitochondrial uncoupler, as well as overexpressed NLRP3 mimicked the silica-induced depolarization and the DNA damage response. A single inhalation of 25 µg silica particles gave a similar rapid DDR in mouse lung. Biomarkers (CC10 and GPRC5A) indicated an involvement of respiratory epithelial cells. CONCLUSIONS: Our findings demonstrate a novel mode of action (MOA) for silica-induced DNA damage and mutagenic double strand breaks in airway epithelial cells. This MOA seems independent of particle uptake and of an involvement of macrophages. Our study might help defining models for estimating exposure levels without DNA damaging effects.

TGF beta promotes repair of bulky DNA damage through increased ERCC1/XPF and ERCC1/XPA interaction.

Transforming growth factor beta (TGFß) is multifunctional cytokine that is involved in the coordination and regulation of many cellular homeostatic processes. Compromised TGFß activity has been attributed to promotion of human cancers. Recent studies have identified a role for TGFß in response to radiation-induced DNA damage, suggesting a link between TGFß and the DNA damage response with implications for cancer development. In this study, the effects of TGFß on promoting the repair of bulky DNA damage, through modulation of nucleotide excision repair (NER), were investigated. We show that treatment of cells with exogenous TGFß leads to enhanced repair of DNA damage formed by polycyclic aromatic hydrocarbons and ultraviolet-C radiation; similarly, cells with constitutively activated endogenous TGFß signaling show comparable responses. This effect of TGFß is independent of the cell cycle. The response to TGFß is decreased in cells that have compromised TGFß signaling through RNA interference of Smad4 and is decreased in NER-deficient cells and cells with compromised NER through RNA interference of excision repair cross-complementing group 1 (ERCC1). Increased interaction and nuclear localization of ERCC1/xeroderma pigmentosum (XP) F and ERCC1/XPA proteins is observed after TGFß treatment. Our study represents the first experimental evidence of a role for TGFß in the repair of bulky DNA damage resulting from promotion of the interaction and localization of repair protein complexes involved in the incision step of NER.

The Water Extract of Juniperus communis L. Induces Cell Death and Sensitizes Cancer Cells to Cytostatic Drugs through p53 and PI3K/Akt Pathways.

Juniper (Juniperus communis L.) is a northern coniferous plant generally used as a spice and for nutritional purposes in foods and drinks. It was previously reported that juniper extract (JE) affects p53 activity, cellular stress, and gene expression induced cell death in human neuroblastoma cells. Therefore, the effects of juniper on p53 and Akt signaling was examined further in A549 lung, 22RV1 and DU145 prostate, and HepG2 liver cancer cells using Western blot, confocal microscopy, and MTT analysis. We found that juniper simultaneously decreased cell viability, activated the p53 pathway, and inactivated the PI3K/Akt pathway. The p53 activation was associated with increased nuclear p53 level. Akt was dephosphorylated, and its inactivation was associated with increased levels of PHLPP1 and PHLPP2 phosphatases. Parallel increases of PARP suggest that JE decreased cell viability by activating cell death. In adtion, JE potentiated the effects of gemcitabine and 5-fluorouracil anticancer drugs. Thus, JE can activate cell death in different cancer cell lines through p53 and Akt pathways.

Cancer Hallmarks Analytics Tool (CHAT): a text mining approach to organize and evaluate scientific literature on cancer.

MOTIVATION: To understand the molecular mechanisms involved in cancer development, significant efforts are being invested in cancer research. This has resulted in millions of scientific articles. An efficient and thorough review of the existing literature is crucially important to drive new research. This time-demanding task can be supported by emerging computational approaches based on text mining which offer a great opportunity to organize and retrieve the desired information efficiently from sizable databases. One way to organize existing knowledge on cancer is to utilize the widely accepted framework of the Hallmarks of Cancer. These hallmarks refer to the alterations in cell behaviour that characterize the cancer cell. RESULTS: We created an extensive Hallmarks of Cancer taxonomy and developed automatic text mining methodology and a tool (CHAT) capable of retrieving and organizing millions of cancer-related references from PubMed into the taxonomy. The efficiency and accuracy of the tool was evaluated intrinsically as well as extrinsically by case studies. The correlations identified by the tool show that it offers a great potential to organize and correctly classify cancer-related literature. Furthermore, the tool can be useful, for example, in identifying hallmarks associated with extrinsic factors, biomarkers and therapeutics targets. AVAILABILITY AND IMPLEMENTATION: CHAT can be accessed at: http://chat.lionproject.net. The corpus of hallmark-annotated PubMed abstracts and the software are available at: http://chat.lionproject.net/about. CONTACT: simon.baker@cl.cam.ac.uk. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Toluene diisocyanate exposure and autotaxin-lysophosphatidic acid signalling.

