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We report the discovery, via a unique high-throughput screening strategy, of a novel bioactive anticancer compound: Thiol Alkylating Compound Inducing Massive Apoptosis (TACIMA)-218. We demonstrate that this molecule engenders apoptotic cell death in genetically diverse murine and human cancer cell lines, irrespective of their p53 status, while sparing normal cells. TACIMA-218 causes oxidative stress in the absence of protective antioxidants normally induced by Nuclear factor erythroid 2–related factor 2 activation. As such, TACIMA-218 represses RNA translation and triggers cell signaling cascade alterations in AKT, p38, and JNK pathways. In addition, TACIMA-218 manifests thiol-alkylating properties resulting in the disruption of redox homeostasis along with key metabolic pathways. When administered to immunocompetent animals as a monotherapy, TACIMA-218 has no apparent toxicity and induces complete regression of pre-established lymphoma and melanoma tumors. In sum, TACIMA-218 is a potent oxidative stress inducer capable of selective cancer cell targeting.

Supplementary data.

Statistical comparison of the DNF taxonomy against single datasets taxonomies, using one-sided superiority tests

Similarity Matrices of the DNF and single-layer taxonomies (based on the CTRPv2 drug sensitivity dataset).

This file contains all the Supplementary Figures (1-9) reporting the results of DNF using the NCI60 drug sensitivity data, as well as additional information regarding the size and distribution for drug communities in the DNF taxonomies

Comparison of predictive value of DNF versus published methods

Drug communities identified from the DNF taxonomies.

Identification of drug targets and mechanism of action (MoA) for new and uncharacterized anticancer drugs is important for optimization of treatment efficacy. Current MoA prediction largely relies on prior information including side effects, therapeutic indication, and chemoinformatics. Such information is not transferable or applicable for newly identified, previously uncharacterized small molecules. Therefore, a shift in the paradigm of MoA predictions is necessary toward development of unbiased approaches that can elucidate drug relationships and efficiently classify new compounds with basic input data. We propose here a new integrative computational pharmacogenomic approach, referred to as Drug Network Fusion (DNF), to infer scalable drug taxonomies that rely only on basic drug characteristics toward elucidating drug–drug relationships. DNF is the first framework to integrate drug structural information, high-throughput drug perturbation, and drug sensitivity profiles, enabling drug classification of new experimental compounds with minimal prior information. DNF taxonomy succeeded in identifying pertinent and novel drug–drug relationships, making it suitable for investigating experimental drugs with potential new targets or MoA. The scalability of DNF facilitated identification of key drug relationships across different drug categories, providing a flexible tool for potential clinical applications in precision medicine. Our results support DNF as a valuable resource to the cancer research community by providing new hypotheses on compound MoA and potential insights for drug repurposing. Cancer Res; 77(11); 3057–69. ©2017 AACR.

This file contains the legends for Supplementary Tables 1 to 5.

This file contains a detailed description of the methods used to reproduce published algorithms for drug clustering.

Enrichment of DNF drug communities

Immunoproteasome-reprogrammed mesenchymal stromal cells (IRMs) can surpass dendritic cells at eliciting tumor-specific immunity. However, the current IRM vaccination regimen remains clinically unsuitable due to the relatively high dose of IRMs needed. Since the administration of a lower IRM dose triggers a feeble anti-tumoral response, we aimed to combine this vaccination regimen with different modalities to fine-tune the potency of the vaccine. In a nutshell, we found that the co-administration of IRMs and interleukin-12 accentuates the anti-tumoral response, whereas the cross-presentation potency of IRMs is enhanced via intracellular succinate build-up, delayed endosomal maturation, and increased endosome-to-cytosol plasticity. Stimulating phagocyte-mediated cancer efferocytosis by blocking the CD47-SIRPα axis was also found to enhance IRM vaccine outcomes. Upon designing a single protocol combining the abovementioned strategies, 60% of treated animals exhibited a complete response. Altogether, this is the first IRM-based vaccination study, optimized to simultaneously target three vaccine-related pitfalls: T-cell response, antigen cross-presentation, and cancer phagocytosis.

Multi-omic approaches offer an unprecedented overview of the development, plasticity, and resistance of cancer. However, the translation from anti-cancer compounds identified in vitro to clinically active drugs have a notoriously low success rate. Here, we review how technical advances in cell culture, robotics, computational biology, and development of reporter systems have transformed drug discovery, enabling screening approaches tailored to clinically relevant functional readouts (e.g., bypassing drug resistance). Illustrating with selected examples of “success stories,” we describe the process of phenotype-based high-throughput drug screening to target malignant cells or the immune system. Second, we describe computational approaches that link transcriptomic profiling of cancers with existing pharmaceutical compounds to accelerate drug repurposing. Finally, we review how CRISPR-based screening can be applied for the discovery of mechanisms of drug resistance and sensitization. Overall, we explore how the complementary strengths of each of these approaches allow them to transform the paradigm of pre-clinical drug development.

We report the discovery, via a unique high-throughput screening strategy, of a novel bioactive anticancer compound: Thiol Alkylating Compound Inducing Massive Apoptosis (TACIMA)-218. We demonstrate that this molecule engenders apoptotic cell death in genetically diverse murine and human cancer cell lines, irrespective of their p53 status, while sparing normal cells. TACIMA-218 causes oxidative stress in the absence of protective antioxidants normally induced by Nuclear factor erythroid 2–related factor 2 activation. As such, TACIMA-218 represses RNA translation and triggers cell signaling cascade alterations in AKT, p38, and JNK pathways. In addition, TACIMA-218 manifests thiol-alkylating properties resulting in the disruption of redox homeostasis along with key metabolic pathways. When administered to immunocompetent animals as a monotherapy, TACIMA-218 has no apparent toxicity and induces complete regression of pre-established lymphoma and melanoma tumors. In sum, TACIMA-218 is a potent oxidative stress inducer capable of selective cancer cell targeting.

