PI3K-δ and PI3K-γ Inhibition by IPI-145 Abrogates Immune Responses and Suppresses Activity in Autoimmune and Inflammatory Disease Models

SummaryPhosphoinositide-3 kinase (PI3K)-δ and PI3K-γ are preferentially expressed in immune cells, and inhibitors targeting these isoforms are hypothesized to have anti-inflammatory activity by affecting the adaptive and innate immune response. We report on a potent oral PI3K-δ and PI3K-γ inhibitor (IPI-145) and characterize this compound in biochemical, cellular, and in vivo assays. These studies demonstrate that IPI-145 exerts profound effects on adaptive and innate immunity by inhibiting B and T cell proliferation, blocking neutrophil migration, and inhibiting basophil activation. We explored the therapeutic value of combined PI3K-δ and PI3K-γ blockade, and IPI-145 showed potent activity in collagen-induced arthritis, ovalbumin-induced asthma, and systemic lupus erythematosus rodent models. These findings support the hypothesis that inhibition of immune function can be achieved through PI3K-δ and PI3K-γ blockade, potentially leading to significant therapeutic effects in multiple inflammatory, autoimmune, and hematologic diseases

PI3Kγ is a molecular switch that controls immune suppression

Macrophages play critical, but opposite, roles in acute and chronic inflammation and cancer1,2,3,4,5. In response to pathogens or injury, inflammatory macrophages express cytokines that stimulate cytotoxic T cells, whereas macrophages in neoplastic and parasitic diseases express anti-inflammatory cytokines that induce immune suppression and may promote resistance to T cell checkpoint inhibitors1,2,3,4,5,6,7. Here we show that macrophage PI 3-kinase γ controls a critical switch between immune stimulation and suppression during inflammation and cancer. PI3Kγ signalling through Akt and mTor inhibits NFκB activation while stimulating C/EBPβ activation, thereby inducing a transcriptional program that promotes immune suppression during inflammation and tumour growth. By contrast, selective inactivation of macrophage PI3Kγ stimulates and prolongs NFκB activation and inhibits C/EBPβ activation, thus promoting an immunostimulatory transcriptional program that restores CD8+ T cell activation and cytotoxicity. PI3Kγ synergizes with checkpoint inhibitor therapy to promote tumour regression and increased survival in mouse models of cancer. In addition, PI3Kγ-directed, anti-inflammatory gene expression can predict survival probability in cancer patients. Our work thus demonstrates that therapeutic targeting of intracellular signalling pathways that regulate the switch between macrophage polarization states can control immune suppression in cancer and other disorders

Detailed stratified GWAS analysis for severe COVID-19 in four European populations

