Fernández-Martínez JL, Álvarez O, De Andrés EJ, de la Viña JFS, Huergo L. Robust Sam- Journal of pling of Altered Pathways for Drug Repositioning Reveals Promising Novel Therapeutics for Rare Diseases Research Inclusion Body Myositis. J Rare Dis Res Treat. (2019) 4(2): 7-15 & Treatment www.rarediseasesjournal.com

Research Article Open Access

Robust Sampling of Altered Pathways for Drug Repositioning Reveals Promising Novel Therapeutics for Inclusion Body Myositis Juan Luis Fernández-Martínez*, Oscar Álvarez, Enrique J. DeAndrés-Galiana, Javier Fernández-Sánchez de la Viña, Leticia Huergo Group of Inverse Problems, Optimization and Machine Learning. Department of Mathematics. University of Oviedo, Oviedo, 33007, Asturias, Spain.

Article Info ABSTRACT

Article Notes In this paper we present a robust methodology to deal with phenotype Received: January 28, 2019 prediction problems associated to drug repositioning in rare diseases, which Accepted: April 3, 2019 is based on the robust sampling of altered pathways. We show the application *Correspondence: to the analysis of IBM (Inclusion Body Myositis) providing new insights about Dr. Juan Luis Fernández-Martínez, Group of Inverse the mechanisms involved in its development: cytotoxic CD8 T cell-mediated Problems, Optimization and Machine Learning. Department immune response and pathogenic protein accumulation in myofibrils related of Mathematics. University of Oviedo, Oviedo, 33007, to the proteasome inhibition. The originality of this methodology consists of Asturias, Spain; Email: [email protected]. performing a robust and deep sampling of the altered pathways and relating © 2019 Fernández-Martínez JL. This article is distributed under these results to possible compounds via the connectivity map paradigm. the terms of the Creative Commons Attribution 4.0 International The methodology is particularly well-suited for the case of rare diseases License. where few genetic samples are at disposal. We believe that this method for drug optimization is more effective and complementary to the target centric approach that loses efficacy due to a poor understanding of the disease mechanisms to establish an optimum mechanism of action (MoA) in the designed drugs. However, the efficacy of the list of drugs and gene targets provided by this approach should be preclinically validated and clinically tested. This methodology can be easily adapted to other rare and non-rare diseases.

Introduction Drug discovery in rare diseases is hampered by intrinsic and extrinsic factors of the drug design process, such as, the limited number of patients affected by the disease and by the increasing

targets and to bring them to the market. A disease is considered rare costs faced by the pharmaceutical companies to find new therapeutic

(in the USA) if it affecting fewer than 200,000 individuals. As result of this definition and the corresponding epidemiological studies, there are approximately 6800 rare diseases, according to the National mechanismInstitute of of Health. action Drug (MOA) discovery that provides involves an theoptimal identification therapeutic of indexnew compounds by reducing to at successfully the same timetreat the the outcomediseases, of that potential is, having side a

effects, in order to have a favorable safety and efficacy profile. The complexity of this process provokes. Although that new the drug orphan development diseases is a capital-intensive process with1 mean costs estimated to 2.8 billion dollars (DiMasi et al., 2016) collectively affect 400 million worldwide, the high developing costs with respect to the small number of affected patients have caused that these diseases were historically neglected by the drug industry. Many of the estimated 5,000 to 8,000 2rare conditions are genetic or havegene, a andgenetic phenotypic component drug (NIH, discovery 2010) . The that main measure approaches phenotypes in drug discovery include target based drug discovery to modulate a specific

Page 7 of 15 Fernández-Martínez JL, Álvarez O, De Andrés EJ, de la Viña JFS, Huergo L. Robust Sampling of Altered Pathways for Drug Repositioning Reveals Promising Novel Journal of Rare Diseases Research & Treatment Therapeutics for Inclusion Body Myositis. J Rare Dis Res Treat. (2019) 4(2): 7-15