The transition from acute to chronic pain is critically important but not well understood. Here, we investigated the pathophysiological mechanisms underlying the transition from acute to chronic low back pain (LBP) and performed transcriptome-wide analysis in peripheral immune cells of 98 participants with acute LBP, followed for 3 months. Transcriptomic changes were compared between patients whose LBP was resolved at 3 months with those whose LBP persisted. We found thousands of dynamic transcriptional changes over 3 months in LBP participants with resolved pain but none in those with persistent pain. Transient neutrophil-driven up-regulation of inflammatory responses was protective against the transition to chronic pain. In mouse pain assays, early treatment with a steroid or nonsteroidal anti-inflammatory drug (NSAID) also led to prolonged pain despite being analgesic in the short term; such a prolongation was not observed with other analgesics. Depletion of neutrophils delayed resolution of pain in mice, whereas peripheral injection of neutrophils themselves, or S100A8/A9 proteins normally released by neutrophils, prevented the development of long-lasting pain induced by an anti-inflammatory drug. Analysis of pain trajectories of human subjects reporting acute back pain in the UK Biobank identified elevated risk of pain persistence for subjects taking NSAIDs. Thus, despite analgesic efficacy at early time points, the management of acute inflammation may be counterproductive for long-term outcomes of LBP sufferers.

Discoid lupus erythematosus (DLE) is an autoimmune disorder with a poorly defined etiology. Despite epidemiologic gender and ethnic biases, a clear genetic basis for DLE remains elusive. In this study, we used exome and RNA sequencing technologies to characterize a consanguineous Lebanese family with four affected individuals who presented with classical scalp DLE and generalized folliculitis. Our results unraveled a novel biallelic variant c.1313C > A leading to a missense substitution p.(Thr438Asn) in TRAF3IP2(NM_147200.3). Expression studies in cultured cells revealed mis-localization of the mutated protein. Functional characterization of the mutated protein showed significant reduction in the physical interaction with the interleukin 17-A receptor (IL17RA), while interaction with TRAF6 was unaffected. By conducting a differential genome-wide transcriptomics analysis between affected and non-affected individuals, we showed that the hair follicle differentiation pathway is drastically suppressed, whereas cytokine and inflammation responses are significantly upregulated. Furthermore, our results were highly concordant with molecular signatures in patients with DLE from a public dataset. In conclusion, this is the first report on a new putative role for TRAF3IP2 in the etiology of DLE. The identified molecular features associated with this gene could pave the way for better DLE-targeted treatment.

Background Mesenchymal stromal cells (MSCs) have been extensively used in the clinic due to their exquisite tissue repair capacity. However, they also hold promise in the field of cellular vaccination as they can behave as conditional antigen presenting cells in response to interferon (IFN)-gamma treatment under a specific treatment regimen. This suggests that the immune function of MSCs can be pharmacologically modulated. Given the capacity of the agonist pyrimido-indole derivative UM171a to trigger the expression of various antigen presentation-related genes in human hematopoietic progenitor cells, we explored the potential use of UM171a as a means to pharmacologically instill and/or promote antigen presentation by MSCs. Methods Besides completing a series of flow-cytometry-based phenotypic analyses, several functional antigen presentation assays were conducted using the SIINFEKL-specific T-cell clone B3Z. Anti-oxidants and electron transport chain inhibitors were also used to decipher UM171a’s mode of action in MSCs. Finally, the potency of UM171a-treated MSCs was evaluated in the context of therapeutic vaccination using immunocompetent C57BL/6 mice with pre-established syngeneic EG.7T-cell lymphoma. Results Treatment of MSCs with UM171a triggered potent increase in H2-Kb cell surface levels along with the acquisition of antigen cross-presentation abilities. Mechanistically, such effects occurred in response to UM171a-mediated production of mitochondrial-derived reactive oxygen species as their neutralization using anti-oxidants or Antimycin-A mitigated MSCs’ ability to cross-present antigens. Processing and presentation of the immunogenic ovalbumin-derived SIINFEKL peptide was caused by de novo expression of the Psmb8 gene in response to UM171a-triggered oxidative stress. When evaluated for their anti-tumoral properties in the context of therapeutic vaccination, UM171a-treated MSC administration to immunocompetent mice with pre-established T-cell lymphoma controlled tumor growth resulting in 40% survival without the need of additional supportive therapy and/or standard-of-care. Conclusions Altogether, our findings reveal a new immune-related function for UM171a and clearly allude to a direct link between UM171a-mediated ROS induction and antigen cross-presentation by MSCs. The fact that UM171a treatment modulates MSCs to become antigen-presenting cells without the use of IFN-gamma opens-up a new line of investigation to search for additional agents capable of converting immune-suppressive MSCs to a cellular tool easily adaptable to vaccination. Graphical abstract

The cedar forests of Lebanon have been threatened by the outbreak caused by climate change of a web-spinning sawfly, Cephalcia tannourinensis (Hymenoptera: Pamphiliidae), which negatively impacted the survival of one of the oldest tree species on earth. In this study, we investigated the occurrence of naturally soil-inhabiting entomopathogenic fungi for their role in containing the massive outbreak of this insect. We used a combination of fungal bioexploration methods, including insect bait and selective media. Morphological features and multilocus phylogeny—based on Sanger sequencing of the transcripts encoding the translation elongation factor 1-alpha (TEF-α), RNA polymerase II second largest subunit (RBP2), and the nuclear intergenic region (Bloc) were used for species identification. The occurrence rate of entomopathogenic fungi (EPF) varied with location, soil structure, forest structure, and isolation method. From 15 soil samples positive for fungal occurrence, a total of 249 isolates was obtained from all locations using different isolation methods. The phylogenetic analysis confirmed the existence of two novel indigenous species: Beauveria tannourinensis sp. nov. and Beauveria ehdenensis sp. nov. In conclusion, the present survey was successful (1) in optimizing the isolation methods for EPF, (2) investigating the natural occurrence of Beauveria spp. in outbreak areas of C. tannourinensis, and (3) in characterizing the presence of new Beauveria species in Lebanese cedar forest soil.