Toluene diisocyanate (TDI) is a reactive chemical used in manufacturing plastics. TDI exposure adversely affects workers' health, causing occupational asthma, but individuals differ in susceptibility. We recently suggested a role for signalling mediated by the enzyme autotaxin (ATX) and its product, lysophosphatidic acid (LPA), in TDI toxicity. Here we genotyped 118 TDI-exposed workers for six single-nucleotide polymorphisms (SNPs) in genes encoding proteins implicated in ATX-LPA signalling: purinergic receptor P2X7 (P2RX7), CC motif chemokine ligand 2 (CCL2), interleukin 1ß (IL1B), and caveolin 1 (CAV1). Two P2RX7 SNPs (rs208294 and rs2230911) significantly modified the associations between a biomarker of TDI exposure (urinary 2,4-toluene diamine) and plasma LPA; two IL1B SNPs (rs16944 and rs1143634) did not. CAV1 rs3807989 modified the associations, but the effect was not statistically significant (p = 0.05-0.09). In vitro, TDI-exposed bronchial epithelial cells (16HBE14o-) rapidly released ATX and IL-1ß. P2X7 inhibitors attenuated both responses, but confocal microscopy showed non-overlapping localizations of ATX and IL-1ß, and down-regulation of CAV1 inhibited the ATX response but not the IL-1ß response. This study indicates that P2X7 is pivotal for TDI-induced ATX-LPA signalling, which was modified by genetic variation in P2RX7. Furthermore, our data suggest that the TDI-induced ATX and IL-1ß responses occur independently.

ATM-activated autotaxin (ATX) propagates inflammation and DNA damage in lung epithelial cells: a new mode of action for silica-induced DNA damage?

Silica exposure is a common risk factor for lung cancer. It has been claimed that key elements in cancer development are activation of inflammatory cells that indirectly induce DNA damage and proliferative stimuli in respiratory epithelial cells. We studied DNA damage induced by silica particles in respiratory epithelial cells and focused the role of the signaling enzyme autotaxin (ATX). A549 and 16 bronchial epithelial cells (16HBE) lung epithelial cells were exposed to silica particles. Reactive oxygen species (ROS), NOD-like receptor family pyrin domain containing-3 (NLRP3) inflammasome activation, ATX, ataxia telangiectasia mutated (ATM), and DNA damage (γH2AX, pCHK1, pCHK2, comet assay) were end points. Low doses of silica induced NLRP3 activation, DNA damage accumulation, and ATM phosphorylation. A novel finding was that ATM induced ATX generation and secretion. Not only silica but also rotenone, camptothecin and H2O2 activated ATX via ATM, suggesting that ATX is part of a generalized ATM response to double-strand breaks (DSBs). Surprisingly, ATX inhibition mitigated DNA damage accumulation at later time points (6-16 h), and ATX transfection caused NLRP3 activation and DNA damage. Furthermore, the product of ATX enzymatic activity, lysophosphatidic acid, recapitulated the effects of ATX transfection. These data indicate an ATM-ATX-dependent loop that propagates inflammation and DSB accumulation, making low doses of silica effective inducers of DSBs in epithelial cells. We conclude that an ATM-ATX axis interconnects DSBs with silica-induced inflammation and propagates these effects in epithelial cells. Further studies of this adverse outcome pathway may give an accurate assessment of the lowest doses of silica that causes cancer.

Automatic semantic classification of scientific literature according to the hallmarks of cancer.

MOTIVATION: The hallmarks of cancer have become highly influential in cancer research. They reduce the complexity of cancer into 10 principles (e.g. resisting cell death and sustaining proliferative signaling) that explain the biological capabilities acquired during the development of human tumors. Since new research depends crucially on existing knowledge, technology for semantic classification of scientific literature according to the hallmarks of cancer could greatly support literature review, knowledge discovery and applications in cancer research. RESULTS: We present the first step toward the development of such technology. We introduce a corpus of 1499 PubMed abstracts annotated according to the scientific evidence they provide for the 10 currently known hallmarks of cancer. We use this corpus to train a system that classifies PubMed literature according to the hallmarks. The system uses supervised machine learning and rich features largely based on biomedical text mining. We report good performance in both intrinsic and extrinsic evaluations, demonstrating both the accuracy of the methodology and its potential in supporting practical cancer research. We discuss how this approach could be developed and applied further in the future. AVAILABILITY AND IMPLEMENTATION: The corpus of hallmark-annotated PubMed abstracts and the software for classification are available at: http://www.cl.cam.ac.uk/∼sb895/HoC.html. CONTACT: simon.baker@cl.cam.ac.uk.