Given the highly variable clinical phenotype of Coronavirus disease 2019 (COVID-19), a deeper analysis of the host genetic contribution to severe COVID-19 is important to improve our understanding of underlying disease mechanisms. Here, we describe an extended genome-wide association meta-analysis of a well-characterized cohort of 3255 COVID-19 patients with respiratory failure and 12 488 population controls from Italy, Spain, Norway and Germany/Austria, including stratified analyses based on age, sex and disease severity, as well as targeted analyses of chromosome Y haplotypes, the human leukocyte antigen region and the SARS-CoV-2 peptidome. By inversion imputation, we traced a reported association at 17q21.31 to a ~0.9-Mb inversion polymorphism that creates two highly differentiated haplotypes and characterized the potential effects of the inversion in detail. Our data, together with the 5th release of summary statistics from the COVID-19 Host Genetics Initiative including non-Caucasian individuals, also identified a new locus at 19q13.33, including NAPSA, a gene which is expressed primarily in alveolar cells responsible for gas exchange in the lung.S.E.H. and C.A.S. partially supported genotyping through a philanthropic donation. A.F. and D.E. were supported by a grant from the German Federal Ministry of Education and COVID-19 grant Research (BMBF; ID:01KI20197); A.F., D.E. and F.D. were supported by the Deutsche Forschungsgemeinschaft Cluster of Excellence ‘Precision Medicine in Chronic Inflammation’ (EXC2167). D.E. was supported by the German Federal Ministry of Education and Research (BMBF) within the framework of the Computational Life Sciences funding concept (CompLS grant 031L0165). D.E., K.B. and S.B. acknowledge the Novo Nordisk Foundation (NNF14CC0001 and NNF17OC0027594). T.L.L., A.T. and O.Ö. were funded by the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation), project numbers 279645989; 433116033; 437857095. M.W. and H.E. are supported by the German Research Foundation (DFG) through the Research Training Group 1743, ‘Genes, Environment and Inflammation’. L.V. received funding from: Ricerca Finalizzata Ministero della Salute (RF-2016-02364358), Italian Ministry of Health ‘CV PREVITAL’—strategie di prevenzione primaria cardiovascolare primaria nella popolazione italiana; The European Union (EU) Programme Horizon 2020 (under grant agreement No. 777377) for the project LITMUS- and for the project ‘REVEAL’; Fondazione IRCCS Ca’ Granda ‘Ricerca corrente’, Fondazione Sviluppo Ca’ Granda ‘Liver-BIBLE’ (PR-0391), Fondazione IRCCS Ca’ Granda ‘5permille’ ‘COVID-19 Biobank’ (RC100017A). A.B. was supported by a grant from Fondazione Cariplo to Fondazione Tettamanti: ‘Bio-banking of Covid-19 patient samples to support national and international research (Covid-Bank). This research was partly funded by an MIUR grant to the Department of Medical Sciences, under the program ‘Dipartimenti di Eccellenza 2018–2022’. This study makes use of data generated by the GCAT-Genomes for Life. Cohort study of the Genomes of Catalonia, Fundació IGTP (The Institute for Health Science Research Germans Trias i Pujol) IGTP is part of the CERCA Program/Generalitat de Catalunya. GCAT is supported by Acción de Dinamización del ISCIII-MINECO and the Ministry of Health of the Generalitat of Catalunya (ADE 10/00026); the Agència de Gestió d’Ajuts Universitaris i de Recerca (AGAUR) (2017-SGR 529). M.M. received research funding from grant PI19/00335 Acción Estratégica en Salud, integrated in the Spanish National RDI Plan and financed by ISCIII-Subdirección General de Evaluación and the Fondo Europeo de Desarrollo Regional (European Regional Development Fund (FEDER)-Una manera de hacer Europa’). B.C. is supported by national grants PI18/01512. X.F. is supported by the VEIS project (001-P-001647) (co-funded by the European Regional Development Fund (ERDF), ‘A way to build Europe’). Additional