Chronic pain is a debilitating and poorly treated condition whose underlying mechanisms are poorly understood. Nerve injury and inflammation cause alterations in gene expression in tissues associated with pain processing, supporting molecular and cellular mechanisms that maintain painful states. However, it is not known whether transcriptome changes can be used to reconstruct a molecular pathophysiology of pain. In the current study, we identify molecular pathways contributing to chronic pain states through the analysis of global changes in the transcriptome of dorsal root ganglia, spinal cord, brain, and blood in mouse assays of nerve injury- and inflammation-induced pain. Comparative analyses of differentially expressed genes identified substantial similarities between 2 animal pain assays and with human low-back pain. Furthermore, the extracellular matrix (ECM) organization has been found the most commonly regulated pathway across all tested tissues in the 2 animal assays. Examination of human genome-wide association study data sets revealed an overrepresentation of differentially expressed genes within the ECM organization pathway in single nucleotide polymorphisms most strongly associated with human back pain. In summary, our comprehensive transcriptomics analysis in mouse and human identified ECM organization as a central molecular pathway in the development of chronic pain.

Mesenchymal stromal cells (MSCs) are commonly known for their immune-suppressive abilities. However, our group provided evidence that it is possible to convert MSCs into potent antigen presenting cells (APCs) using either genetic engineering or pharmacological means. Given the capacity of UM171a to trigger APC-like function in MSCs, and the recent finding that this drug may modulate the epigenome by inhibiting the lysine-specific demethylase 1 (LSD1), we explored whether the direct pharmacological inhibition of LSD1 could instill APC-like functions in MSCs akin to UM171a. The treatment of MSCs with the LSD1 inhibitor tranylcypromine (TC) elicits a double-stranded (ds)RNA stress response along with its associated responsive elements, including pattern recognition receptors (PRRs), Type-I interferon (IFN), and IFN-stimulated genes (ISGs). The net outcome culminates in the enhanced expression of H2-Kb, and an increased stability of the cell surface peptide: MHCI complexes. As a result, TC-treated MSCs stimulate CD8 T-cell activation efficiently, and elicit potent anti-tumoral responses against the EG.7 T-cell lymphoma in the context of prophylactic vaccination. Altogether, our findings reveal a new pharmacological protocol whereby targeting LSD1 in MSCs elicits APC-like capabilities that could be easily exploited in the design of future MSC-based anti-cancer vaccines.

Dendritic cells (DCs) excel at cross-presenting antigens, but their effectiveness as cancer vaccine is limited. Here, we describe an innovative vaccine approach using mesenchymal stromal cells (MSCs) engineered to express the immunoproteasome (IPr) complex (MSC-IPr). Such modification instilled efficient antigen cross-presenting abilities associated with enhanced major histocompatibility complex (MHC)I and CD80 expression, de novo expression of interleukin-12 along with higher chemokine secretion. In addition, the cross-presentation capacity of MSC-IPr is highly dependent on AMPK signaling, oxidative phosphorylation and production of reactive oxygen species. Compared to DCs, MSC-IPr hold the ability to cross-present a vastly different epitope repertoire, which translates into potent re-activation of T-cell immunity against EL4 lymphoma and B16 melanoma tumors. Moreover, therapeutic vaccination of animals with pre-established tumors efficiently controls cancer growth, an effect further enhanced when combined with antibodies targeting PD1, CTLA4, LAG3 or 4-1BB under both autologous and allogeneic settings. MSC-IPr constitute therefore a novel subset of non-hematopoietic antigen-presenting cells suitable for the future design of universal cell-based cancer vaccines.

Proteasomes are complex macromolecular structures existing in various forms to regulate a myriad of cellular processes. Besides degrading unwanted or misfolded proteins (proteostasis), distinct immune functions were ascribed for the immunoproteasome and thymoproteasome (TPr) complexes. For instance, antigen degradation during ongoing immune responses mainly relies on immunoproteasome activity, whereas intrathymic CD8 T-cell development requires peptide generation by the TPr complex. Despite these substantial differences, the functional contribution of the TPr to peripheral T-cell immunity remains ill-defined. We herein explored whether the use of mesenchymal stromal cells (MSCs) engineered to exhibit altered proteasomal activity through de novo expression of the TPr complex can be exploited as a novel anti-cancer vaccine capable of triggering potent CD8 T-cell activation. Phenotypic and molecular characterization of MSC-TPr revealed a substantial decrease in MHCI (H2-Kb and H2-Dd) expression along with elevated secretion of various chemokines (CCL2, CCL9, CXCL1, LIX, and CX3CL1). In parallel, transcriptomic analysis pinpointed the limited ability of MSC-TPr to present endogenous antigens, which is consistent with their low expression levels of the peptide-loading proteins TAP, CALR, and PDAI3. Nevertheless, MSC-TPr cross-presented peptides derived from captured soluble proteins. When tested for their protective capacity, MSC-TPr triggered modest anti-tumoral responses despite efficient generation of effector memory CD4 and CD8 T cells. In contrast, clodronate administration prior to vaccination dramatically enhanced the MSC-TPr-induced anti-tumoral immunity clearly highlighting a refractory role mediated by phagocytic cells. Thus, our data elute to a DC cross-priming-dependant pathway in mediating the therapeutic effect of MSC-TPr.

