METHODS AND COMPOUNDS FOR THE TREATMENT OR PREVENTION OF SEVERE INFLUENZA

Abstract

A p38 MAPK inhibitor for use in the treatment or prevention of severe influenza in a human patient. In some embodiments, the severe influenza may be characterised by hypercytokinemia involving elevated levels of one or more pro-inflammatory cytokines. The p38 MAP kinase inhibitor may act to inhibit the release of such pro-inflammatory mediators from endothelial cells. In some embodiments, the p38 MAP kinase inhibitor may inhibit the release of IP 10 from endothelial cells, preferably in a dose-dependent manner.

Claims

1. A p38 MAPK inhibitor for use in the treatment or prevention of severe influenza in a human patient.

2. A p38 MAPK inhibitor for use as claimed in claim 1, wherein said severe influenza is characterised by hypercytokinemia.

3. A p38 MAPK inhibitor for use as claimed in claim 2, wherein said hypercytokinemia involves elevated levels of one or more cytokines selected from TNFα, IL-6, IL-8 and IP10.

4. A p38 MAP kinase inhibitor for use as claimed in any preceding claim, which inhibits the release of pro-inflammatory mediators from endothelial cells.

5. A p38 MAP kinase inhibitor for use as claimed in claim 4, which inhibits the release of pro-inflammatory cytokines from endothelial cells.

6. A p38 MAP kinase inhibitor for use as claimed in claim 4 or 5, which inhibits the release of IP10 from endothelial cells.

7. A p38 MAP kinase inhibitor for use as claimed in claim 5 or 6, which exhibits dose-dependent inhibition of cytokine release from endothelial cells.

8. A p38 MAP kinase inhibitor for use as claimed in any preceding claim, which inhibits the release of pro-inflammatory cytokines from immune cells.

9. A p38 MAPK inhibitor for use as claimed in any preceding claim, wherein said severe influenza is characterised by symptoms or signs of hypoxemia or cardiopulmonary insufficiency.

10. A p38 MAPK inhibitor for use as claimed in claim 9, wherein said symptoms or signs of hypoxemia or cardiopulmonary insufficiency include one or more of dyspnoea, tachypnoea, cyanosis, low blood pressure and hypoxia.

11. A p38 MAPK inhibitor for use as claimed in claim 10, wherein said severe influenza is characterised by tachypnoea (respiratory rate ≥30 for ages ≥12 years, rate ≥40 for ages 6 to 12 years, rate 45 for ages 3 to 6 years, rate ≥50 for ages 1 to 3 years.

12. A p38 MAPK inhibitor for use as claimed in claim 9, wherein said severe influenza is characterised by any discomfort with breathing or dyspnoea.

13. A p38 MAPK inhibitor for use as claimed in any preceding claim, wherein said severe influenza is characterised by comorbidity with a lower respiratory disorder without radiological pulmonary infiltrates.

14. A p38 MAPK inhibitor for use as claimed in any preceding claim, wherein said severe influenza is characterised by symptoms or signs suggesting CNS and/or peripheral neuromuscular disorders.

15. A p38 MAPK inhibitor for use as claimed in any preceding claim, wherein said severe influenza is characterised by severe dehydration.

16. A p38 MAPK inhibitor for use as claimed in any preceding claim, wherein said severe influenza is characterised by fatigue and/or lethargy.

17. A p38 MAPK inhibitor for use as claimed in any preceding claim, wherein said severe influenza is characterised by the presence of radiological pulmonary infiltrate.

18. A p38 MAPK inhibitor for use as claimed in any preceding claim, wherein said severe influenza involves evidence of sustained viral infection.

19. A p38 MAPK inhibitor for use as claimed in any preceding claim, wherein said severe influenza involves invasive secondary bacterial infection.

20. A p38 MAPK inhibitor for use as claimed in any preceding claim, wherein said severe influenza involves a lower respiratory tract disorder or inflammation.

21. A p38 MAPK inhibitor for use as claimed in any preceding claim, wherein said severe influenza is characterised by mono- or multi-organ failure or septic shock.

22. A p38 MAPK inhibitor for use as claimed in any preceding claim, wherein the patient is an infant or elderly or is a pregnant woman.

23. A p38 MAPK inhibitor for use as claimed in any preceding claim, wherein one or more underlying comorbidities predispose the patient to severe influenza.

24. A p38 MAPK inhibitor for use as claimed in any preceding claim, wherein the p38 MAP kinase inhibitor is administered to the patient for a maximum period of 1-5 days.

25. A p38 MAPK inhibitor for use as claimed in any preceding claim, wherein the p38 MAP kinase inhibitor is administered to the patient once a day.

26. A p38 MAPK inhibitor for use as claimed in any preceding claim, wherein the p38 MAP kinase inhibitor is selected from 2-(4-Chlorophenyl)-4-(fluorophenyl)-5-pyridin-4-yl-1,2-dihydropyrazol-3-one, RWJ-67657 (RW Johnson Pharmaceutical Research Institute); RDP-58 (Sangstat Medical); Scios-469 (talmapimod) (Scios, J&J); MKK3/MKK6 inhibitor (Signal Research Division); SB-210313 analogue, SB-220025 (Aventis), SB-238039, HEP-689, SB-203580 (Leo), SB-239063 (R. W. Johnson), SB-239065, SB-242235 (SmithKline Beecham Pharmaceuticals); VX-702 and VX-745 (Vertex Pharmaceuticals); AMG-548 (Amgen); Astex p38 kinase inhibitor (Bayer); BIRB-796 (Doramapimod) (Boehringer Ingelheim Pharmaceuticals); RO 4402257 (Pamapimod) (Roche, Palo Alto), Celltech p38 MAP kinase inhibitor (Celltech Group plc.); FR-167653 (Fujisawa Pharmaceutical); SB-681323 (Dilmapimod) (GlaxoSmithKline) and SB-281832 (GlaxoSmithKline plc, Scios); MAP kinase inhibitor of LEO Pharmaceuticals (LEO Pharma A/S); Merck & Co. p38 MAP kinase inhibitor (Merck research Laboratories); SC-040 and SC-XX906 (Monsanto); Novartis adenosine A3 antagonists (Novartis AG); p38 MAP kinase inhibitor (NovartisPharma AG); CP-64131 (Pfizer); CNI-1493 (Picower Institute for Medical Research); RPR-200765A (Phone-Poulenc Rorer); and Roche p38 MAP kinase inhibitor and Ro-320-1195 (Roche Bioscience), AIK-3, AKP-001 (ASKA Pharma), Antibiotic LL Z1640-2, ARRY-614, ARRY-797, AS-1940477, AVE-9940, AZD-7624, BCT-197, BIRB-1017BS, BMS-582949, CAY10571, CBS-3595, CCT-196969, CCT-241161, CDP-146, CGH 2466, CHR-3620, Chloromethiazole edisylate, CM PD-1, Doramapimod, EO 1428, FY-101C, FX-005, GSK-610677 (GlaxoSmithKline), HE-3286, HSB-13, JX 401, KC-706 (Kemia), KC-706 (ITX-5061) (iTherX Inc.), LEO-15520, LEO-1606, Losmapimod (GlaxoSmithKline), LP-590, LY-30007113, LY2228820, M L 3403, OX-27-NO, NP-202, pexmetinib, PF-03715455 (Pfizer), PH-797804 (Pfizer), PS-540446, ralimetinib, regorafenib, RO-3201195, RWJ 67657, RWJ-67657, SB 202190 (Leo), SB 203580 (Pfizer), SB 203580 hydrochloride (Pfizer), SB202190, SB202190 hydrochloride (Roche), SB-681323 (Tanabe Sciyaku), SB-856553, SC-80036, SCD-282, SCIO-323, SCIO-469, SD-06, semapimod, SKF 86002, SX 011, SYD-003, TA-5493, TAK 715 (Takeda Pharma), Tie2 Kinase Inhibitor (Tanabe Pharma), TOP-1210, TOP-1630, UR-13870 (Bristol-Myers Squibb), UR-13870 (Palau Pharma) and VGX-1027.