Cancer Risk Assessment of Airborne PAHs Based on in Vitro Mixture Potency Factors.

Complex mixtures of polycyclic aromatic hydrocarbons (PAHs) are common environmental pollutants associated with adverse human health effects including cancer. However, the risk of exposure to mixtures is difficult to estimate, and risk assessment by whole mixture potency evaluations has been suggested. To facilitate this, reliable in vitro based testing systems are necessary. Here, we investigated if activation of DNA damage signaling in vitro could be an endpoint for developing whole mixture potency factors (MPFs) for airborne PAHs. Activation of DNA damage signaling was assessed by phosphorylation of Chk1 and H2AX using Western blotting. To validate the in vitro approach, potency factors were determined for seven individual PAHs which were in very good agreement with established potency factors based on cancer data in vivo. Applying the method using Stockholm air PAH samples indicated MPFs with orders of magnitude higher carcinogenic potency than predicted by established in vivo-based potency factors. Applying the MPFs in cancer risk assessment suggested that 45.4 (6% of all) cancer cases per year in Stockholm are due to airborne PAHs. Applying established models resulted in <1 cancer case per year, which is far from expected levels. We conclude that our in vitro based approach for establishing MPFs could be a novel method to assess whole mixture samples of airborne PAHs to improve health risk assessment.

Gender differences in cancer susceptibility: role of oxidative stress.

Cancer is a leading cause of death worldwide and environmental factors, including chemicals, have been suggested as major etiological incitements. Cancer statistics indicates that men get more cancer than women. However, differences in the known risk factors including life style or occupational exposure only offer partial explanation. Using a text mining tool, we have investigated the scientific literature concerning male- and female-specific rat carcinogens that induced tumors only in one gender in NTP 2-year cancer bioassay. Our evaluation shows that oxidative stress, although frequently reported for both male- and female-specific rat carcinogens, was mentioned significantly more in literature concerning male-specific rat carcinogens. Literature analysis of testosterone and estradiol showed the same pattern. Tox21 high-throughput assay results, although showing only weak association of oxidative stress-related processes for male- and female-specific rat carcinogens, provide additional support. We also analyzed the literature concerning 26 established human carcinogens (IARC group 1). Oxidative stress was more frequently reported for the majority of these carcinogens, and the Tox21 data resembled that of male-specific rat carcinogens. Thus, our data, based on about 600000 scientific abstracts and Tox21 screening assays, suggest a link between male-specific carcinogens, testosterone and oxidative stress. This implies that a different cellular response to oxidative stress in men and women may be a critical factor in explaining the greater cancer susceptibility observed in men. Although the IARC carcinogens are classified as human carcinogens, their classification largely based on epidemiological evidence from male cohorts, which raises the question whether carcinogen classifications should be gender specific.

Exposure to polychlorinated biphenyls and prostate cancer: population-based prospective cohort and experimental studies.

Polychlorinated biphenyls (PCBs) are highly persistent environmental pollutants and are undesirable components of our daily food. PCBs are classified as human carcinogens, but the evidence for prostate cancer is limited and available data are inconsistent. We explored the link between non-dioxin-like PCB and grade of prostate cancer in a prospective cohort as well as in cell experiments. A population-based cohort of 32496 Swedish men aged 45-79 years was followed prospectively through 1998-2011, to assess the association between validated estimates of dietary PCB exposure and incidence of prostate cancer by grade (2789 cases, whereof 1276 low grade, 756 intermediate grade, 450 high grade) and prostate cancer mortality (357 fatal cases). In addition, we investigated a non-dioxin-like PCB153-induced cell invasion and related markers in normal prostate stem cells (WPE-stem) and in three different prostate cancer cell lines (PC3, DU145 and 22RV1) at exposure levels relevant to humans. After multivariable-adjustment, dietary PCB exposure was positively associated with high-grade prostate cancer, relative risk (RR) 1.35 [95% confidence interval (CI): 1.03-1.76] and with fatal prostate cancer, RR 1.43 (95% CI: 1.05-1.95), comparing the highest tertile with the lowest. We observed no association with low or intermediate grade of prostate cancer. Cell invasion and related markers, including MMP9, MMP2, Slug and Snail, were significantly increased in human prostate cancer cells as well as in prostate stem cells after exposure to PCB153. Our findings both from the observational and experimental studies suggest a role of non-dioxin-like PCB153 in the development of high-grade and fatal prostate cancer.

Unsupervised discovery of information structure in biomedical documents.