disease, that regulate important cellular mechanisms, signaling events, or have important protein coding associated with the disease to unravelling translational3 remarked thatbiomarkers the phenotypic and identifying approach small generally molecules provides with better high an expression matrix E of different samples (patients and results.therapeutic Drug index.development Swinney for andrare Xia,diseases (2014) has additional functions. Following this approach the data consists in challenges in comparison to common diseases due to the that are monitored in the analysis, and the columns are the genetichealthy probescontrols). that The are rows measured in the inmatrix each sample.are the samplesWe also need the array (Cobs) that provides the observed classes fewer patients available for inclusion in clinical trials and of the set of samples that have monitored and form the thetheir use geographical of deep learning dispersion. methodologies Therefore, is hampered a pragmatic by the training dataset, informed by medical doctors. approach is needed for finding novel orphan drugs, since limited amount of samples. In this paper we introduce an L*(g), involves solving the Finding the discriminatory genetic signatures efficient methodology to address orphan drug discovery in optimization of the cost function corresponding to the classifier rare diseases, which is based in a robust sampling of the O( ) = ( ) obs , genetic pathways altered by the disease, that is, the set of 1 demonstratemost discriminatory that this genesrobust of phenotypic the IBM phenotype approach is which able (2) classes (Cobs) and the corresponding set of predictions tohave obtain been interesting altered by results the disease. in the case In this of Inclusion paper we Body will L*(gto), via measure the genetic the signature difference g between the observedL Myositis, highlighting viral infection as a possible trigger ( ) obs notation 1 represents the prediction error, of this disease and Interferon-gamma-mediated Signaling and the classifier *. The refers in this case to the algorithm used to characterize which coincides with the number of uncorrected samples Pathway as the main mechanism involved. The word robust L* according to g: Acc(g g). predicted by the classifier and is related to the accuracy of determinacy of this kind of problems As a result of this ) = 100 - O( these pathways by dealing with the intrinsic high under underdetermined since the number of monitored genetic This kind of prediction problems are highly preclinicallyanalysis, the mainvalidated altered and pathways clinically andtested. different potential samples, and consequently, the associated uncertainty orphan drugs are presented. These findings should be spaceprobes ofis alwaysthese problemsmuch larger is thanhuge. the Mathematically, number of disease the Understanding defective pathways uncertainty space relative to L* is composed by the sets of Phenotype prediction consists of identifying the set accuracy: high predictive genetic networks with similar predictive development and constitutes one of the main challenges M = {g: O(g) < tol or sets of genes that influence the disease genesis and tol Expression (3) means}. that the uncertainty space (3)of faced in drug design. Two main obstacles related to the the phenotype prediction problem contains all the genetic toanalysis the sample of genetic dimension, data with and translationalthe absence ofmeans a conceptual are the modelhigh dimension that relates of the the different genetic informationgenetic signatures with respect to the tol:Acc(g > 100-tol. networks whose predictive accuracy is greater than 100 - class prediction, more precisely, an operator of the form: Mtol is crucial, ( ): s C= {1, 2}, since the genetic signatures contained in this set are The sampling and posterior analysis of that links the genetic signature g to the set of classes (1) C high degree of under-determinacy of the learning problem expected to be involved in the disease development. The

= {1, 2} in which the phenotype is divided (in the case of a division might correspond to different interesting (2) makes the characterization of the involvedE) and biological in the binary classification problem). In practice the phenotype problems in drug design, such as, unravelling the altered pathwaysclass assignment7 to be very (Cobs ambiguous) provoke that(De Andrés-Galianathe genetic signature et al., 2016a) . Noise in data (expression matrix 4; understanding the mechanisms of genetic pathways in a disease (see for instance Fernández- with the highest predictive accuracy cannot explain the Martínez et al., 2017)5 origin of the disease (De Andrés-Galiana et al., 2016 b). the high discriminatory genetic responsibleaction of a drug of undesirable(MoA) in a specific side effects context (see (see for for instance networksThe methodology in M are involved presented in the in thismechanistic paper is pathways based in Chen et al., 2016) , or6. the genetic pathways that might be tol thatthe following serve to explain assumption: the disease “ development, and therefore ReinboltMicroarray et al., 2018)technologies provide relative levels of gene can be used to finding orphan drugs able to re-establish ciently the homeostasis perturbed by the disease

used to sample Mtol expression in the transcriptome, and can be effi ”. The algorithm modelled to unravel the altered genetic pathways in a was the holdout sampler (Fernández- Page 8 of 15 Fernández-Martínez JL, Álvarez O, De Andrés EJ, de la Viña JFS, Huergo L. Robust Sampling of Altered Pathways for Drug Repositioning Reveals Promising Novel Journal of Rare Diseases Research & Treatment Therapeutics for Inclusion Body Myositis. J Rare Dis Res Treat. (2019) 4(2): 7-15