27. A p38 MAPK inhibitor for use as claimed in any of claims 1-25, wherein the p38 MAP kinase inhibitor is selected from 8-(2,6-difluorophenyl)-2-(1,3-dihydroxypropan-2-ylamino)-4-(4-fluoro-2-methylphenyl)pyrido[2,3-d]pyrimidin-7-one (Dilmapimod), GSK-610677 and 6-[5-(cyclopropylcarbamoyl)-3-fluoro-2-methylphenyl]-N-(2,2-dimethylpropyl)pyridine-3-carboxamide (Losmapimod).

28. A p38 MAPK inhibitor for use as claimed in any of claims 1-25, wherein the p38 MAP kinase inhibitor is selected from 5-[(2-chloro-6-fluorophenyl)acetylamino]-3-(4-fluorophenyl)-4-(4-pyrimidinyl)isoxazole (AKP-001), KC-706, (1-[5-tert-butyl-2-(3-chloro-4-hydroxyphenyl)pyrazol-3-yl]-3-[[2-[[3-[2-(2- hydroxyethylsulfanyl)phenyl]-[1,2,4]triazolo[4,3-a]pyridin-6-yl]sulfanyl]phenyl]methyl]urea) (PF-03715455), (3-[3-bromo-4-[(2,4-difluorophenyl)methoxy]-6-methyl-2-oxopyridin-1-yl]-N,4-dimethylbenzamide) (PH-797804) and RV-7031.

29. A p38 MAPK inhibitor for use as claimed in any of claims 1-25, wherein the p38 MAP kinase inhibitor is 2-methoxy-1-{4-[(4-{3-[5-(tert-butyl)-2-(p-tolyl)-2H-pyrazol-3-yl]ureido}-1-naphthyloxy)methyl]-2- pyridylamino}-1-ethanone (RV-568) or 2-methoxy-1-[4-(4-{3-[5-(tert-butyl)-2-(p-tolyl)-2H-pyrazol-3-yl]ureido}-1-naphthyloxy)-2- pyridylamino]-1-ethanone.

30. A p38 MAPK inhibitor for use as claimed in any of claims 1-25, wherein the p38 MAP kinase inhibitor is 4,6-bis(p-fluorophenyl)-2-methyl-5-(4-pyridyl)-1,2,7-triaza-2H-indene (UR-13870).

31. A pharmaceutical composition for use in the treatment or prevention of severe influenza in a human patient, the composition comprising a p38 MAPK inhibitor.

32. A method of treating or preventing severe influenza in a human patient in need thereof comprising administering to the patient a therapeutically or prophylactically effective amount of a p38 MAPK inhibitor.

33. A method as claimed in claim 32, wherein the p38 MAPK inhibitor is a p38 MAPK inhibitor as claimed in any of claims 1-30.

Description

BRIEF DESCRIPTION OF THE DRAWINGS

[0106] FIG. 1 illustrates the identification of signalling pathways.

[0107] FIG. 2 illustrates the mapping the activity of genes in IL-1, TNFα and IL-6 stimulated pathways. These cytokines are produced by influenza virus infected cells and found to be increased in the blood of people infected with influenza, particularly those hospitalised with severe influenza. The hatched lines indicate gene expression levels with lines sloping from top right to bottom left indicating upregulation (e.g. TNF-α), and lines sloping from top left to bottom right (e.g. LBP) indicating down-regulation; genes that are both upregulated and down-regulated are indicated by cross-hatching. The line spacing represents the intensity of up- or down-regulation, with more densely packed lines indicating greater activity. The maps were generated using IPA. A “route” through a pathway is defined as a single contiguous connection of proteins that extend from the plasma membrane through to the nucleus.

[0108] FIG. 3 shows an example of scoring a route through the IL-6 pathway of FIG. 2.

[0109] FIG. 4 shows three key cell types involved in the pathology of severe influenza.

[0110] FIG. 5 is a schematic of influenza ‘soup’ production and electrogenerated chemiluminescence analysis in human epithelial cells. Infected cell “soups” contain key cytokines found in clinical samples.

[0111] FIG. 6 shows Western blotting of phosphorylated P38 and HSP27 in response to viral soup application and effects of P38 inhibition in epithelial cells. Electrogenerated chemiluminescence analysis of inflammatory cytokine production in response to viral soup application, and effects of P38 inhibition in epithelial cells.

[0112] FIG. 7 shows Western blotting of phosphorylated HSP27 in response to viral soup application and effects of P38 inhibition in endothelial cells. Electrogenerated chemiluminescence analysis of inflammatory cytokine production in response to viral soup application, and effects of P38 inhibition in endothelial cells.

[0113] FIG. 8 shows Western blotting of phosphorylated HSP27 in response to viral soup application and effects of P38 inhibition in immune cells. Electrogenerated chemiluminescence analysis of inflammatory cytokine production in response to viral soup application, and effects of P38 inhibition in immune cells. Cell viability of immune cells in response to increasing concentrations of P38 inhibitor.

[0114] FIG. 9 shows electrogenerated chemiluminescence analysis of inflammatory cytokine production in response to LPS, CD-3 and viral soup application. Effects of P38 inhibition on viral soup induced inflammatory cytokine in immune cells.

[0115] FIG. 10 shows the effects of p38 and MEK inhibitors on IP10 production by HUVECs stimulated with 70% HBEC viral soup. Secreted cytokine levels were assayed by electrogenerated chemiluminescence. Statistical significance was calculated using one-way ANOVA with Dunnett's multiple comparison post hoc test.

[0116] FIG. 11 shows compound effects on IL-1b production from immune cells. Each point on the dot plot represents an individual experiment. Statistical significance was calculated using one-way ANOVA with Dunnett's multiple comparison post hoc test.

[0117] FIG. 12. shows compound effects on TNFa production from immune cells. Each point on the dot plot represents an individual experiment. Statistical significance was calculated using one-way ANOVA with Dunnett's multiple comparison post hoc test.

[0118] FIG. 13 shows compound effects on IP10 production from endothelial cells. Each point on the dot plot represents an individual experiment. Statistical significance was calculated using one-way ANOVA with Dunnett's multiple comparison post hoc test.

[0119] FIG. 14 shows compound effects on IL8 production from endothelial cells. Each point on the dot plot represents an individual experiment. Statistical significance was calculated using one-way ANOVA with Dunnett's multiple comparison post hoc test.

[0120] FIG. 15 shows the cytokine levels in 28 healthy volunteers infected with influenza virus (samples collected at Day −1 to Day 28, hollow dots) and 30 individuals hospitalised with severe influenza (stippled dots). Blood samples from the severe patients were collected between 24 and 72 hours after admission to hospital. The statistical significance of differences in cytokine levels between the infected healthy volunteers (D2 and D3) and the hospitalised patients (influenza A or B) was calculated using the Mann-Whitney U test.

EXAMPLES

Example 1: Identification of p38 MAPK by Transcriptomic Analysis

[0121] Bioinformatics analysis of transcriptomic data from blood samples collected from human volunteers and patients infected with influenza was used to map the signalling pathways activated in the human host response to influenza infection in both uncomplicated (mild and moderate) and severe influenza (see PHE Guidance on Use of Anti-Viral Agents for the Treatment and Prophylaxis of Seasonal Influenza (2015-16), version 6.0, September 2015). Human viral challenge studies were carried out and transcriptomic data from those studies were used for mapping the former, while transcriptomic data from a field-based sampling study (Hoang, L. T. et al., 2014) were used for mapping the latter. Comparison of signalling pathways identified by comparing both datasets enabled the identification of signalling pathways that are very active in severe influenza versus mild and moderate influenza. Further analysis of individual pathway components identified p38 MAPK as a key “node” in a number of these active pathways.