BACKGROUND: Recognizing low right ventricular (RV) function from 2-dimentiontial echocardiography (2D-ECHO) is challenging when parameters are contradictory. We aim to develop a model to predict low RV function integrating the various 2D-ECHO parameters in reference to cardiac magnetic resonance (CMR)—the gold standard. METHODS: We retrospectively identified patients who underwent a 2D-ECHO and a CMR within 3 months of each other at our institution (American University of Beirut Medical Center). We extracted three parameters (TAPSE, S’ and FAC(RV)) that are classically used to assess RV function. We have assessed the ability of 2D-ECHO derived parameters and clinical features to predict RV function measured by the gold standard CMR. We compared outcomes from four machine learning algorithms, widely used in the biomedical community to solve classification problems. RESULTS: One hundred fifty-five patients were identified and included in our study. Average age was 43±17.1 years old and 52/156 (33.3%) were females. According to CMR, 21 patients were identified to have RV dysfunction, with an RVEF of 34.7%±6.4%, as opposed to 54.7%±6.7% in the normal RV population (P

The beginning of the twenty-first century has been marked by three distinct waves of zoonotic coronavirus outbreaks into the human population. The current pandemic COVID-19 (Coronavirus disease 2019) is caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). With a rapid infection rate, it is a global threat endangering the livelihoods of millions worldwide. Currently, and despite the collaborative efforts of governments, researchers, and the pharmaceutical industries, there are no substantially significant treatment protocols for the disease. To address the need for such an immediate call of action, we leveraged the largest dataset of drug-induced transcriptomic perturbations, public SARS-CoV-2 transcriptomic datasets, and expression profiles from normal lung transcriptomes. Our unbiased systems biology approach not only shed light on previously unexplored molecular details of SARS-CoV-2 infection (e.g., interferon signaling, inflammation and ACE2 co-expression hallmarks in normal and infected lungs) but most importantly prioritized more than 50 repurposable drug candidates (e.g., Corticosteroids, Janus kinase and Bruton kinase inhibitors). Further clinical investigation of these FDA approved candidates as monotherapy or in combination with an antiviral regimen (e.g., Remdesivir) could be promising treatment options against COVID-19.

Raynaud's Phenomenon (RP) results from exaggerated cold-induced vasoconstriction. RP patients suffer from vasospastic attacks and compromised digital blood perfusion leading to a triple color change at the level the fingers. Severe RP may cause ulcers and threaten tissue viability. Many drugs have been used to alleviate the symptoms of RP. These include calcium-channel blockers, cGMP-specific phosphodiesterase type 5 inhibitors, prostacyclin analogs, and angiotensin receptor blockers. Despite their variety, these drugs do not treat RP but rather alleviate its symptoms. To date, no drug for RP has been yet approved by the U.S Food and Drugs Administration. Cilostazol is a selective inhibitor of phosphodiesterase-III, originally prescribed to treat intermittent claudication. Owing to its antiplatelet and vasodilating properties, cilostazol is being repurposed as a potential drug for RP. This review focuses on the different lines of action of cilostazol serving to enhance blood perfusion in RP patients.

Phenotypic screening is an ideal strategy for the discovery of novel bioactive molecules. Using a customized high-throughput screening (HTS) assay employing primary T lymphocytes, we screened a small library of 4,398 compounds with unknown biological function/target to identify compounds eliciting immunomodulatory properties and discovered a sulfonyl-containing hit, we named InhiTinib. This compound inhibited interferon (IFN)-gamma production and proliferation of primary CD3+ T cells without inducing cell death. In contrast, InhiTinib triggered apoptosis in several murine and human cancer cell lines. Besides, the compound was well tolerated by immunocompetent mice, triggered tumor regression in animals with pre-established EL4 T-cell lymphomas, and prolonged the overall survival of mice harboring advanced tumors. Altogether, our data demonstrate the anti-cancer properties of InhiTinib, which can henceforth bridge to wider-scale biochemical and clinical tests following further in-depth pharmacodynamic studies., Graphical Abstract Using a high-throughput screening (HTS) assay employing transgenic T cells which fluoresce upon T cell receptor (TCR) activation, we screened a small library of compounds with unknown biological function/target to identify compounds with potential immunomodulatory properties. Among the screened library, we discovered a sulfonyl-containing hit, we named. This compound inhibited interferon (IFN)-gamma production and proliferation of primary CD3+ T-cells without inducing cell death. In contrast, InhiTinib triggered apoptosis in several murine and human cancer cell lines. Further in vivo studies showed the compound is well tolerated by immunocompetent mice, triggers tumor regression in animals with pre-established EL4 T-cell lymphomas, and prolongs the overall survival of mice harboring advanced tumors.