9, that generates different random therapeutic hypothesis that are currently used and Martínez et al., 2018a) comparingThis knowledge to the novel is results important that are to presented understand in this the 75/25 data bags (or holdouts), where 75 % of the data in paper. each bag is used for learning and 25% for blind validation. mostFor each frequently of these sampled bags the genes, small-scale taking into genetic account signature all the The data is found. The posterior analysis consists of finding the high predictive networks (small-scale genetic signatures The microarray dataset that we interpreted to analyze with high validation accuracy), serves to establish the IBM contains 22283 genetic probes and 34 samples: 11 defective genetic pathways using ontological platforms. healthy controls15,16 and 23 IBM samples (Greenberg et al., This holdout sampler has been successfully applied in very2002, high 2005) underdetermined. Class 1 corresponds character since to healthy the number controls of other fields to sample the uncertainty space in different geneticand class probes 2 to IBM is 655 patients. greater This than genetic the number experiment of samples. has a technological inverse problems (Fernández-Martínez10,11 et al., As it has been previously highlighted, this is a common analysis2018b; Fernández-Muñiz is used to perform et al., drug 2019) repositioning. In this usingpaper thewe feature of all phenotype prediction problems, that brings took a step forward, and the knowledge issued. from this ambiguity in the phenotype prediction if the modelling 12 Material and Methods. Application to IBM approach that is used is not able to handle this intrinsic connectivity map paradigm (Lamb et al., 2006) feature, that highly impacts the results obtained in the drug State-of-the-art

Inclusion Body Myositis (IBM) is the most common design process. This dataset al.so contained 6 samples of Resultspatients withand discussionpolymyositis (PM). inflammatory muscle disease characterized by progressive Altered genetic pathways muscle weakness in older adults. The progressive course of IBM leads slowly to severe disability. IBM is a rare disease with a very low prevalence rate. The causes for over-expressedTable 1 shows (expression the list of inthe IBM most higher frequently than in sampled healthy IBM are unknown. Two main theories, and coexist: the second the firstone genes by the holdout sampler, divided into two categories: aone degenerative suggests an disorderinflammation-immune related to13 aging reaction of the triggered muscle by a virus (Ghannam et al., 2014) controls) and under-expressed. This list contains the most important 37 genes in each category, that can be clustered • HLA genes belonging to the Major Histocompatibility fibers and. an abnormal pathogenic protein accumulation into the main following families: in myofibrils14 related to the proteasome inhibition (Rose, 2013)According to cureibm.org the clinical trials in IBM HLA-E); complex class I (HLA-A, HLA-B, HLA-C, HLA-G, • 1. Arimoclomol (University College, England): this include the following treatments: • drug targets the proper folding of the proteins to Immunoglobulin Kappa genes (IGK, IGKC)); Actin genes (ACTB, ACTG1); Calcium binding Protein • genes (S100A4, S100A6); 2. clearingPioglitazone away (theJohns abnormal Hopkins clumps University, in the USA):muscle. this drug, used for diabetes), targets the improvement of • Interferon Regulatory genes (IRF9). the function of defective mitochondria to increase • Ferritin production genes (FLT). muscle strength. and Genes related to Immunodeficiency (B2M, STAT1), 3. Rapamycin •

(Hôpital Pitié-Salpetriêre, France): this Tubulin genes (TUBA1B). drug regulates cell growth and metabolism and has an immunosuppressive effect, and was used These genes are also related to other disease to prevent kidney transplant rejection. This drug phenotypes, such as Muscular Dystrophy, HIV type 1 and failed to show efficacy, although the patients treated andBecher can Muscular guide the Dystrophy.drug repositioning This knowledge in some cases,is important that is, 4. improvedFollistatin 6-minutes: this drug distance is used walked. to block myostatin, drugsbecause used it for shows that howdiseases different could phenotypesbe useful to treat are relatedIBM.

a protein which inhibits muscle growth. Blocking The• main pathways issued from this analysis were: myostatin allows the muscles to grow. No adverse genes). effects were detected, and patients who received the Antigen processing and presentation (B2M and HLA therapy improved in a 6-minute walk test.