data included in this study were obtained in part by the COVICAT Study Group (Cohort Covid de Catalunya) supported by IsGlobal and IGTP, European Institute of Innovation & Technology (EIT), a body of the European Union, COVID-19 Rapid Response activity 73A and SR20-01024 La Caixa Foundation. A.J. and S.M. were supported by the Spanish Ministry of Economy and Competitiveness (grant numbers: PSE-010000-2006-6 and IPT-010000-2010-36). A.J. was also supported by national grant PI17/00019 from the Acción Estratégica en Salud (ISCIII) and the European Regional Development Fund (FEDER). The Basque Biobank, a hospital-related platform that also involves all Osakidetza health centres, the Basque government’s Department of Health and Onkologikoa, is operated by the Basque Foundation for Health Innovation and Research-BIOEF. M.C. received Grants BFU2016-77244-R and PID2019-107836RB-I00 funded by the Agencia Estatal de Investigación (AEI, Spain) and the European Regional Development Fund (FEDER, EU). M.R.G., J.A.H., R.G.D. and D.M.M. are supported by the ‘Spanish Ministry of Economy, Innovation and Competition, the Instituto de Salud Carlos III’ (PI19/01404, PI16/01842, PI19/00589, PI17/00535 and GLD19/00100) and by the Andalussian government (Proyectos Estratégicos-Fondos Feder PE-0451-2018, COVID-Premed, COVID GWAs). The position held by Itziar de Rojas Salarich is funded by grant FI20/00215, PFIS Contratos Predoctorales de Formación en Investigación en Salud. Enrique Calderón’s team is supported by CIBER of Epidemiology and Public Health (CIBERESP), ‘Instituto de Salud Carlos III’. J.C.H. reports grants from Research Council of Norway grant no 312780 during the conduct of the study. E.S. reports grants from Research Council of Norway grant no. 312769. The BioMaterialBank Nord is supported by the German Center for Lung Research (DZL), Airway Research Center North (ARCN). The BioMaterialBank Nord is member of popgen 2.0 network (P2N). P.K. Bergisch Gladbach, Germany and the Cologne Excellence Cluster on Cellular Stress Responses in Aging-Associated Diseases, University of Cologne, Cologne, Germany. He is supported by the German Federal Ministry of Education and Research (BMBF). O.A.C. is supported by the German Federal Ministry of Research and Education and is funded by the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) under Germany’s Excellence Strategy—CECAD, EXC 2030–390661388. The COMRI cohort is funded by Technical University of Munich, Munich, Germany. This work was supported by grants of the Rolf M. Schwiete Stiftung, the Saarland University, BMBF and The States of Saarland and Lower Saxony. K.U.L. is supported by the German Research Foundation (DFG, LU-1944/3-1). Genotyping for the BoSCO study is funded by the Institute of Human Genetics, University Hospital Bonn. F.H. was supported by the Bavarian State Ministry for Science and Arts. Part of the genotyping was supported by a grant to A.R. from the German Federal Ministry of Education and Research (BMBF, grant: 01ED1619A, European Alzheimer DNA BioBank, EADB) within the context of the EU Joint Programme—Neurodegenerative Disease Research (JPND). Additional funding was derived from the German Research Foundation (DFG) grant: RA 1971/6-1 to A.R. P.R. is supported by the DFG (CCGA Sequencing Centre and DFG ExC2167 PMI and by SH state funds for COVID19 research). F.T. is supported by the Clinician Scientist Program of the Deutsche Forschungsgemeinschaft Cluster of Excellence ‘Precision Medicine in Chronic Inflammation’ (EXC2167). C.L. and J.H. are supported by the German Center for Infection Research (DZIF). T.B., M.M.B., O.W. und A.H. are supported by the Stiftung Universitätsmedizin Essen. M.A.-H. was supported by Juan de la Cierva Incorporacion program, grant IJC2018-035131-I funded by MCIN/AEI/10.13039/501100011033. E.C.S. is supported by the Deutsche Forschungsgemeinschaft (DFG; SCHU 2419/2-1).Peer reviewe