[0122] Healthy human volunteers were intranasally challenged with influenza A/Wisconsin/67/2005 (H3N2) (Zaas, A. K. et al., Gene expression signatures diagnose influenza and other symptomatic respiratory viral infection in humans, Cell Host Microbe, 2009; 17: 207-217 and Davenport, E. E. et al., Transcriptomic profiling facilitates classification of response to influenza challenge, J. Mol. Med., 2015; 93: 105-114) or with influenza A/Perth/16/2009 (H3N2) (internal study, not published). PAXgene™ samples of whole blood were collected from the volunteers at various time points for subsequent transcriptome analysis. Methods for influenza A/Wisconsin/67/2005 (H3N2) viral challenge, case definitions, sample collection, RNA purification and microarray analysis are as detailed in Zaas et al., 2009 and Davenport et al., 2015. Methods for influenza A/Perth/16/2009 (H3N2) viral challenge, case definitions and sample collection were as described for the Wisconsin strain except RNA purification and microarray analysis using Affymetrix HGU133 Plus 2.0 arrays were performed by Almac (https://web.archive.org/web/20160317153848/http://www.almacgroup.com/). Methods for recruiting patients with severe influenza, blood sample collection, RNA purification and microarray analysis are as detailed in Hoang et al., 2014.

[0123] Microarray data files for the Zaas et al., 2009, Davenport et al., 2015 and Hoang et al., 2014 studies were downloaded from the Gene Expression Omnibus (GEO) database (https://web.archive.org/web/20160622040853/http://www.ncbi.nlm.nih.gov/geo/) using the accession numbers GSE52428, GSE61754 and GSE61821, respectively. Microarray data (.CEL) files for the unpublished study were downloaded from Almac and stored locally for bioinformatics analysis. All four transcriptomic datasets were processed and analysed using the R (version 3.0.2.) integrated suite of software facilities for data manipulation, calculation and graphical display (https://web.archive.org/web/20160623011408/http://www.R-project.org). Quality assessment of raw microarray data was performed using statistical methods standard in the art (e.g. Heber, S. and Sick, B., Quality assessment of affymetrix genechip data, Omics, 2006; 10: 358-368). Affymetrix datasets were normalised using the Robust Multi-array Average (RMA) method [https://www.bioconductor.org/packages/3.3/bioc/manuals/affy/man/affy.pdf] and Illumina datasets were normalised using the Lumi package [https://www.bioconductor.org/packages/3.3/bioc/manuals/lumi/man/lumi.pdf]. Both packages were executed in the R environment. To facilitate annotation of probe-sets and gene names, Affymetrix chip definition files (version 17.1.0) were downloaded from the BrainArray website (https://web.archive.org/web/20160623112758/http://brainarray.mbni.med.umich.edu/Brainarra y/Database/CustomCDF/17.1.0/ensg.asp) and Illumina chip definition files (illuminaHumanv4.db) were downloaded from the Bioconductor website (https://web.archive.org/web/20151209032754/http://bioconductor.org/package/release/data/an notation/html/illuminaHumany4.db.html).

[0124] The latter files were used with microarray data from Davenport et al., 2015 and Hoang et al., 2014.

[0125] Normalised Zaas et al., 2009, Davenport et al., 2015 and Perth datasets were individually merged with the Hoang et al., 2014 dataset using the COMBAT module in the InSilicoMerging package in Bioconductor (https://web.archive.org/web/20150905151657/http://www.bioconductor.org/packages/release/bioc/html/inSilicoMerging.html). Differential gene expression analysis on merged data sets was carried out using the limma package in R (https://www.bioconductor.org/packages/3.3/bioc/vignettes/limma/inst/doc/usersguide.pdf). For pairwise comparisons only data from infected volunteers in the Zaas et al., 2009, Davenport et al., 2015 and Perth datasets were used, equating to 11, 14 and 5 subjects, respectively. From the Hoang et al., 2014 dataset only data for the three H3N2-infected severe influenza patients in the data set were used. For each merged data set two pairwise comparisons were performed to identify genes that were upregulated relative to baseline levels after infection with virus and then further upregulated in the severe patient samples:

[0126] Perth: day −1 vs day 3 and; day 3 vs Hoang et al., 2014 severe.

[0127] Zaas et al., 2009: day −1 vs 60 hours and; 60 hours vs Hoang et al., 2014 severe.

[0128] Davenport et al., 2015: day 0 vs 48 hours and; 48 hours vs Hoang et al., 2014 severe.

[0129] To maximise the number of upregulated genes that could be mapped to pathways, all genes showing fold-changes >0 were identified. Each of the 6 resulting gene lists were analysed through the use of QIAGEN's Ingenuity® Pathway Analysis (IPA®, QIAGEN Redwood City, https://web.archive.org/web/20131021061639/http://www.ingenuity.com/). This resulted in the identification of 650 signalling pathways which were reduced to 353 after the removal of 297 metabolic pathways. FIG. 1 summarises this process.

[0130] In order to interrogate the relevance of each of these signalling pathways to the pathogenesis of severe influenza, a manual scoring approach was devised to identify very active “routes” within these pathways in the complicated versus the “uncomplicated” influenza datasets. In this context “routes” are defined as contiguous connections of proteins in a canonical pathway that extend from the plasma membrane through to the nucleus. As a result, a canonical pathway may have a number of different routes through it. Using this scoring approach, routes within IPA canonical pathways were mapped directionally from the plasma membrane to the nucleus and the ‘overlay’ function in IPA was used to show gene activity. To illustrate this process an example of three pathways identified using this method is shown in FIG. 2.

[0131] Individual routes in the identified 353 pathways were manually scored for gene activity as exemplified in FIG. 3 for a route through the IL-1 canonical pathway in which:

TABLE-US-00001 TABLE 1 Nodes Up- Nodes not Pathway Route regulated up-regulated IL-6 IL6R + GP130-SHC- 81% SHC-Ras signalling GRB2-SOS-Ras-cRAF- MEK-ERK-ELK + SRF

[0132] In all, 491 routes showing ≥75% up-regulated nodes were identified (exemplified in Table 2 below). Of these, 95 routes containing >3 nodes were identified in which 100% of all the nodes in the route were upregulated in the Hoang et al., 2014 severe influenza dataset versus baseline (D-1 or D0) in the Zaas et al., 2009, Davenport et al., 2015 and Perth datasets (Table 3). Twenty-four of these 95 routes were shown to be ≥75% upregulated compared with pathways derived from the mild and moderate H3N2 and H1N1 influenza datasets from Hoang et al., 2014 (H3N2 and H1N1—mild and moderate) and Zaas et al., 2009 (H1N1—D-1 and 60 h; Table 4).

[0133] Inspection of the 95 routes highlighted a number of potentially targetable nodes from which p38MAPK was chosen because of its well characterised role in inflammation and the availability of high quality clinically tested small molecule inhibitors for use in in vitro and ex vivo studies.