Page 9 of 15 Fernández-Martínez JL, Álvarez O, De Andrés EJ, de la Viña JFS, Huergo L. Robust Sampling of Altered Pathways for Drug Repositioning Reveals Promising Novel Journal of Rare Diseases Research & Treatment Therapeutics for Inclusion Body Myositis. J Rare Dis Res Treat. (2019) 4(2): 7-15

Table 1. List of over-expressed and under-expressed genes in the • Antigen Processing and Presentation. set of most discriminatory genes of the IBM vs healthy controls (HC) phenotype. Over-expression means in this case higher expression in • IBM patients than in HC. • Interferon-gamma-mediatedAntigen Processing and Presentation Signaling Pathway. of Peptide Over-expressed genes/probes Under-expressed genes/probes Antigen via MHC Class I. HLA-B NDUFS7 • HLA-C EIF1 206559_x_at CAPN3 • TypeRegulation I Interferon of Immune Signaling Response. Pathway. B2M DCUN1D2 EEF1A1 SLC38A3 HLA-G PFKFB1 The same pathways (Immune System/ Interferon TIMP1 RAD23A Gamma Signaling/ Immune Response IFN Alpha/beta FTL TMEM159 Signaling Pathway/ Cytokine Signaling in Immune System/ S100A6 MIR6778 /// SHMT1 Antigen Presentation- Folding, Assembly and Peptide HCRP1 EIF1 Loading of Class I MHC/ Type II Interferon Signaling STAT1 EEF1G /// MIR3654 (IFNG)/ NF-kappaB Signaling/ Antigen Processing-Cross MIR7703 /// PSME2 YBX3 Presentation/ Natural Killer Cell Receptors/ Influenza A/ TUBA1B PNPLA4 Immune Response Role of DAP12 Receptors in NK Cells/ BTN3A3 AQP4 Viral Carcinogenesis) were also found for PM patients. LOC101060363 /// PPIA DTNA This result suggests that the results shown in this paper C11orf48 /// LOC102288414 GLUL might be generalizable to the entire class of inflammatory HLA-F EEF1G /// MIR3654 myopathies. Table 2 shows the results of the pathway RPS4Y1 LGR5 analysis17 provided by Enrichr2016 (Kuleshov et al., IRF9 ITGB6 /// LOC100505984 analysis. 2016) , confirming the results of the previous pathway PRUNE2 PBX1 Drug repositioning for IBM IL32 RS1 TMSB10 EIF4B ACTB /// ACTG1 ITGB6 /// LOC100505984 been gained, to select one or several targets and applying S100A4 216737_at the Thestate-of-the-art final step consists in drug in repositioning using the knowledge (Bezerianos that et has al., SP100 DHPS B3GALT4 GRB10 18 CD24 LMCD1 2017) . In this case we have used the Connectivity Map ATP6V0E2 ACTN2 drugs(CMAP and 02) orphan web application diseases frommodelling the Broad transcriptomic Institute, which data MLLT11 IDE serves to identify potential. CMAP biological searches relationships for drugs between tested NANS SAMD4A in different cell lines12 at different doses that are able to CDKN1A RXRA re-establish(Lamb et al., the 2006) homeostasis, that is, the overexpressed IGK /// IGKC USP24 UCP2 YBX1 expressed genes are increased in expression. CMAP uses PARP12 CARM1 genes in the disease are down-regulated and the under- TUBA1C PAIP2B ESYT1 EEF2 a modified Kolmogorov-Smirnov test to calculate the LOC101060363 /// PPIA SIX1 algorithmsimilarity ofalso a considers drug perturbed the opposite expression effects profile of the to drug the gene expression profile used to query the database. This • cells (actin, HLA and Immunoglobulin Kappa genes). to decrease its score. As indicated by CMAP, when the up- Immune Response Role of DAP12 receptors in NK and down-regulated lists correspond to the disease state, • Phagosome (actin, HLA and tubulin genes). then the perturbagens with the most negative connections • effectswould correspondsimilar to the to diseasepotential state. treatments, It should while be noted the ones that thewith algorithm the most used positive for drug scores discovery will elicitis deterministic, transcriptional that Immune response IFN alpha/beta signaling pathway is, the drugs that are found do not change as far as the lists • (STAT1, IRF9 and HLA genes). genes). of over-expressed and under-expressed genes remain the Influenza A pathway (STAT1, IRF9, actin and HLA • HLA genes). same. This fact highlights the importance of using a robust Interferon Gamma Signaling (B2M, STAT1, IRF9 and establish the drugs hits are those that are highly correlated tomethod the phenotype. for pathway analysis. The genes that are used to