Summary Dendritic cells (DCs) excel at cross-presenting antigens, but their effectiveness as cancer vaccine is limited. Here, we describe a vaccination approach using mesenchymal stromal cells (MSCs) engineered to express the immunoproteasome complex (MSC-IPr). Such modification instills efficient antigen cross-presentation abilities associated with enhanced major histocompatibility complex class I and CD80 expression, de novo production of interleukin-12, and higher chemokine secretion. This cross-presentation capacity of MSC-IPr is highly dependent on their metabolic activity. Compared with DCs, MSC-IPr hold the ability to cross-present a vastly different epitope repertoire, which translates into potent re-activation of T cell immunity against EL4 and A20 lymphomas and B16 melanoma tumors. Moreover, therapeutic vaccination of mice with pre-established tumors efficiently controls cancer growth, an effect further enhanced when combined with antibodies targeting PD-1, CTLA4, LAG3, or 4-1BB under both autologous and allogeneic settings. Therefore, MSC-IPr constitute a promising subset of non-hematopoietic antigen-presenting cells suitable for designing universal cell-based cancer vaccines., Graphical abstract, Highlights • Stable expression of the immunoproteasome in MSCs instills a pro-inflammatory phenotype • Induced metabolic alterations drive antigen cross-presentation by MSC-IPr • Engineered MSC-IPr elicit potent anti-tumoral immunity • The immunopeptidome of MSC-IPr is distinct from dendritic cells, Abusarah et al. demonstrate that mesenchymal stromal cells engineered to express the immunoproteasome (MSC-IPr) exhibit distinct antigen presentation properties, display altered metabolic signatures, and present a unique set of antigens compared with standard dendritic cells. These attributes make them ideal candidates for the future design of cell-based cancer vaccines.

Recent cancer pharmacogenomic studies profiled large panels of cell lines against hundreds of approved drugs and experimental chemical compounds. The overarching goal of these screens is to measure sensitivity of cell lines to chemical perturbations, correlate these measures to genomic features, and thereby develop novel predictors of drug response. However, leveraging these valuable data is challenging due to the lack of standards for annotating cell lines and chemical compounds, and quantifying drug response. Moreover, it has been recently shown that the complexity and complementarity of the experimental protocols used in the field result in high levels of technical and biological variation in the in vitro pharmacological profiles. There is therefore a need for new tools to facilitate rigorous comparison and integrative analysis of large-scale drug screening datasets. To address this issue, we have developed PharmacoDB (pharmacodb.pmgenomics.ca), a database integrating the largest cancer pharmacogenomic studies published to date. Here, we describe how the curation of cell line and chemical compound identifiers maximizes the overlap between datasets and how users can leverage such data to compare and extract robust drug phenotypes. PharmacoDB provides a unique resource to mine a compendium of curated cancer pharmacogenomic datasets that are otherwise disparate and difficult to integrate.

Introduction New fluorinated diaryl ethers and bisarylic ketones were designed and evaluated for their anti-inflammatory effects in primary macrophages. Methods The synthesis of the designed molecules started from easily accessible and versatile gem-difluoro propargylic derivatives. The desired aromatic systems were obtained using Diels–Alder/aromatization sequences and this was followed by Pd-catalyzed coupling reactions and, when required, final functionalization steps. Both direct inhibitory effects on cyclooxygenase-1 or -2 activities, protein expression of cyclooxygenase-2 and nitric oxide synthase-II and the production of prostaglandin E2, the pro-inflammatory nitric oxide and interleukin-6 were evaluated in primary murine bone marrow-derived macrophages in response to lipopolysaccharide. Docking of the designed molecules in cyclooxygenase-1 or -2 was performed. Results Only fluorinated compounds exerted anti-inflammatory activities by lowering the secretion of interleukin-6, nitric oxide, and prostaglandin E2, and decreasing the protein expression of inducible nitric oxide synthase and cyclooxygenase-2 in mouse primary macrophages exposed to lipopolysaccharide, as well as cyclooxygenase activity for some inhibitors with different efficiencies depending on the R-groups. Docking observation suggested an inhibitory role of cyclooxygenase-1 or -2 for compounds A3, A4 and A5 in addition to their capacity to inhibit nitrite, interleukin-6, and nitric oxide synthase-II and cyclooxygenase-2 expression. Conclusion The new fluorinated diaryl ethers and bisarylic ketones have anti-inflammatory effects in macrophages. These fluorinated compounds have improved potential anti-inflammatory properties due to the fluorine residues in the bioactive molecules.

Additional file 2. ARRIVE Check list.

Motivation High-throughput molecular profiles of human cells have been used in predictive computational approaches for stratification of healthy and malignant phenotypes and identification of their biological states. In this regard, pathway activities have been used as biological features in unsupervised and supervised learning schemes. Results We developed SIGN (Similarity Identification in Gene expressioN), a flexible open-source R package facilitating the use of pathway activities and their expression patterns to identify similarities between biological samples. We defined a new measure, the transcriptional similarity coefficient, which captures similarity of gene expression patterns, instead of quantifying overall activity, in biological pathways between the samples. To demonstrate the utility of SIGN in biomedical research, we establish that SIGN discriminates subtypes of breast tumors and patients with good or poor overall survival. SIGN outperforms the best models in DREAM challenge in predicting survival of breast cancer patients using the data from the Molecular Taxonomy of Breast Cancer International Consortium. In summary, SIGN can be used as a new tool for interrogating pathway activity and gene expression patterns in unsupervised and supervised learning schemes to improve prognostic risk estimation for cancer patients by the biomedical research community. Availability and implementation An open-source R package is available (https://cran.r-project.org/web/packages/SIGN/).