TABLE-US-00002 TABLE 2 An example of route scoring analysis. Nodes↑ Pathway Route Nodes (%) ↓Nodes NFKB growth factor receptors-RAS-RAF-MEKK1-IKKa-NFKB2-RELB- 10 92 IKKB lymphogenesis NFKB IL-1R/TLR-MYD88-TYRAP-IRAP-IRAK-TRAF6-TAK1-IKKa-IKBP65- 8 93 IKKB P65NFKB-P65NFKB-inflammation Role of JAK1 and JAK3 in IL21Ralpha/IL2Rgamma-JAK3-STAT1/3/5* 4 100 cytokine signalling PI3K-AKT signalling RTK Integrin-PINCH-ILK-PI3K-PP2A-AKT-CRAF-MEK1/2-ERK1/2-P70S6K- 9 89 cell growth PI3K-AKT signalling RTK Integrin-PINCH-ILK-PI3K-PP2A-AKT-CRAF-MEK1/2-ERK 1/2-P70S6K- 9 89 cell growth PI3K-AKT signalling integrin Integrin-PINCH-ILK-PI3K-PP2A-AKT-CRAF-MEK1/2-ERK1/2-P70S6K- 9 78 cell growth NFKB TNF-TANK-TRAF-FADD-RIP-MAP3K3-IKKa-IKBP65-P65NFKB- 7 87.5 TNF-R/ P65NFKB-inflammation IKKB CNTF signalling (CNTFR-LIFR-GP130)-JAK1/2-SHP2-GRB2-SOS-RAS-CRAF-MEK1/2- 10 90 SHP2 ERK1/2-P()RSK-gene expression CNTF signalling (CNTFR-LIFR-GP130)-TYK2-STAT1/3-gene expression 3 100 role of JAK in IL-6 type (GP130-OSMR)-intermediate signalling-ERK1/2-p38MAPK-JNK-signalling 4 100 cytokine signalling role of JAK in IL-6 type (GP130-OSMR)-JAK2-STAT1/3/5-gene expression 3 100 cytokine signalling role of JAK in IL-6 type (GP130-OSMR)-STAT1/3-gene expression 2 100 cytokine signalling HER-2 signalling in breast (HER1/HER2)-GRB2-SOS-RAS-(CYCLIND1-CDK6-CYCLINE-p27KIP1)- 5 80 HER1- cancer cell cycle progression and proliferation HER2 HER-2 signalling in breast (HER1/HER2)-PI3K-AKT-CYCLIND1-cell cycle progression 4 75 HER1- cancer HER2 role of JAk1, JAK2 and TYK2 (IFNAR1-IFNAR2)-TYK2-STAT2-STAT1-gene expression 4 100 in interferon signalling IL-9 signalling (IL-9R-IL2R)-JAK3-IRS1/2-PI3K-PI3ksignalling 5 100

TABLE-US-00003 TABLE 3 Ninety-five routes containing 100% upregulated nodes in the Hoang et al., 2014 severe influenza dataset versus the Zaas et al., 2009, Davenport et al., 2015 and Perth baseline datasets. Number of Pathway Route Nodes Acute myeloid leukemia signalling FLT3-GRB2-SOS-RAS-RAF-MEK-ERK1/2-cell 7 proliferation Gaq signalling GqR-Ga/b/y-PYK2-PI3K-AKT-IKK-NFkB* 7 p38 MAPK signalling TNFR/fas-TRADD/FAD-TRAF2-Ask1-MKK4- 7 P38MAKa-CHOP-transcription p38 MAPK signalling TNFR/fas-TRADD/FAD-TRAF2-Ask1-MKK4- 7 P38MAKa-ELK1-transcription p38 MAPK signalling TNFR/fas-TRADD/FAD-TRAF2-Ask1-MKK4- 7 P38MAPKa-MEF2 SAPK/JNK signalling TRADD/RIP/FADD-TRAF2-GCKs-MEKK1- 7 MKK4/7-JNK-ELK-1* Sertoli cell sertoli cell junction CLDN-ZO2-factin-actinin alpha-tubulin-KEAP1- 7 signalling Myo7a-junction dynamics HIF1a signalling RTK-PI3K-AKT-HIF1a-ARNT-ET1-vascular 6 tone* HIF1a signalling RIK-PI3K-AKT-HIF1a-ARM-MMPs-ECM 6 regulation* IL6 signalling TNFR-TRAF2-TAK1-MKK4/7-JNK-ELK1* 6 Protein Kinase A signalling PKAr/PKAc-RAP1-BRAF-MEK1/2-ERK1/2- 6 ELK1* SAPK/JNK signalling TRADD/RIP/FADD-TRAF2-ASK1-MKK4/7- 6 JNK-ELK-1* ERK5 signalling SRC-MEKK2/3-MEK5-ERK5-SAP1* 5 Glucocorticoid Receptor CYTOKINE RECEPTOR-TRAF2-TAK1- 5 signalling MKK4/7-P38MAPK-STABILIZATION OF MRNA, TRANSLATION* Growth Hormone signalling GHR-JAK2-ERK1/2-CEBPA* 5 Growth Hormone signalling GHR-JAK2-ERK1/2-P90RSK-SRF/ELK1* 5 HIF1a signalling RTK-PI3K-AKT-HIF1a-ARNT-GLUT* 5 HIF1a signalling RTK-PI3K-AKT-HIF1a-ARNT-VEGF* 5 IL-22 signalling IL22R1/2-TYK2-STAT1/3/5-SOCS3* 5 IL-8 CXCR1/2-PI3K-Akt-AP1-IntegrinAlphavBeta3 5 (Chemotaxis) IL-8 CXCR1/2-Ras-Raf-MEK1/2-ERK1/2- 5 (Neutrophil Degranulation) leptin sigalling in obesity LEPR-JAK2-STAT3-(SOCS3-POMC)-aMSH- 5 anorexia Paxillin signalling Integrina/b-FAK-GRB2-SOS-Ras-ERK/MAPK* 5 Role of RIG like receptors in dsRNA-RIG1-IPS1-rRAF3-rBK1-IRF7-(IFNa- 5 antiviral innate immunity MDA5/LGP2/R1G1)* Role of RIG like receptors in MDA5-IPS1-TRAF3-TBK1-IRF7-(IFNa- 5 antiviral innate immunity MDA5/LGP2/RIG1)* Role of RIG like receptors in TRIM25-RIG1-IPS1-TRAF3-IRF7-(IFNa- 5 antiviral innate immunity MDA5/LGP2/RIG1)* CD40 signalling CD40-JAK3-STAT3-ICAM1* 4 ceramide signalling EDG-SPHK-NFKB-AP1-activation of 4 inflammatory genes ceramide signalling SMPD-(ceramide)-PI3K-AKT-apoptosis * 4 Eicosanoid signalling PLA2-ALOX5-LTA4h-LTB4R- 4 chemotaxis/proliferation/allergic asthma/angiogenesis/ G alpha I signalling GiCOUPLED RECEPTOR- 4 Galphai/Gbcta/Ggamma-SRC-STAT3* Germ Cell-Sertoli Cell Junction TGFbetaR-RAS-MEK1/2-ERK1/2-actin 4 signalling depolymerisation* GM-CSF signalling GMCSFRA-HCK-PI3K-AKT-cell survival/cell 4 proliferation* GM-CSF signalling GMCSFRA-JAK2-STAT3-(BCLXL- 4 CYCLIND1)* G-Protein Coupled Receptor Gicoupled receptor-GALPHAi/0-SRC-STAT3 * 4 signalling IGF-1 signalling IGF1R-JAK1/2-STAT3-SOCS3* 4 IL-8 CXCR1/2-JNK-NFkB-ICAM-1 IL-8 CXCR1/2-PI3K-MEK1/2-ERK1/2-(Neutrophil 4 Degranulation) IL-8 CXCR1/2-Rho-NFkB-ICAM-1 4 JAK/STAT cytokine receptor-JAK-STAT-(CFOS-IL6-SOCS- 4 BCLXL)* MSP-RON signalling pathway RON-PI3K-PKC zeta-F-ACTIN-phagocytic 4 activity in macrophages* PI3K signalling in B Lymphocytes IL4R-IRS-P85/PI3K-P110/PI3K-NFKB 4 PPARα/RXRα Activation ADIPOR-AMPK-P38MAPK-PPARalpha 4 Production of nitric oxide and TLR2/4-PI3K-AKT-NFKB-Inos 4 ROS in macrophages Production of nitric oxide and TLR2/4-MKK4/-JNK-AP1 4 ROS in macrophages RAR activation IL-3Ra/b-JAK2-STAT5-RAR/RXR* 4 Role of MAPK signalling in the ASK-1-MKK4/7-JNK-CASP3-APOPTOSIS 4 Pathogenesis of Influenza Role of RIG like receptors in dsRNA-R1G1-IPS1-TRAF3-IRF7-(IFNa- 4 antiviral innate immunity MDA5/LGP2/RIG1)* Role of RIG like receptors in MDA5-IPS1-TRAF3-IRF7-(IFNa- 4 antiviral innate immunity MDA5/LGP2/RIG1)* signalling by Rho Family GTPases Integrin-ARHGEF-RHO-FAK-cytoskeletal 4 reorganisation* signalling by Rho Family GTPases Integrin-ARHGEF-RHO-PKNI-cell trafficking* 4 Sphingosine-1-phosphate signalling SIPR(2/3/4)-GAI-PI3K-AKT-CELL SURVIVAL* 4 Tec Kinase signalling Integrin-FAK-TEC KINASE- 4 (FAK, PKC, PAK, VAV, FACTIN, RHOGTPASE, NFKB, JNK, STAT-TFII-1*) Tec Kinase signalling TCR-SRC-TEC KINASE- 4 (FAK, PKC, PAK, VAV, FACTIN, RHOGTPASE, NFKB, JNK, STAT-TFII-1*) Acute myeloid leukemia signalling FLT3-STAT3/5-PIM1-regulates apoptosis 3 Antioxidant action of vitamin C CSF2Ralpha/beta-JAK2-STAT5-gene expression* 3 CNTF signalling (CNTFR-LIFR-GP130)-TYK2-STAT1/3-gene 3 expression* Dendritic Cell Maturation LTbctaR-IKK-RELB/NFKB-cross presentation 3 EPHRIN RECEPTOR signalling EPHA-JAK2-STAT3-CELL PROLIFERATION* 3 EPHRIN RECEPTOR signalling EPHB-PI3KG-AKT-CELL MIGRATION, CELL 3 PROLIFERATION EPHRIN RECEPTOR signalling INTEGRIN-MEK1/2-ERK1/2-AXON 3 GUIDANCE,CELL PROLIFERATION* FcyRIIB signalling in B FCyR-BTK-JNK-apoptosis* 3 lymphocytes Glucocorticoid Receptor signalling CYTOKINE RECEPTOR-JAK2-STAT1* 3 Glucocorticoid Receptor signalling CYTOKINE RECEPTOR-JAK3-STAT3/5* 3 GNRH signalling GnRHR-Gai-NfkB 3 IL-12 signalling and Production in TLR4-p38/MAPK-IL12 3 Macrophages IL-3 signalling IL3Ralpha/beta-JAK1/2-STAT1/3/5/6-gene 3 expression* IL6 signalling GP130 (IL6R)-JAK2-STAT3-gene expression* 3 IL-8 CXCR1-PLD-NADPH oxidase-(Superoxide 3 production-Respiratory Burst) IL-8 CXCR1-G Protein alpha/beta/gamma-PI3Ky- 3 (Chemotaxis-Respiratory Burst)* LPS stimulated MAPK signalling TLR4-IKK-IKB-NFKB-gene expression* 3 mTOR signalling Nutrients-RHEB-mTORc2-AKT-PI3K/AKT 3 signalling* mTOR signalling Nutrients-RHEB-mTORc2-AKT-(Rho/PKC)- 3 actin organisation PDGF signalling PDGFRa/b-SPHK-CRK-mitogenesis* 3 Protein Kinase A signalling PKA-PHK-PYG-glycolysis* 3 Regulation of cellular mechanics by CNG-CALPAIN-RB 3 calpain protease role of JAK in IL-6 type cytokine (GP130-OSMR)-JAK2-STAT1/3/5-gene 3 signalling expression* Role of JAK2 in Hormone-like GHR-JAK2-IRS-PI3K/AKT SIGNALLING* 3 cytokine signalling Role of JAK2 in Hormone-like GHR-JAK2-STAT1/3-GENE EXPRESSION* 3 cytokine signalling Role of JAK2 in Hormone-like GHR-JAK2-STATS-GENE EXPRESSION* 3 cytokine signalling Role of Macrophages, Fibroblasts GP130-JAK2-STAT3-gene expression* 3 and Endothelial Cells in Rheumatoid Arthritis Role of Pattern Recognition NALP3-casp1-IL1b* 3 Receptors in Recognition of Bacteria and Viruses Role of Pattern Recognition NOD1-Casp1-IL1b* 3 Receptors in Recognition of Bacteria and Viruses Role of PI3K/AKT signalling in the PI3K-AKT-IKB, NFKB 3 Pathogenesis of Influenza Role of tissue factor in cancer PAR2-ERK1/2-HBEGF-angiogenesis 3 Role of tissue factor in cancer PAR2-ERK1/2-VEGFa-angiogenesis 3 Role of tissue factor in cancer PAR2-p38/MAPK-uPar-tumour invasion 3 Role of tissue factor in cancer PAR2-p38/MAPK-IL-1b-angiogenesis 3 Role of tissue factor in cancer PAR2-p38/MAPK-VEGFa-angiogenesis 3 STAT3 pathway cytokine receptors-TYK2/JAK2-STAT3- 3 transcription-immune response-proliferation- survival* STAT3 pathway GFR-JAK2/SRC-STAT3-transcription-immune 3 response-proliferation-survival * Synaptic long term depression AMPAR-Lyn-PKC-Phosphorylation* 3 Tec Kinase signalling FCeR1-TEC kinase- 3 (FAK, PKC, PAK, VAV, FACTIN, RHOGTPASE, NFKB, JNK, STAT-TFII-1*) Tec Kinase signalling TLR4-TEC kinase- 3 (FAK, PKC, PAK, VAV, FACTIN, RHOGTPASE, NFKB, JNK, STAT-TFII-1*)