Besides, the main biological processes involved were: Page 10 of 15 Fernández-Martínez JL, Álvarez O, De Andrés EJ, de la Viña JFS, Huergo L. Robust Sampling of Altered Pathways for Drug Repositioning Reveals Promising Novel Journal of Rare Diseases Research & Treatment Therapeutics for Inclusion Body Myositis. J Rare Dis Res Treat. (2019) 4(2): 7-15

Table 2. Main pathways provided by Enrichr2016 using different ontological databases. Database Pathways Phagosome/ Viral myocarditis/Viral carcinogenesis/ Antigen processing and presentation/ Herpes simplex infection/ Al- KEG lograft rejection/ Graft-versus-host disease/ Type I diabetes mellitus/ Autoimmune thyroid disease/ Pathogenic Escherich- ia coli infection Allograft Rejection/ Translation Factors/ Proteasome Degradation/ Cardiomyopathy/ Translation Factors muscles/ Patho- WikiPathways genic Escherichia coli infection/ Type II interferon signaling (IFNG)/ TGF-beta Receptor Signaling/ Interferon type I signal- ing pathways/ Integrated Pancreatic Cancer Pathway. Endosomal-Vacuolar pathway/ Interferon gamma signaling/ Antigen Presentation: Folding, assembly and peptide loading of class I MHC/ ER-Phagosome pathway/ Antigen Processing-Cross presentation/Interferon Signaling/ Interferon alpha-be- REACTOME ta signaling/ Cytokine Signaling in Immune system/ Immunoregulatory interactions between a Lymphoid and a non-Lym- phoid cells/ Immune System. Glucocorticoid receptor regulatory network/ Signaling events mediated by PRL/IL6-mediated signaling events/IFN-gamma NCI-Nature pathway/Signaling events mediated by Stem cell factor receptor (c-Kit)/ Signaling events mediated by HDAC Class III/Regu- lation of Androgen receptor/IL12-mediated signaling events/mTOR signaling pathway/PDGFR-beta signaling pathway.

Table 3. A) List of main compounds found by CMAP with positive Table 4. List of main compounds found by CMAP02 with similar effects (potential treatments). effects to the disease state. CMAP name dose cell score up down CMAP name dose cell score up down chlormezanone 15 µM HL60 -1 -0.334 0.239 suloctidil 12 µM HL60 1 0.413 -0.235 thapsigargin 100 nM MCF7 -0.99 -0.326 0.241 trichostatin A 100 nM MCF7 0.93 0.464 -0.139 felodipine 10 µM MCF7 -0.974 -0.397 0.16 trichostatin A 1 µM MCF7 0.915 0.369 -0.223 palmatine 10 µM HL60 -0.972 -0.261 0.296 trichostatin A 100 nM MCF7 0.912 0.398 -0.192 oxaprozin 300 µM MCF7 -0.949 -0.191 0.352 oxedrine 24 µM HL60 0.911 0.287 -0.303 clorsulon 11 µM MCF7 -0.94 -0.314 0.224 vorinostat 10 µM MCF7 0.901 0.446 -0.138 chlorprothixene 11 µM HL60 -0.932 -0.274 0.259 cefotaxime 8 µM HL60 -0.93 -0.321 0.211 Table 5. List of the main compounds found by LC1000DCS. Score Combination 0.2836 Exemestane BRD-K48016779 0.2687 Exemestane PHENOLPHTHALEIN Table 3 shows the drugs found by CMAP with positive 0.2687 Exemestane BRD-A24054354 effects and best scores (smaller than -0.90). The drug with 0.2687 Rimexolone BRD-A24054354 the highest score found was chlormezanone, which is a 0.2687 Exemestane BRD-K53472085 muscle relaxant. This drug has as main side effect to cause toxic epidermal necrolysis. Thapsigargin is an inhibitor of the sarco-endoplasmic reticulum Ca2+ ATPase (SERCA), inhibitionand inhibits of thethe fusion autophagic of autophagosomes process induces with stress lysosomes on the Inhibitorsuloctidil, (HDI) which that is adecreases vasodilator cholesterol to treat levelscerebral in neuronalvascular which is the last step in the autophagic process. The cellsdisorders. by modulating Trichostatin key A, genes which in is cholesterol Histone Deacetylase synthesis aendoplasmic calcium channel 19reticulum blocker and typeleads used to cellular to treat death high (Ganley blood 22 et al., 2011) comes in the second place. Felodipine is pressure. Palmatine is a protoberberine alkaloid that has cancer(Nunes cell-lines. et al., 2017) Vorinostat. This is drug also also an HDI. has showedOxedrine positive is also several pharmacological activities, including antimicrobial, aeffects cardiac with stimulant. respect to One the of disease the major when limitations used in prostate of this approach is that drugs are not tested in muscle cell lines. In . glucose and cholesterol-lowering, antitumoral, and20 immunomodulatory properties (Cai et al., 2016) adenocarcinomafact, the results showed cell line) in and Table PC3 4 (humanshowed prostatethree cell cancer lines: Oxaprozin is a non-steroidal anti-inflammatory drug and HL60 (human leukemia cell line), MCF7 (human breast apoptotic agent that inhibits Akt, NF-κB and caspase-3 . Clorsulon caution in the case of muscle cell lines. We have also used activation.is an anthelmintic IKK/NF-κB agent. inhibition Cefotaxime causes is antigenan antibiotic21 presenting used cell line). Therefore, these results should be interpreted with cellsto treat to undergo a number cell death of (Tilstrabacterial et al.,infections, 2014) such as, the LC1000CDS package from NIH-LINCS program (http:// www.lincsproject.org) to look for potential treatments. Table Staphylococcus aureus, which is one bacteria whose 5 shows the main compounds obtained to reverse the disease pathways appeared to associated to IBM in this analysis. Exemestane and Rimexolone. Exemestane is an aromatase effects, that is, promoting gene regulations against inhibitorsignature. and This Rimexolone table highlights is a glucocorticoid different combinations steroid used to of Table 4 shows the drugs found by CMAP with adverse homeostasis. The drug with the highest score found was treat eye inflammation and keratitis.