Detailed stratified GWAS analysis for severe COVID-19 in four European populations

Given the highly variable clinical phenotype of Coronavirus disease 2019 (COVID-19), a deeper analysis of the host genetic contribution to severe COVID-19 is important to improve our understanding of underlying disease mechanisms. Here, we describe an extended GWAS meta-analysis of a well-characterized cohort of 3,260 COVID-19 patients with respiratory failure and 12,483 population controls from Italy, Spain, Norway and Germany/Austria, including stratified analyses based on age, sex and disease severity, as well as targeted analyses of chromosome Y haplotypes, the human leukocyte antigen (HLA) region and the SARS-CoV-2 peptidome. By inversion imputation, we traced a reported association at 17q21.31 to a highly pleiotropic ∼0.9-Mb inversion polymorphism and characterized the potential effects of the inversion in detail. Our data, together with the 5th release of summary statistics from the COVID-19 Host Genetics Initiative, also identified a new locus at 19q13.33, including NAPSA, a gene which is expressed primarily in alveolar cells responsible for gas exchange in the lung.Andre Franke and David Ellinghaus were supported by a grant from the German Federal Ministry of Education and Research (01KI20197), Andre Franke, David Ellinghaus and Frauke Degenhardt were supported by the Deutsche Forschungsgemeinschaft Cluster of Excellence “Precision Medicine in Chronic Inflammation” (EXC2167). David Ellinghaus was supported by the German Federal Ministry of Education and Research (BMBF) within the framework of the Computational Life Sciences funding concept (CompLS grant 031L0165). David Ellinghaus, Karina Banasik and Søren Brunak acknowledge the Novo Nordisk Foundation (grant NNF14CC0001 and NNF17OC0027594). Tobias L. Lenz, Ana Teles and Onur Özer were funded by the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation), project numbers 279645989; 433116033; 437857095. Mareike Wendorff and Hesham ElAbd are supported by the German Research Foundation (DFG) through the Research Training Group 1743, "Genes, Environment and Inflammation". This project was supported by a Covid-19 grant from the German Federal Ministry of Education and Research (BMBF; ID: 01KI20197). Luca Valenti received funding from: Ricerca Finalizzata Ministero della Salute RF2016-02364358, Italian Ministry of Health ""CV PREVITAL – strategie di prevenzione primaria cardiovascolare primaria nella popolazione italiana; The European Union (EU) Programme Horizon 2020 (under grant agreement No. 777377) for the project LITMUS- and for the project ""REVEAL""; Fondazione IRCCS Ca' Granda ""Ricerca corrente"", Fondazione Sviluppo Ca' Granda ""Liver-BIBLE"" (PR-0391), Fondazione IRCCS Ca' Granda ""5permille"" ""COVID-19 Biobank"" (RC100017A). Andrea Biondi was supported by the grant from Fondazione Cariplo to Fondazione Tettamanti: "Biobanking of Covid-19 patient samples to support national and international research (Covid-Bank). This research was partly funded by a MIUR grant to the Department of Medical Sciences, under the program "Dipartimenti di Eccellenza 2018–2022". This study makes use of data generated by the GCAT-Genomes for Life. Cohort study of the Genomes of Catalonia, Fundació IGTP. IGTP is part of the CERCA Program / Generalitat de Catalunya. GCAT is supported by Acción de Dinamización del ISCIIIMINECO and the Ministry of Health of the Generalitat of Catalunya (ADE 10/00026); the Agència de Gestió d’Ajuts Universitaris i de Recerca (AGAUR) (2017-SGR 529). Marta Marquié received research funding from ant PI19/00335 Acción Estratégica en Salud, integrated in the Spanish National RDI Plan and financed by ISCIIISubdirección General de Evaluación and the Fondo Europeo de Desarrollo Regional (FEDER-Una manera de hacer Europa").Beatriz Cortes is supported by national grants PI18/01512. Xavier Farre is supported by VEIS project (001-P-001647) (cofunded by European Regional Development Fund (ERDF), “A way to build Europe”). Additional data included in this study was obtained in part by the COVICAT Study Group (Cohort Covid de Catalunya) supported by IsGlobal and