The beginning of the twenty-first century has been marked by three distinct waves of zoonotic coronavirus outbreaks into the human population. The COVID-19 (Coronavirus disease 2019) pandemic is caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and emerged as a global threat endangering the livelihoods of millions worldwide. Currently, and despite collaborative efforts, diverse therapeutic strategies from ongoing clinical trials are still debated. To address the need for such an immediate call of action, we leveraged the largest dataset of drug-induced transcriptomic perturbations, public SARS-CoV-2 transcriptomic datasets, and expression profiles from normal lung transcriptomes. Most importantly, our unbiased systems biology approach prioritized more than 50 repurposable drug candidates (e.g., Corticosteroids, Janus kinase and Bruton kinase inhibitors). Further clinical investigation of these FDA approved candidates as monotherapy or in combination with an antiviral regimen (e.g., Remdesivir) could lead to promising outcomes in COVID-19 patients., Graphical Abstract, Highlights A large repertoire of drug repurposing across SARS-CoV-2 transcriptomic settings Pathway enrichment revealed TNF-NFkB signaling as a targetable hallmark for COVID-19 Drug enrichment identified BTK inhibitors as repurposable candidates for COVID-19 Identified drug candidates warrant investigation in models of SARS-CoV-2 infection

Summary Genomic instability affects the reproducibility of experiments that rely on cancer cell lines. However, measuring the genomic integrity of these cells throughout a study is a costly endeavor that is commonly forgone. Here, we validate the identity of cancer cell lines in three pharmacogenomic studies and screen for genetic drift within and between datasets. Using SNP data from these datasets encompassing 1,497 unique cell lines and 63 unique pharmacological compounds, we show that genetic drift is widely prevalent in almost all cell lines with a median of 4.5%–6.1% of the total genome size drifted between any two isogenic cell lines. This study highlights the need for molecular profiling of cell lines to minimize the effects of passaging or misidentification in biomedical studies. We developed the CCLid web application, available at www.cclid.ca, to allow users to screen the genomic profiles of their cell lines against these datasets. A record of this paper's transparent peer review process is included in the Supplemental Information.

T-box (TBX) transcription factors are evolutionary conserved genes and master transcriptional regulators. In mammals, TBX2 subfamily (TBX2, TBX3, TBX4, and TBX5) genes are expressed in the developing lung bud and tracheae. Our group previously showed that the expression of TBX2 subfamily was significantly high in human normal lungs, but markedly suppressed in lung adenocarcinoma (LUAD). To further elucidate their role in LUAD pathogenesis, we first confirmed abundant expression of protein products of the four members by immunostaining in adult human normal lung tissues. We also found overall suppressed expression of these genes and their corresponding proteins in a panel of human LUAD cell lines. Transient over-expression of each of the genes in human (NCI-H1299), and mouse (MDA-F471) derived lung cancer cells was found to significantly inhibit growth and proliferation as well as induce apoptosis. Genome-wide transcriptomic analyses on NCI-H1299 cells, overexpressing TBX2 gene subfamily, unraveled novel regulatory pathways. These included, among others, inhibition of cell cycle progression but more importantly activation of the histone demethylase pathway. When using a pattern-matching algorithm, we showed that TBX's overexpression mimic molecular signatures from azacitidine treated NCI-H1299 cells which in turn are inversely correlated to expression profiles of both human and murine lung tumors relative to matched normal lung. In conclusion, we showed that the TBX2 subfamily genes play a critical tumor suppressor role in lung cancer pathogenesis through regulating its methylating pattern, making them putative candidates for epigenetic therapy in LUAD.

T-box (TBX) transcription factors are evolutionary conserved genes and master transcriptional regulators. In mammals, TBX2 subfamily (TBX2, TBX3, TBX4, and TBX5) genes are expressed in the developing lung bud and tracheae. Our group previously showed that the expression of TBX2 subfamily was significantly high in human normal lungs, but markedly suppressed in lung adenocarcinoma (LUAD). To further elucidate their role in LUAD pathogenesis, we first confirmed abundant expression of protein products of the four members by immunostaining in adult human normal lung tissues. We also found overall suppressed expression of these genes and their corresponding proteins in a panel of human LUAD cell lines. Transient over-expression of each of the genes in human (NCI-H1299), and mouse (MDA-F471) derived lung cancer cells was found to significantly inhibit growth and proliferation as well as induce apoptosis. Genome-wide transcriptomic analyses on NCI-H1299 cells, overexpressing TBX2 gene subfamily, unraveled novel regulatory pathways. These included, among others, inhibition of cell cycle progression but more importantly activation of the histone demethylase pathway. When using a pattern-matching algorithm, we showed that TBX's overexpression mimic molecular signatures from azacitidine treated NCI-H1299 cells which in turn are inversely correlated to expression profiles of both human and murine lung tumors relative to matched normal lung. In conclusion, we showed that the TBX2 subfamily genes play a critical tumor suppressor role in lung cancer pathogenesis through regulating its methylating pattern, making them putative candidates for epigenetic therapy in LUAD.

Despite an obvious role for consanguinity in congenital heart disease (CHD), most studies fail to document a monogenic model of inheritance except for few cases. We hereby describe a first-degree cousins consanguineous Lebanese family with 7 conceived children: 2 died in utero of unknown causes, 3 have CHD, and 4 have polydactyly. The aim of the study is to unveil the genetic variant(s) causing these phenotypes using next generation sequencing (NGS) technology. Targeted exome sequencing identified a heterozygous duplication in CSRP1 which leads to a potential frameshift mutation at position 154 of the protein. This mutation is inherited from the father, and segregates only with the CHD phenotype. The in vitro characterization demonstrates that the mutation dramatically abrogates its transcriptional activity over cardiac promoters like NPPA. In addition, it differentially inhibits the physical association of CSRP1 with SRF, GATA4, and with the newly described partner herein TBX5. Whole exome sequencing failed to show any potential variant linked to polydactyly, but revealed a novel missense mutation in TRPS1. This mutation is inherited from the healthy mother, and segregating only with the cardiac phenotype. Both TRPS1 and CSRP1 physically interact, and the mutations in each abrogate their partnership. Our findings add fundamental knowledge into the molecular basis of CHD, and propose the di-genic model of inheritance as responsible for such malformations.