TABLE-US-00004 TABLE 4 Comparison of route scores between H3N2 and H1N1. H3N2 H1N1 Severe vs Severe vs Severe vs Severe vs Severe vs Severe vs Severe vs Severe vs Baseline Peak Mild Moderate Baseline Peak Mild Moderate Pathway Route H3N2 H3N2 H3N2 H3N2 H1N1 H1N1 H1N1 H1N1 Growth Hormone GHR-JAK2-ERK1/2-CEBPA* 100.00 93.33 100.00 100 75 75 75 75 signaling PPARα/RXRα ADIPOR-AMPK-P38MAPK- 100.00 100.00 100.00 100 100 100 100 75 Activation PPARalpha-REGULATION of growth hormone genes GM-CSF GMCSFRA-HCK-PI3K- 100.00 100.00 100.00 100 100 100 100 100 signaling AKT-cell survival/ cell proliferation* Sphingosine-1- SIPR(2/3/4)-GAI-PI3K-AKT- 100.00 100.00 100.00 100 100 100 100 100 phosphate signaling CELL SURVIVAL* ceramide signaling SMPD-(ceramide)-PI3K- 100.00 100.00 100.00 100 100 100 100 100 AKT-apoptosis* IL-8 CXCR1/2-PI3K-MEK1/2- 100.00 93.33 100.00 100 75 75 100 100 ERK1/2-(Neutrophil Degranulation) Paxillin signaling Integrina/b-FAK-GRB2- 100.00 100.00 100.00 100 100 100 100 100 SOS-Ras-ERK/MAPK* Tec Kinase FCeR1-TEC kinase- 100.00 100.00 100.00 100 100 100 100 100 signaling (FAK, PKC, PAK, VAV, FACTIN, RHOGTPASE, NFKB, JNK, STAT-TFII-1*) Tec Kinase TCR-SRC-TEC KINASE- 100.00 100.00 100.00 100 100 100 100 100 signaling (FAK, PKC, PAK, VAV, FACTIN, RHOGTPASE, NFKB, JNK, STAT-TFII-1*) Tec Kinase TLR4-TEC kinase- 100.00 100.00 100.00 100 100 100 100 100 signaling (FAK, PKC, PAK, VAV, FACTIN, RHOGTPASE, NFKB, JNK, STAT-TFII-1*) signaling by Rho Integrin-ARHGEF-RHO- 100.00 100.00 100.00 100 75 75 75 75 Family GTPases PKNI-celltrafficking* Regulation of CNG-CALPAIN-RB 100.00 100.00 100.00 100 100 100 100 100 cellular mechanics by calpain protease Tec Kinase Integrin-FAK-TEC KINASE- 100.00 100.00 100.00 100 100 100 100 100 signaling (FAK, PKC, PAK, VAV, FACTIN, RHOGTPASE, NFKB, JNK, STAT-TFII-1*) Acute myeloid FLT3-GRB2-SOS-RAS-RAF- 100.00 100.00 100.00 85.71 100 100 100 100 leukemia signaling MEK-ERK1/2-cell proliferation signaling by Rho Integrin-ARHGEF-RHO-FAK- 100.00 95.23 100.00 100 100 100 100 100 Family GTPases cytoskeletal reorganisation* IL-8 CXCR1/2-Ras-Raf-MEK1/2- 100.00 91.67 100.00 100 80 80 100 100 ERK1/2-(Neutrophil Degranulation) JAK/STAT cytokine receptor-JAK-STAT- 100.00 91.67 100.00 100 75 75 100 100 (CFOS-IL6-SOCS-BCLXL)* MSP-RON RON-PI3K-PKC zeta- 100.00 91.67 100.00 100 75 100 75 75 signaling F-ACTIN-phagocytic pathway activity in macrophages* Germ Cell- TGFbetaR-RAS-MEK1/2- 100.00 91.67 100.00 100 100 100 100 100 Sertoli Cell ERK1/2-actin Junction signaling depolymerisation* Role of MAPK ASK-1-MKK4/7-JNK- 100.00 83.33 100.00 100 75 75 75 75 signaling in the CASP3-APOPTOSIS Pathogenesis of Influenza Role of PI3K/AKT PI3K-AKT-IKB, NFKB 100.00 77.78 100.00 100 100 100 75 75 signaling in the Pathogenesis of Influenza Protein Kinase PKAr/PKAc-RAP1-BRAF- 100.00 100.00 83.33 83.33 100 83.33 83.33 83.33 A signaling MEK1/2-ERK1/2-ELK1* IL-8 CXCR1/2-PI3K-Akt-AP1- 100.00 80.55 80.00 100 75 80 100 100 IntegrinAlphavBeta3 (Chemotaxis) Production of nitric TLR2/4-MKK4/7-JNK-AP1 100.00 91.67 75.00 100 100 100 100 100 oxide and ROS in macrophages