IGTP, EIT COVID-19 Rapid Response activity 73A and SR20-01024 La Caixa Foundation. Antonio Julià and Sara Marsal were supported by the Spanish Ministry of Economy and Competitiveness (grant numbers: PSE-010000-2006-6 and IPT-010000-2010-36). Antonio Julià was also supported the by national grant PI17/00019 from the Acción Estratégica en Salud (ISCIII) and the FEDER. The Basque Biobank is a hospitalrelated platform that also involves all Osakidetza health centres, the Basque government's Department of Health and Onkologikoa, is operated by the Basque Foundation for Health Innovation and Research-BIOEF. Mario Cáceres received Grants BFU2016-77244-R and PID2019-107836RB-I00 funded by the Agencia Estatal de Investigación (AEI, Spain) and the European Regional Development Fund (FEDER, EU). Manuel Romero Gómez, Javier Ampuero Herrojo, Rocío Gallego Durán and Douglas Maya Miles are supported by the “Spanish Ministry of Economy, Innovation and Competition, the Instituto de Salud Carlos III” (PI19/01404, PI16/01842, PI19/00589, PI17/00535 and GLD19/00100), and by the Andalussian government (Proyectos Estratégicos-Fondos Feder PE-0451-2018, COVID-Premed, COVID GWAs). The position held by Itziar de Rojas Salarich is funded by grant FI20/00215, PFIS Contratos Predoctorales de Formación en Investigación en Salud. Enrique Calderón's team is supported by CIBER of Epidemiology and Public Health (CIBERESP), "Instituto de Salud Carlos III". Jan Cato Holter reports grants from Research Council of Norway grant no 312780 during the conduct of the study. Dr. Solligård: reports grants from Research Council of Norway grant no 312769. The BioMaterialBank Nord is supported by the German Center for Lung Research (DZL), Airway Research Center North (ARCN). The BioMaterialBank Nord is member of popgen 2.0 network (P2N). Philipp Koehler has received non-financial scientific grants from Miltenyi Biotec GmbH, Bergisch Gladbach, Germany, and the Cologne Excellence Cluster on Cellular Stress Responses in Aging-Associated Diseases, University of Cologne, Cologne, Germany. He is supported by the German Federal Ministry of Education and Research (BMBF).Oliver A. Cornely is supported by the German Federal Ministry of Research and Education and is funded by the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) under Germany's Excellence Strategy – CECAD, EXC 2030 – 390661388. The COMRI cohort is funded by Technical University of Munich, Munich, Germany. Genotyping was performed by the Genotyping laboratory of Institute for Molecular Medicine Finland FIMM Technology Centre, University of Helsinki. This work was supported by grants of the Rolf M. Schwiete Stiftung, the Saarland University, BMBF and The States of Saarland and Lower Saxony. Kerstin U. Ludwig is supported by the German Research Foundation (DFG, LU-1944/3-1). Genotyping for the BoSCO study is funded by the Institute of Human Genetics, University Hospital Bonn. Frank Hanses was supported by the Bavarian State Ministry for Science and Arts. Part of the genotyping was supported by a grant to Alfredo Ramirez from the German Federal Ministry of Education and Research (BMBF, grant: 01ED1619A, European Alzheimer DNA BioBank, EADB) within the context of the EU Joint Programme – Neurodegenerative Disease Research (JPND). Additional funding was derived from the German Research Foundation (DFG) grant: RA 1971/6-1 to Alfredo Ramirez. Philip Rosenstiel is supported by the DFG (CCGA Sequencing Centre and DFG ExC2167 PMI and by SH state funds for COVID19 research). Florian Tran is supported by the Clinician Scientist Program of the Deutsche Forschungsgemeinschaft Cluster of Excellence “Precision Medicine in Chronic Inflammation” (EXC2167). Christoph Lange and Jan Heyckendorf are supported by the German Center for Infection Research (DZIF). Thorsen Brenner, Marc M Berger, Oliver Witzke und Anke Hinney are supported by the Stiftung Universitätsmedizin Essen. Marialbert Acosta-Herrera was supported by Juan de la Cierva Incorporacion program, grant IJC2018-035131-I funded by MCIN/AEI/10.13039/501100011033. Eva C Schulte is supported by the Deutsche Forschungsgemeinschaft (DFG; SCHU 2419/2-1).N