Background Genome-wide expression profiling is increasingly being used to identify transcriptional changes induced by drugs and environmental stressors. In this context, the Toxicogenomics Project–Genomics Assisted Toxicity Evaluation system (TG-GATEs) project generated transcriptional profiles from rat liver samples and human/rat cultured primary hepatocytes exposed to more than 100 different chemicals. Objectives To assess the capacity of the cell culture models to recapitulate pathways induced by chemicals in vivo, we leveraged the TG-GATEs data set to compare the early transcriptional responses observed in the liver of rats treated with a large set of chemicals with those of cultured rat and human primary hepatocytes challenged with the same compounds in vitro. Methods We developed a new pathway-based computational pipeline that efficiently combines gene set enrichment analysis (GSEA) using pathways from the Reactome database with biclustering to identify common modules of pathways that are modulated by several chemicals in vivo and in vitro across species. Results We found that some chemicals induced conserved patterns of early transcriptional responses in in vitro and in vivo settings, and across human and rat genomes. These responses involved pathways of cell survival, inflammation, xenobiotic metabolism, oxidative stress, and apoptosis. Moreover, our results support the transforming growth factor beta receptor (TGF-βR) signaling pathway as a candidate biomarker associated with exposure to environmental toxicants in primary human hepatocytes. Conclusions Our integrative analysis of toxicogenomics data provides a comprehensive overview of biochemical perturbations affected by a large panel of chemicals. Furthermore, we show that the early toxicological response occurring in animals is recapitulated in human and rat primary hepatocyte cultures at the molecular level, indicating that these models reproduce key pathways in response to chemical stress. These findings expand our understanding and interpretation of toxicogenomics data from human hepatocytes exposed to environmental toxicants. Citation El-Hachem N, Grossmann P, Blanchet-Cohen A, Bateman AR, Bouchard N, Archambault J, Aerts HJ, Haibe-Kains B. 2016. Characterization of conserved toxicogenomic responses in chemically exposed hepatocytes across species and platforms. Environ Health Perspect 124:313–320; http://dx.doi.org/10.1289/ehp.1409157

Summary: Pharmacogenomics holds great promise for the development of biomarkers of drug response and the design of new therapeutic options, which are key challenges in precision medicine. However, such data are scattered and lack standards for efficient access and analysis, consequently preventing the realization of the full potential of pharmacogenomics. To address these issues, we implemented PharmacoGx, an easy-to-use, open source package for integrative analysis of multiple pharmacogenomic datasets. We demonstrate the utility of our package in comparing large drug sensitivity datasets, such as the Genomics of Drug Sensitivity in Cancer and the Cancer Cell Line Encyclopedia. Moreover, we show how to use our package to easily perform Connectivity Map analysis. With increasing availability of drug-related data, our package will open new avenues of research for meta-analysis of pharmacogenomic data. Availability and implementation: PharmacoGx is implemented in R and can be easily installed on any system. The package is available from CRAN and its source code is available from GitHub. Contact: bhaibeka@uhnresearch.ca or benjamin.haibe.kains@utoronto.ca Supplementary information: Supplementary data are available at Bioinformatics online.

In 2013, we published a comparative analysis of mutation and gene expression profiles and drug sensitivity measurements for 15 drugs characterized in the 471 cancer cell lines screened in the Genomics of Drug Sensitivity in Cancer (GDSC) and Cancer Cell Line Encyclopedia (CCLE). While we found good concordance in gene expression profiles, there was substantial inconsistency in the drug responses reported by the GDSC and CCLE projects. We received extensive feedback on the comparisons that we performed. This feedback, along with the release of new data, prompted us to revisit our initial analysis. We present a new analysis using these expanded data, where we address the most significant suggestions for improvements on our published analysis — that targeted therapies and broad cytotoxic drugs should have been treated differently in assessing consistency, that consistency of both molecular profiles and drug sensitivity measurements should be compared across cell lines, and that the software analysis tools provided should have been easier to run, particularly as the GDSC and CCLE released additional data. Our re-analysis supports our previous finding that gene expression data are significantly more consistent than drug sensitivity measurements. Using new statistics to assess data consistency allowed identification of two broad effect drugs and three targeted drugs with moderate to good consistency in drug sensitivity data between GDSC and CCLE. For three other targeted drugs, there were not enough sensitive cell lines to assess the consistency of the pharmacological profiles. We found evidence of inconsistencies in pharmacological phenotypes for the remaining eight drugs. Overall, our findings suggest that the drug sensitivity data in GDSC and CCLE continue to present challenges for robust biomarker discovery. This re-analysis provides additional support for the argument that experimental standardization and validation of pharmacogenomic response will be necessary to advance the broad use of large pharmacogenomic screens.

Medical imaging can visualize characteristics of human cancer noninvasively. Radiomics is an emerging field that translates these medical images into quantitative data to enable phenotypic profiling of tumors. While radiomics has been associated with several clinical endpoints, the complex relationships of radiomics, clinical factors, and tumor biology are largely unknown. To this end, we analyzed two independent cohorts of respectively 262 North American and 89 European patients with lung cancer, and consistently identified previously undescribed associations between radiomic imaging features, molecular pathways, and clinical factors. In particular, we found a relationship between imaging features, immune response, inflammation, and survival, which was further validated by immunohistochemical staining. Moreover, a number of imaging features showed predictive value for specific pathways; for example, intra-tumor heterogeneity features predicted activity of RNA polymerase transcription (AUC = 0.62, p=0.03) and intensity dispersion was predictive of the autodegration pathway of a ubiquitin ligase (AUC = 0.69, p

Computational docking and scoring techniques have revolutionized structural bioinformatics by providing unprecedented insights on key aspects of ligand-receptor interaction. Docking is used for optimizing known drugs and for identifying novel binders by predicting their binding mode and affinity. AutoDock and AutoDockTools are free of charge techniques that have been extensively cited in the literature as essential tools in structure-based drug design. Moreover, these methods are fast enough to permit virtual screening of ligand libraries containing tens of thousands of compounds. However using Autodock requires some knowledge in programming which creates a limitation for biologists and makes them prone for commercial applications. Here, we selected a relevant target involved in the progression of Alzheimer disease and provided a fully reproducible docking protocol. This example will show how docking techniques would be an important asset to identify new BACE1 inhibitors. The following friendly user tutorial targets both undergraduate and graduate students, allowing them to understand docking as a computational tool for structure-based drug design.