Example 2: Effects of p38MAPK Inhibition on Inflammatory Mediator Release in Key Cell Types Relevant to Severe Influenza

[0134] Two p38 MAPK inhibitors were used in in vitro and ex vivo experiments: 1) PH797804, an ATP-competitive highly potent, selective and metabolically stable inhibitor of p38 (Hope HR1, et al., Anti-inflammatory properties of a novel N-phenyl pyridinone inhibitor of p38 mitogen-activated protein kinase: preclinical-to-clinical translation, Pharmacol. Exp. Ther., 2009 (December); 331(3): 882-95); and 2) Dilmapimod (SB-681323—Betts JC1, et al., Gene expression changes caused by the p38 MAPK inhibitor dilmapimod in COPD patients: analysis of blood and sputum samples from a randomized, placebo-controlled clinical trial, Pharmacol. Res. Perspect., 2015 (February); 3(1): e00094). The structures of these compounds are as follows:

##STR00004##

[0135] Experimental testing of p38MAPK inhibition was carried out in three cell types that arc key players in the pathology of severe influenza: epithelial; endothelial; and immune cells (FIG. 4).

Epithelial Cells

[0136] A549 cells (adenocarcinoma human alveolar basal epithelial cells) or HBEC (Human Bronchial

[0137] Epithelial Cells) were infected with A/Perth/16/2009(H3N2) virus from which viral conditioned media (or ‘viral soup’) was collected. In the experiments described here, the application of viral soup either back onto epithelial cells or onto the other cell types of interest (endothelial and immune) was performed in order to simulate the action of inflammatory mediators that are produced from Influenza infected epithelial cells.

[0138] For infection, high titre stocks of Influenza (H3N2) virus were produced by infection of MDCK-RVL cells (available from ATCC as MDCK (NBL-2) (ATCC® CCL-34), derived from a kidney of an apparently normal adult female cocker spaniel, September, 1958, by S. H. Madin and N. B. Darby. The line is hyperdiploid, and there is a bi-modal chromosome number distribution. There are no consistent identifiable marker chromosomes. One normal X chromosome is present in most spreads. The cells are positive for keratin by immunoperoxidase staining). MDCK-RVL cells were plated in T175 flask and allowed to grow to 85-90% confluence. The next day, cells were washed twice with infection media. The Influenza A/Perth/16/2009 (H3N2) stock was removed from −80° C. and thawed on ice. The cells were infected with virus stock at 0.01 MOI for one hour in infection media. At the end of incubation period, unbound virus was removed from the cells. The cells were washed once with infection media and overlaid with infection media and allowed to incubate for 48 hours in 37° C. at 5% CO2/air incubator. After incubation, the flasks were frozen at −80° C. for a day. Next day, the flasks were thawed at room temperature and virus supernatant was centrifuged (2000 g, 10 min) and pooled together. The virus stock was aliquoted and stored at −80° C.

[0139] Viral “soups” were prepared using the A549 cell line and primary human bronchial epithelial cells (HBECs). For the preparation of A549 soups cells were plated in a T175 flask and allowed to grow to obtain 85-90% confluence. The cells were washed twice with infection media. The Influenza A/Perth/16/2009 (H3N2)-WGC stock was removed from −80° C. and thawed on ice. The cells were infected with virus stock at 0.01 MOI for one hour in infection media. The unbound virus was removed from the cells at the end of the incubation period and cells were washed once with infection media before overlaying with infection media. The cells were incubated for 48 hours in 37° C. at 5% CO.sup.2/air incubator. After incubation, the media (‘viral soup’) was collected from all flasks, centrifuged (2000 g, 10 min) and pooled together. The viral soup was aliquoted and stored at −80° C. For the preparation of HBEC soups cells were passaged (P-3 or P-4) in T-175 flasks and infected with Influenza A/Perth/16/2009 (H3N2)-WGC stock at 0.01 MOI for one hour in HBECS infection media. Following incubation, the virus was removed and cells were washed with HBECS growth medium. The cells were then overlaid with HBECS infection medium, for 48 hours in 37° C. at 5% CO.sub.2/air incubator. At the end of incubation period, the HBEC viral soup was processed in a similar way to the A549 soup.

[0140] Viral growth kinetics were optimised for generating viral soups. To determine multistep growth curves, A549 cells or HBECs were infected with virus at an MOI of 0.01 TCID50/cell at 37° C. for one hour. Following incubation, the cells were washed and overlaid with respective infection media. The samples were harvested for viral titre and measurement of cytokines at various time points for 72 hours. The viral titres were obtained by TCID50 on MDCK cells.

[0141] Prior to experimental testing both A549 and HBEC soup preparations were evaluated by electrogenerated chemiluminescence for the presence of inflammatory mediators using methods as recommended by the vendor (https://web.archive.org/web/20160522190937/https://www.mesoscale.com/). Both soup preparations were found to contain elevated levels of the following cytokines (IL1-β, IL-6, IL-8, IL-10, TNFα and RANTES; FIG. 5).

[0142] In vitro data were generated from A549 cells to test the effect of A549 viral soup application on p38 activation as measured by western blotting of the phosphorylation status of p38MAPK itself and downstream signalling target, HSP27. For western blotting confluent cells were washed in PBS and lysed in RIPA with protease inhibitor (Sigma-P8340), phosphatase inhibitor cocktails 2 and 3 (Sigma P5726 and P0044) and phosphatase inhibitors Na3VO4 and NaF on ice. Protein concentrations were determined using the Pierce BCA Protein Assay Kit and equal concentrations of each sample created in 4×Laemmli sample buffer (BIO-RAD 161-0747) with 2-mercaptoethanol. Samples were run on a 12% gel and then transferred on to nitrocellulose. Membranes were blocked using 5% milk powder, then probed for phospho-HSP27 (Ser82) (D1H2F6) XP® Rabbit (CST #9709) or HSP27 (G31) Mouse (CST #2402). Secondary antibodies used were Peroxidase AffiniPure Goat Anti-Rabbit or Mouse IgG (H+L) (Jackson Immuno Research Laboratories 111-035-003). Membranes were stripped for re-probing using Restore™ PLUS Western Blot Stripping Buffer (Life technologies #46430). The membranes were treated with Amersham ECL Prime Western Blotting Detection Reagent (GE/Amersham #RPN2232) and imaged using ChemiDoc™ Touch Imaging System (BIO-RAD). Analysis was performed using the Image Lab software.