Temperature and its impact on predation risk within aquatic ecosystems

Metabolic rates of fish and their activity levels are optimized. When environmental temperatures are below their optimum, increasing temperature will increase their rates of energy consumption resulting in a corresponding increase in the risk of starvation. For that reason we predicted that within this temperature range food is of greater value at higher temperatures so fish should be willing to incur greater costs to obtain it. To test this hypothesis we measured how the activity and foraging rates of the fathead minnow changed with temperature at 4, 15, and 24 C. As expected, fish activity and foraging were greater at higher temperatures. We then measured the impact of predation risk on foraging decisions at 5, 15, and 23 C. At 5 and 15 C the risk of predation had a significant effect on foraging decisions, but no effect at 23 C. These results demonstrate that increasing temperatures below their optimal level diminish the impact of predation risk on foraging behaviour and may mean that the direct consumptive effect of predators on aquatic communities will be greater at warmer temperatures while the risk of predation will become a less important factor, and vice versa.The accepted manuscript in pdf format is listed with the files at the bottom of this page. The presentation of the authors' names and (or) special characters in the title of the manuscript may differ slightly between what is listed on this page and what is listed in the pdf file of the accepted manuscript; that in the pdf file of the accepted manuscript is what was submitted by the author

Abrocitinib 100 mg Once Daily for Moderate-to-Severe Atopic Dermatitis: A Review of Efficacy and Safety, and Expert Opinion on Use in Clinical Practice

Abrocitinib is a Janus kinase (JAK) 1-selective inhibitor approved for the treatment of moderate-to-severe atopic dermatitis (AD). Although specific dose recommendations for abrocitinib vary across regional product labels, abrocitinib 100 mg once daily is recommended as a starting and maintenance dose. This review summarizes the efficacy and safety of abrocitinib 100 mg once daily for patients with moderate-to-severe AD based on data from the pivotal phase 3 studies of the JAK1 Atopic Dermatitis Efficacy and Safety (JADE) clinical program, JADE MONO-1 (NCT03349060), JADE MONO-2 (NCT03575871), JADE COMPARE (NCT03720470), JADE TEEN (NCT03796676), and JADE REGIMEN (NCT03627767). Preliminary long-term efficacy and safety data are also summarized from the long-term extension study JADE EXTEND (NCT03422822). Expert opinion on use of abrocitinib 100 mg once daily in clinical practice is provided. In addition to efficacy, the decision to use abrocitinib for the treatment of AD should allow for individual patient factors such as age, comorbidities, previous therapy, quality of life, and treatment tolerability, and involve shared decision-making between the patient and clinician

The phosphoinositide-3 kinase (PI3K)-δ,γ inhibitor, duvelisib shows preclinical synergy with multiple targeted therapies in hematologic malignancies.

Duvelisib is an orally active dual inhibitor of PI3K-δ and PI3K-γ in clinical development in hematologic malignancies (HM). To identify novel pairings for duvelisib in HM, it was evaluated alone and in combination with 35 compounds comprising a diverse panel of standard-of-care agents and emerging drugs in development for HM. These compounds were tested in 20 cell lines including diffuse large B-cell, follicular, T-cell, and mantle cell lymphomas, and multiple myeloma. Single agent activity was seen in fourteen cell lines, with a median GI50 of 0.59 μM. A scalar measure of the strength of synergistic drug interactions revealed a synergy hit rate of 19.3% across the matrix of drug combinations and cell lines. Synergy with duvelisib was prominent in lymphoma lines with approved and emerging drugs used to treat HM, including dexamethasone, ibrutinib, and the BCL-2 inhibitor venetoclax. Western blotting revealed that certain duvelisib-treated cell lines showed inhibition of phosphorylated (p) AKT at serine 473 only out to 12 hours, with mTORC2 dependent re-phosphorylation of pAKT evident at 24 hours. Combination with dexamethasone or ibrutinib, however, prevented this reactivation leading to durable inhibition of pAKT. The combination treatments also inhibited downstream signaling effectors pPRAS40 and pS6. The combination of duvelisib with dexamethasone also significantly reduced p-4EBP1, which controls cap dependent translation initiation, leading to decreased levels of c-MYC 6 hours after treatment. In support of the in vitro studies, in vivo xenograft studies revealed that duvelisib in combination with the mTOR inhibitor everolimus led to greater tumor growth inhibition compared to single agent administration. These data provide a rationale for exploring multiple combinations in the clinic and suggest that suppression of mTOR-driven survival signaling may be one important mechanism for combination synergy

Abrocitinib 100 mg Once Daily for Moderate-to-Severe Atopic Dermatitis: Efficacy, Safety, and Expert Opinion on Use in Clinical Practice

   The article associated with this page has been accepted for online publication and is in the final stages of production. The link to the full text will be made available on this page in the next few days. The above video abstract represents the opinions of the authors. For a full list of declarations, including funding and author disclosure statements, and copyright information, please see the full text online. (see “read the peer-reviewed publication” opposite). </p