MOTIVATION: Information structure (IS) analysis is a text mining technique, which classifies text in biomedical articles into categories that capture different types of information, such as objectives, methods, results and conclusions of research. It is a highly useful technique that can support a range of Biomedical Text Mining tasks and can help readers of biomedical literature find information of interest faster, accelerating the highly time-consuming process of literature review. Several approaches to IS analysis have been presented in the past, with promising results in real-world biomedical tasks. However, all existing approaches, even weakly supervised ones, require several hundreds of hand-annotated training sentences specific to the domain in question. Because biomedicine is subject to considerable domain variation, such annotations are expensive to obtain. This makes the application of IS analysis across biomedical domains difficult. In this article, we investigate an unsupervised approach to IS analysis and evaluate the performance of several unsupervised methods on a large corpus of biomedical abstracts collected from PubMed. RESULTS: Our best unsupervised algorithm (multilevel-weighted graph clustering algorithm) performs very well on the task, obtaining over 0.70 F scores for most IS categories when applied to well-known IS schemes. This level of performance is close to that of lightly supervised IS methods and has proven sufficient to aid a range of practical tasks. Thus, using an unsupervised approach, IS could be applied to support a wide range of tasks across sub-domains of biomedicine. We also demonstrate that unsupervised learning brings novel insights into IS of biomedical literature and discovers information categories that are not present in any of the existing IS schemes. AVAILABILITY AND IMPLEMENTATION: The annotated corpus and software are available at http://www.cl.cam.ac.uk/∼dk427/bio14info.html.

Phosphatase and tensin homolog deleted on chromosome 10 (PTEN) and PH domain and leucine-rich repeat phosphatase cross-talk (PHLPP) in cancer cells and in transforming growth factor ß-activated stem cells.

Akt kinase controls cell survival, proliferation, and invasive growth and is a critical factor for cancer development. Here we describe a cross-talk between phosphatases that may preserve levels of activated/phosphorylated Akt and confer aggressive growth of cancer cells. In prostatic cancer cells, but not in non-transformed cells or in prostate stem cells, we found that the phosphatase and tensin homolog deleted on chromosome 10 (PTEN) overexpression down-regulated PH domain and leucine-rich repeat phosphatase (PHLPP) and that PHLPP overexpression down-regulated PTEN. We also show that silencing PTEN by siRNA increased the levels of PHLPPs. This cross-talk facilitated invasive migration and was mediated by epigenetic alterations, including activation of miR-190, miR-214, polycomb group of proteins, as well as DNA methylation. A role for the purinergic receptor P2X4, previously associated with wound healing, was indicated. We also show that TGF-ß1 induced cross-talk concomitant with epithelial-mesenchymal transition in stem cells. The cross-talk emerged as an integrated part of epithelial-mesenchymal transition. We conclude that cross-talk between PTEN and PHLPPs is silenced in normal prostate cells but activated in TGF-ß1 transformed prostate stem and cancer cells and facilitates invasive growth.

Toluene diisocyanate: Induction of the autotaxin-lysophosphatidic acid axis and its association with airways symptoms.

Diisocyanates are industrial chemicals which have a wide range of applications in developed and developing countries. They are notorious lung toxicants and respiratory sensitizers. However, the mechanisms behind their adverse effects are not adequately characterized. Autotaxin (ATX) is an enzyme producing lysophosphatidic acid (LPA), and the ATX-LPA axis has been implicated in lung related inflammatory conditions and diseases, including allergic asthma, but not to toxicity of environmental low-molecular-weight chemicals. We investigated effects of toluene diisocyanate (TDI) on ATX induction in human lung epithelial cell models, and we correlated LPA-levels in plasma to biomarkers of TDI exposure in urine collected from workers exposed to <5ppb (parts per billion). Information on workers' symptoms was collected through interviews. One nanomolar TDI robustly induced ATX release within 10min in vitro. A P2X7- and P2X4-dependent microvesicle formation was implicated in a rapid ATX release and a subsequent protein synthesis. Co-localization between purinergic receptors and ATX was documented by immunofluorescence and confocal microscopy. The release was modulated by monocyte chemoattractant protein-1 (MCP-1) and by extracellular ATP. In workers, we found a dose-response relationship between TDI exposure biomarkers in urine and LPA levels in plasma. Among symptomatic workers reporting "sneezing", the LPA levels were higher than among non-symptomatic workers. This is the first report indicating induction of the ATX-LPA axis by an environmental low-molecular-weight chemical, and our data suggest a role for the ATX-LPA axis in TDI toxicity.

Detection of benz[j]aceanthrylene in urban air and evaluation of its genotoxic potential.