[0143] Induction of phosphorylation on both of these enzymes was detected indicating that p38MAPK is activated following application of A549 viral soup (FIG. 6). Furthermore, incubation with p38 MAPK inhibitors (Dilmapimod and PH 797804) was shown to dose dependently inhibit the induction of both p38MAPK and HSP27 phosphorylation by our A549 viral soup, confirming that this induction is a p38MAPK dependent process within these epithelial cells.

[0144] The effect of A549 viral soup on inflammatory cytokine production in A549 cells as measured by electrogenerated chemiluminescence was also explored. As shown in FIG. 6, A549 soup was found to induce the production of key inflammatory cytokines (IL-6 and IP-10) to a greater extent compared with control uninfected A549 soup. Application of the two p38 MAPK inhibitors on A549 cells prior to A549 viral soup application significantly attenuated release of both IL-6 and IP-10 (FIG. 6). These data demonstrate that the release of inflammatory mediators in response to A549 viral soup application on A549 cells is a p38MAPK dependent process.

Endothelial Cells

[0145] The application of HBEC viral soup on to Human Umbilical Vein Endothelial Cells (HUVECs) was performed in order to simulate the interaction of inflammatory mediators that are produced from Influenza infected epithelial cells onto endothelial cells.

[0146] In vitro data were generated from HUVEC cells to test the effect of HBEC viral soup application on p38 activation as measured by western blotting of the phosphorylation status of the p38MAPK downstream signalling target, HSP27. Induction of phosphorylation on HSP27 was detected indicating that p38MAPK is activated following application of HBEC viral soup (FIG. 5). Furthermore, pre-incubation with p38 MAPK inhibitors (Dilmapimod and PH 797804) was shown to dose dependently inhibit the induction of HSP27 phosphorylation by the HBEC viral soup, confirming that this induction is a p38MAPK dependent process within these endothelial cells.

[0147] The effect of HBEC viral soup on inflammatory cytokine production in HUVEC cells as measured by electrogenerated chemiluminescence (see methods) was also explored. As shown in FIG. 5, HBEC viral soup was found to induce the production of key inflammatory cytokines (IL-6 and IP-10) to a greater extent compared with control HBEC uninfected soup. Incubation of HUVEC cells with the two p38 MAPK inhibitors prior to HBEC viral soup application was found to significantly attenuate the HBEC viral soup induced release of both IL-6 and IP-10 (FIG. 7). These data demonstrate that the release of inflammatory mediators in response to HBEC viral soup application in HUVEC endothelial cell is a p38MAPK dependent process.

Immune Cells

[0148] The application of A549 viral soup onto human Peripheral Blood Mononuclear Cells (PBMCs) was performed in order to simulate the interaction of inflammatory mediators that are produced from Influenza infected epithelial cells onto immune cells. PBMCs were isolated according to the manufacturers recommendations (Bøyum, A., Separation of leucocytes from blood and bone marrow, Scand. J. Clin. Lab. Invest., 1968, 21, suppl. 97).

[0149] Ex vivo data were generated from immune cells to test the effect of A549 viral soup application on p38 activation as measured by Western blotting (see above for method) of the phosphorylation status of the p38MAPK downstream signalling target, HSP27. Induction of phosphorylation on HSP27 was detected, indicating that p38MAPK is activated following application of A549 viral soup (FIG. 8). Furthermore, pre-incubation with p38 MAPK inhibitors (Dilmapimod and PH 797804) was shown to dose dependently inhibit the induction of HSP27 phosphorylation by the A549 viral soup, confirming that this induction is a p38MAPK dependent process within these immune cells (FIG. 8).

[0150] The effect of A549 viral soup on inflammatory cytokine production in immune cells as measured by electrogenerated chemiluminescence (see above) was also explored. As shown in FIG. 8, A549 viral soup was found to induce the production of key inflammatory cytokines (TNFα, IL-6 and CXCL8) to a greater extent compared with control A549 uninfected soup. Pre-incubation of p38 MAPK inhibitors (Dilmapimod and PH 797804) on immune cells prior to A549 viral soup application was found to significantly attenuate the A549 viral soup induced release of TNFα, IL-1-β, IL-6 and CXCL8 (FIG. 8). These data demonstrate that the release of inflammatory mediators in response to A549 viral soup application in immune cells is a p38MAPK driven process.

[0151] Additional ex vivo data were generated from immune cells whereby the induction of inflammatory mediators in response to A549 viral soup was compared to known inflammatory stimulants (anti-CD3 and LPS). The induction of TNFα, IL-1-β, IL-6 and IL-8 by A549 viral soup was found to be greater compared with these known inflammatory stimulants (FIG. 9).

Example 3: p38 MAPK Inhibitory Activity

[0152] The enzyme inhibitory activity of a compound may be determined by fluorescence resonance energy transfer (FRET) using synthetic peptides labelled with both donor and acceptor fluorophores (Z-LYTE, Invitrogen).

[0153] Recombinant, phosphorylated p38 MAPK gamma (MAPK12:Millipore) is diluted in HEPES buffer, mixed with the candidate compound at desired final concentrations and incubated for two hours at room temperature. The FRET peptide (2 μM) and ATP (100 μM) are next added to the enzyme/compound mixture and incubated for one hour. Development reagent (protease) is added for one hour prior to detection in a fluorescence microplate reader. The site-specific protease only cleaves non-phosphorylated peptide and eliminates the FRET signal. Phosphorylation levels of each reaction are calculated using the ratio of coumarin emission (donor) over fluorescein emission (acceptor) with high ratios indicating high phosphorylation and low ratios, low phosphorylation levels. The percentage inhibition of each reaction is calculated relative to non-inhibited control, and the 50% inhibitory concentration (IC.sub.50 value) then calculated from the concentration-response curve.

[0154] For p38 MAPK alpha (MAPK14: Invitrogen), enzyme activity is evaluated indirectly by determining activation/phosphorylation of the down-stream molecule, MAPKAP-K2. The p38 MAPK a protein is mixed with its inactive target MAPKAP-K2 (Invitrogen) and the candidate compound for two hours at room temperature. The FRET peptide (2 μM), which is a phosphorylation target for MAPKAP-K2, and ATP (10 μM) are then added to the enzymes/compound mixture and incubated for one hour. Development reagent is then added and the mixture incubated for one hour before detection by fluorescence completed the assay protocol.

Example 4: P38MAPK Inhibition (p38i) Versus Inhibition of Other Potential Targets

[0155] As indicated in Example 1 above, a number of targetable nodes in the 95 pathway routes highlighted by transcriptomic and bioinformatics were identified. The compound profiling experiments in Example 2 show that p38i is effective in reducing the production of inflammatory mediator release in cell types relevant to the pathology of severe influenza. This was found not to be the case for 9 other nodes that were examined: PI3K, MEK, ERK, JNK, JAK/STAT, PKC, SRC, BtK and mTor. Drug inhibition of none of these 9 nodes gave an inhibition profile as effective as p38i in epithelial, endothelial and immune cells.

[0156] By way of example, data comparing p38i versus mitogen-activated protein kinase kinase (MEK) inhibition (MEKi) by MEK inhibitors Refametinib (Iverson C et al., RDEA119/BAY 869766: a potent, selective, allosteric inhibitor of MEK1/2 for the treatment of cancer. Cancer Res., 2009; 69: 6839-6847) and Selumetinib (Huynh H et al., Targeted inhibition of the extracellular signal-regulated kinase pathway with AZD6244 (ARRY-142886) in the treatment of hepatocellular carcinoma, Molecular Cancer Therapeutics, 2007; 6:138-146) are presented in FIG. 10 of the accompanying drawings.