The phosphoinositide-3 kinase (PI3K)-δ,γ inhibitor, duvelisib shows preclinical synergy with multiple targeted therapies in hematologic malignancies - Fig 3

<p><b>A Combination treatment of duvelisib plus dexamethasone or ibrutinib leads to sustained inhibition of pAKT</b>. Western blot analysis of DOHH2 (top) and SU-DHL-4 (bottom) treated with duvelisib (1 μM), dexamethasone (500 nM), ibrutinib (100nM) or the combination of duvelisib plus dexamethasone or ibrutinib for 6 hours or 24 hours and stained with pAKT (S473). <b>B. mTOR inhibition can suppress re-phosphorylation of pAKT.</b> SU-DHL-4 cells treated with duvelisib (1 μM), the pan-PI3K inhibitor GDC-0941(500 nM) or the ERK inhibitor SCH-772984 (500 nM) resulted in re-phosphorylation of pAKT (S473) at 24 hours, while combination with the PI3K/mTOR inhibitor PF-04691502 (500 nM) prevented re-phosphorylation of pAKT at 24 hours. <b>C. Re-phosphorylation of pAKT after duvelisib treatment is dependent on mTORC2</b>. DOHH2 (top) or SU-DHL-4 (bottom) treated with duvelisib (1 μM), mTOR1/2 inhibitor AZD-8055 (200 nM) or the mTORC1 inhibitor rapamycin (100 nM) for 1 hour (left) or following a 24 hour treatment with duvelisib (1 μM)(right). <b>D. Duvelisib combinations with dexamethasone and ibrutinib reduce activation of downstream effectors.</b> DOHH2 (top) and SU-DHL-4 (bottom) were treated with duvelisib, dexamethasone and ibrutinib as in Fig 3A. Western blot staining for downstream effectors pPRAS40 (T246), pP70S6K (T389) and pS6 (S235/236). <b>E. Combination of duvelisib with dexamethasone or ibrutinib leads to inhibition of cap-dependent translation</b>. DOHH2 (left) and SU-DHL-4 (right) treated as in Fig 3A and western blot stained for p4EBP1 (S65), c-MYC, peIF4E (s209) and cleaved PARP. The total eIF4E blots demonstrate that equal amounts of protein were loaded per lane.</p

Identification of compounds with anti-proliferative activity against Trypanosoma brucei brucei strain 427 by a whole cell viability based HTS campaign

Human African Trypanosomiasis (HAT) is caused by two trypanosome sub-species, Trypanosoma brucei rhodesiense and Trypanosoma brucei gambiense. Drugs available for the treatment of HAT have significant issues related to difficult administration regimes and limited efficacy across species and disease stages. Hence, there is considerable need to find new alternative and less toxic drugs. An approach to identify starting points for new drug candidates is high throughput screening (HTS) of large compound library collections. We describe the application of an Alamar Blue based, 384-well HTS assay to screen a library of 87,296 compounds against the related trypanosome subspecies, Trypanosoma brucei brucei bloodstream form lister 427. Primary hits identified against T.b. brucei were retested and the IC(50) value compounds were estimated for T.b. brucei and a mammalian cell line HEK293, to determine a selectivity index for each compound. The screening campaign identified 205 compounds with greater than 10 times selectivity against T.b. brucei. Cluster analysis of these compounds, taking into account chemical and structural properties required for drug-like compounds, afforded a panel of eight compounds for further biological analysis. These compounds had IC(50) values ranging from 0.22 µM to 4 µM with associated selectivity indices ranging from 19 to greater than 345. Further testing against T.b. rhodesiense led to the selection of 6 compounds from 5 new chemical classes with activity against the causative species of HAT, which can be considered potential candidates for HAT early drug discovery. Structure activity relationship (SAR) mining revealed components of those hit compound structures that may be important for biological activity. Four of these compounds have undergone further testing to 1) determine whether they are cidal or static in vitro at the minimum inhibitory concentration (MIC), and 2) estimate the time to kill