Benz[j]aceanthrylene (B[j]A) is a cyclopenta-fused polycyclic aromatic hydrocarbon with strong mutagenic and carcinogenic effects. We have identified B[j]A in air particulate matter (PM) in samples collected in Stockholm, Sweden and in Limeira, Brazil using LC-GC/MS analysis. Determined concentrations ranged between 1.57 and 12.7 and 19.6-30.2 pg/m(3) in Stockholm and Limeira, respectively, which was 11-30 times less than benzo[a]pyrene (B[a]P) concentrations. Activation of the DNA damage response was evaluated after exposure to B[j]A in HepG2 cells in comparison to B[a]P. We found that significantly lower concentrations of B[j]A were needed for an effect on cell viability compared to B[a]P, and equimolar exposure resulted in significant more DNA damage with B[j]A. Additionally, levels of γH2AX, pChk1, p53, pp53, and p21 proteins were higher in response to B[j]A than B[a]P. On the basis of dose response induction of pChk1 and γH2AX, B[j]A potency was 12.5- and 33.3-fold higher than B[a]P, respectively. Although B[j]A levels in air were low, including B[j]A in the estimation of excess lifetime cancer risk increased the risk up to 2-fold depending on which potency factor for B[j]A was applied. Together, our results show that B[j]A could be an important contributor to the cancer risk of air PM.

Atorvastatin prevents ATP-driven invasiveness via P2X7 and EHBP1 signaling in PTEN-expressing prostate cancer cells.

Epidemiological studies indicate that statins, cholesterol-lowering drugs, prevent aggressive prostate cancer and other types of cancer. Employing essentially non-prostate cell lines, we previously showed that statins rapidly downregulate nuclear levels of phosphorylated Akt via P2X7, a purinergic receptor recently implicated in invasive growth. Here, we present studies on phosphatase and tensin homolog deleted on chromosome 10 (PTEN)-positive prostatic cells. We document an involvement of EH domain-binding protein 1 (EHBP1), previously associated with aggressive prostate cancer and insulin-stimulated trafficking and cell migration, in P2X7 signaling. We also show that EHBP1 is essential for an anti-invasive effect of atorvastatin. Furthermore, EHBP1 interacted with P-Rex1, a guanine nucleotide exchange factor previously implicated in invasive growth. Mevalonate did not prevent this anti-invasive effect of atorvastatin. These data indicate that atorvastatin modulates invasiveness via P2X7, EHBP1 and P-Rex1. Interestingly, the interaction between EHBP1 and P-Rex1 was not induced by extracellular adenosine triphosphate (ATP), the endogenous P2X7 ligand, and statins counteracted invasiveness stimulated by extracellular ATP. In support of these experimental data, a population-based genetic analysis showed that a loss of function allele in the P2X7 gene (rs3751143) associated with non-aggressive cancer, and the common allele with aggressive cancer. Our data indicate a novel signaling pathway that inhibits invasiveness and that is druggable. Statins may reduce the risk of aggressive prostate cancer via P2X7 and by counteracting invasive effects of extracellular ATP.

Active learning-based information structure analysis of full scientific articles and two applications for biomedical literature review.

MOTIVATION: Techniques that are capable of automatically analyzing the information structure of scientific articles could be highly useful for improving information access to biomedical literature. However, most existing approaches rely on supervised machine learning (ML) and substantial labeled data that are expensive to develop and apply to different sub-fields of biomedicine. Recent research shows that minimal supervision is sufficient for fairly accurate information structure analysis of biomedical abstracts. However, is it realistic for full articles given their high linguistic and informational complexity? We introduce and release a novel corpus of 50 biomedical articles annotated according to the Argumentative Zoning (AZ) scheme, and investigate active learning with one of the most widely used ML models-Support Vector Machines (SVM)-on this corpus. Additionally, we introduce two novel applications that use AZ to support real-life literature review in biomedicine via question answering and summarization. RESULTS: We show that active learning with SVM trained on 500 labeled sentences (6% of the corpus) performs surprisingly well with the accuracy of 82%, just 2% lower than fully supervised learning. In our question answering task, biomedical researchers find relevant information significantly faster from AZ-annotated than unannotated articles. In the summarization task, sentences extracted from particular zones are significantly more similar to gold standard summaries than those extracted from particular sections of full articles. These results demonstrate that active learning of full articles' information structure is indeed realistic and the accuracy is high enough to support real-life literature review in biomedicine. AVAILABILITY: The annotated corpus, our AZ classifier and the two novel applications are available at http://www.cl.cam.ac.uk/yg244/12bioinfo.html