##STR00005##

[0157] Neither Refametinib nor Selumetinib showed dose-dependent inhibition of IP10 production in endothelial cells stimulated with HBEC viral soup and actually appeared to increase levels of IP10 at higher drug concentrations (see FIG. 10).

[0158] A number of potential drug targets have been proposed for severe influenza (e.g. Liu Q et al., 2015 and Fedson DS, 2009). p38i was also compared versus drug compounds for a selection of these proposed targets.

[0159] For these experiments, PH797804 was benchmarked versus corticosteroid (methyl prednisolone), macrolide (Azithromycin), PPAR agonist (Pioglitazone), PDE4 inhibitor (Roflumilast), NFκB inhibitor (EVP4593) and statin (Pravastatin) at four drug concentrations (1 nM, 10 nM, 100 nM and 1000 nM) in endothelial cells (HUVECs stimulated with HBEC viral soup), or immune cells (PBMCs plus granulocytes stimulated with A549 viral soup as described in Example 2 above).

[0160] The effects of drug compound administration on IP-10, IL-8 and MCP-1 production from endothelial cells and on IL-1β, IL-6, IL-8 and TNF-α production from immune cells was assayed using electrogenerated chemiluminescence. In immune cells, corticosteroid and macrolide drug treatment showed dose-dependent inhibition of all four assayed cytokines, whereas p38i showed dose-dependent inhibition of only three of the four. The inhibitory profile of the other drugs tested was variable and did not match that of corticosteroid, macrolide, or p38i. The results are summarised in Table 5 below.

TABLE-US-00005 TABLE 5 Comparison of inhibitory effects of drug compounds for literature-proposed targets for severe influenza versus p38i. PBMCs plus granulocytes were isolated as described in Example 2 and stimulated with A549 viral soup. Secreted cytokine levels were assayed by electrogenemted chemiluminescence and IC50 and iMax values were calculated from the dose responses using non-linear regression fit using a scientific 2D graphing and statistics software package (GraphPad PRISM ® version 6.07 software). Where data did not show a dose-dependent inhibition, the IC50 and iMax values were not calculated (empty boxes). Corticosteroid p38 inhibitor Methyl Macrolide PPAR agonist PDE4 inhibitor NFkB inhibitor Statin PH797804 Prednisolone Azithromycin Pioglitazone Roflumilast QNZ (EVP4593) Pravastatin IC50 iMax IC50 iMax IC50 iMax IC50 iMax IC50 iMax IC50 iMax IC50 iMax (nM) (%) (nM) (%) (nM) (%) (nM) (%) (nM) (%) (nM) (%) (nM) (%) IL1B 9.7 79% 8.4 77% 0.5 50% IL8 2.3 87% 8.4 90% 0.8 46% 0.1 37%  0.09 31%  0.2 47% TNFa 3.9 91% 20.2  79% 86.9  63% 10.8  74% 43.6  37% IL6 36.6  57% 119    45%  0.02 41%

[0161] The inhibition plots for IL1-b and TNFα for the compounds tested are shown in FIGS. 11 and 12.

[0162] With endothelial cells, in contrast to immune cells, only p38 and NFκB inhibitors showed dose-dependent inhibition of the three cytokines assayed. None of the other drugs tested showed a comparable inhibitory effect. The results are summarised in Table 6 below.

TABLE-US-00006 TABLE 6 Comparison of inhibitory effects of drug compounds for literature-proposed targets for severe influenza versus p38i. HUVEC cells were stimulated with HBEC viral soup. Secreted cytokine levels were assayed by electrogenerated chemiluminescence and IC50 and iMax values were calculated from the dose responses using non-linear regression fit with a scientific 2D graphing and statistics software package (GraphPad PRISM ® version 6.07 software). Where data did not show a dose-dependent inhibition, the IC50 and iMax values were not calculated. Corticosteroid p38 inhibitor Methyl Macrolide PPAR agonist PDE4 inhibitor NFkB inhibitor Statin PH797804 Prednisolone Azithromycin Pioglitazone Roflumilast QNZ (EVP4593) Pravastatin IC50 iMax IC50 iMax IC50 iMax IC50 iMax IC50 iMax IC50 iMax IC50 iMax (nM) (%) (nM) (%) (nM) (%) (nM) (%) (nM) (%) (nM) (%) (nM) (%) IP10 7.5 88% 3.3 72% 78 35% IL8 28.9  86% 6.5 60% MCP1 13.1  36%  3.84 44%

[0163] The inhibition plots for IP10 and IL8 are shown in FIGS. 13 and 14.

[0164] Based on the results obtained in the immune cell experiments, the superiority of p38i versus the other drugs was unexpected, especially methyl prednisolone, which is used routinely in clinical settings to treat a range of inflammatory diseases (e.g. asthma) and is commonly prescribed for severe influenza, although there is uncertainty over their potential benefit or harm (Rodrigo C et al., Corticosteroids as adjunctive therapy in the treatment of influenza, Cochrane Database of Systematic Reviews, 2016, Issue 3. Art. No.: CD010406. DOI:10.1002/14651858.CD010406.pub2]. NFκB is downstream of p38, so the inhibition profile seen is not unexpected.

Example 5: Levels of a Number of Cytokines in Serum from Patients Hospitalised for Severe Influenza were Significantly Raised Relative to Influenza-Infected Individuals without Severe Influenza

[0165] Cytokine levels in serum samples from 30 subjects hospitalised with severe influenza during the 2015 influenza season and from 28 healthy subjects infected after intranasal inoculation with influenza A/1-I3N2 Perth/16/2009 virus were assayed using electrogenerated chemiluminescence. In the case of the former, a serum sample prepared from a blood sample collected 24-72 hours after the subject was admitted to hospital was analysed. In the case of the latter, serum was analysed from blood samples collected at 12 pre-determined intervals (Day −1 to Day 28). Eight cytokines were observed to be significantly raised in the hospitalised versus the infected healthy subjects: IL-8, IL-7, IL-16, Eotaxin, IP10, MCP1, MCP4 and VEGF. The results for four of these are shown in FIG. 15.

[0166] The results show that the hospitalised subjects are distinguishable from the healthy infected subjects in terms of their serum cytokine profiles.

ABBREVIATIONS

[0167] ATP Adenosine triphosphate

[0168] Btk Bruton's tyrosine kinase

[0169] ERK Extracellular signal-regulated kinases)

[0170] GSK Glaxo Smith-Kline

[0171] HBEC Human bronchial epithelial cells

[0172] HSP27 Heat shock protein 27

[0173] HUVEC Human vascular endothelial cells

[0174] IC50 Half maximal inhibitory concentration

[0175] iMax Maximal inhibition (as a %)

[0176] IL1-b Interleukin 1 beta

[0177] IL-6 Interleukin 6

[0178] IL-8 Interleukin 8

[0179] IPA Ingenuity Pathways Analysis

[0180] JAK/STAT Janus kinase/signal transducer and activator of transcription

[0181] JNK c-Jun N-terminal kinase

[0182] MCP-1 Monocyte chemotactic protein-1

[0183] MDCK Madin Darby canine kidney

[0184] MEK Mitogen-activated protein kinase kinase

[0185] MEKi MEK inhibition (by drug)

[0186] mTOR Mechanistic target of rapamycin

[0187] NFκB Nuclear factor kappa-light-chain-enhancer of activated B cells

[0188] P38 MAPK P38 Mitogen-activated protein kinases

[0189] P38i p38 inhibition (by drug)

[0190] PBMC Peripheral blood mononuclear cells

[0191] PDE4 Phosphodiesterase 4

[0192] PKC Protein kinase

[0193] PPAR Peroxisome proliferation-activated receptor

[0194] SRC Src kinase

[0195] TNFα Tumour necrosis factor alpha