Congenital heart disease is the leading cause of death in the first year of life. Mutations only in few genes have been linked to some cases of CHD. Thalidomide was used by pregnant women for morning sickness but was removed from the market because it caused severe malformations including CHDs. We used both in silico docking software, and in vitro molecular and biochemical methods to document a novel interaction involving Thalidomide, TBX5, and HAND2. Thalidomide binds readily to TBX5 through amino acids R81, R82, and K226 all implicated in DNA binding. It reduces TBX5 binding to DNA by 40%, and suppresses TBX5 mediated activation of the NPPA and VEGF promoters by 70%. We documented a novel interaction between TBX5 and HAND2, and showed that a p.G202V HAND2 variant associated with CHD and coronary artery diseases found in a large Lebanese family with high consanguinity, drastically inhibited this interaction by 90%. Similarly, thalidomide inhibited the TBX5/HAND2 physical interaction, and the in silico docking revealed that the same amino acids involved in the interaction of TBX5 with DNA are also involved in its binding to HAND2. Our results establish a HAND2/TBX5 pathway implicated in heart development and diseases.

Stratifying healthy and malignant phenotypes and identifying their biological states using high-throughput molecular data has been the focus of many computational approaches during the last decade. Using multivariate changes in expression of genes within biological pathways, as fingerprints of complex phenotypes, we developed a new methodology for Similarity Identification in Gene expressioN (SIGN). In this approach, we use centroid classifier to identify phenotype of each biological sample. To obtain similarity of a given biological sample with classes of phenotypes, we defined a new distance measure, transcriptional similarity coefficient (TSC) which captures similarity of gene expression patterns between a biological pathway in two samples or populations. We showed that TSC, as an interpretable and stable distance measure in SIGN, captures all oncogenic hallmarks for breast cancer even with low sample size, by comparing healthy and patient tumor samples in the largest breast cancer dataset. In this study, we demonstrate that SIGN is a flexible, yet robust approach for classification based on transcriptomics data. Comparing early and late relapses within each molecular subtypes of breast cancer, our method enabled subtype-specific stratification of breast cancer patients into groups with significantly different survival. Moreover, we used SIGN to classify with more than 99% specificity the site of extraction of healthy and tumor samples from the Genotype-Tissue Expression (GTEx) and The Cancer Genome Atlas (TCGA) datasets. We showed that SIGN also enables robust identification of hematopoietic stem cell and progenitors within the hematopoietic hierarchy. We further explored chemical perturbation data in the Connectivity Map (CMAP) database and showed that SIGN was able to classify seven classes of drugs based on their mechanism of action. In conclusion, we showed that SIGN can be used to achieve interpretable and robust transcriptomic-based classification of healthy and malignant samples, as well as drugs based on their known mechanism of action, supporting the generalizability and relevance of the method for the analysis of gene expression profiles.

Identification of drug targets and mechanism of action (MoA) for new and uncharacterized anticancer drugs is important for optimization of treatment efficacy. Current MoA prediction largely relies on prior information including side effects, therapeutic indication, and chemoinformatics. Such information is not transferable or applicable for newly identified, previously uncharacterized small molecules. Therefore, a shift in the paradigm of MoA predictions is necessary toward development of unbiased approaches that can elucidate drug relationships and efficiently classify new compounds with basic input data. We propose here a new integrative computational pharmacogenomic approach, referred to as Drug Network Fusion (DNF), to infer scalable drug taxonomies that rely only on basic drug characteristics toward elucidating drug–drug relationships. DNF is the first framework to integrate drug structural information, high-throughput drug perturbation, and drug sensitivity profiles, enabling drug classification of new experimental compounds with minimal prior information. DNF taxonomy succeeded in identifying pertinent and novel drug–drug relationships, making it suitable for investigating experimental drugs with potential new targets or MoA. The scalability of DNF facilitated identification of key drug relationships across different drug categories, providing a flexible tool for potential clinical applications in precision medicine. Our results support DNF as a valuable resource to the cancer research community by providing new hypotheses on compound MoA and potential insights for drug repurposing. Cancer Res; 77(11); 3057–69. ©2017 AACR.

Computational docking and scoring techniques have revolutionized structural bioinformatics by providing unprecedented insights on key aspects of ligand-receptor interaction. Docking is used for optimizing known drugs and for identifying novel binders by predicting their binding mode and affinity. AutoDock and AutoDockTools are free of charge techniques that have been extensively cited in the literature as essential tools in structure-based drug design. Moreover, these methods are fast enough to permit virtual screening of ligand libraries containing tens of thousands of compounds. However using Autodock requires some knowledge in programming which creates a limitation for biologists and makes them prone for commercial applications. Here, we selected a relevant target involved in the progression of Alzheimer disease and provided a fully reproducible docking protocol. This example will show how docking techniques would be an important asset to identify new BACE1 inhibitors. The following friendly user tutorial targets both undergraduate and graduate students, allowing them to understand docking as a computational tool for structure-based drug design.