Page 11 of 15 Fernández-Martínez JL, Álvarez O, De Andrés EJ, de la Viña JFS, Huergo L. Robust Sampling of Altered Pathways for Drug Repositioning Reveals Promising Novel Journal of Rare Diseases Research & Treatment Therapeutics for Inclusion Body Myositis. J Rare Dis Res Treat. (2019) 4(2): 7-15

Figure 1: Correlation tree among the most discriminatory genes of the IBM phenotype.

Table 6. Compounds found by Gene Analytics acting on the main discrimina genes (headers) of the correlation tree shown in Figure 1. Figure 1 shows the correlation tree among the most Name Matched Genes tory genes7 of the IBM phenotype using the (DeAndrés- Pearson Decitabine HLA-B HLA-G, STAT1, TIMP1, S100A4. Galiana et al., 2016a) . This tree is23 built via the minimum Oligonucleotide HLA-G, HLA-B, STAT1, IRF9, S100A4, S100A6. spanning tree (Kruskal, 1956) HLA-B, STAT1, IRF9, S100A4, S100A6, SP100, Retinoic Acid correlation coefficient among the most discriminatory TIMP1. genes of the IBM phenotype. This tree has a header gene Tyrosine HLA-B, STAT1, IRF9, TIMP1, S100A4. (HLA-C) who is connected to other edges with the highest Ifn-alpha HLA-G, STAT1, IRF9 absolute value of the correlation coefficient between 2,5-Oligoadenylate HLA-B, STAT1, IRF9 discriminatorygene expressions. genes Therefore, of the thisIBM treephenotype can be is used inter- to Matrigel HLA-G, STAT1, S100A4, TIMP1. regulated.understand how the gene expression of the most important Ribavirin HLA-B, STAT1, TIMP1. VEGF HLA-G, STAT1, TIMP1, TMSB10. Cyclosporine HLA-B, STAT1, TIMP1 Ribonucleic Acid HLA-G, HLA-B, TIMP1 It can be observed that STAT1 impacts positively the Progesterone HLA-G, STAT1, S100A4, S100A6, TIMP1. expression of HLA-G and this gene impacts the header gene Rosiglitazone STAT1, TIMP1. HLA-C, which is the one with the highest discriminatory Niclosamide STAT1, S100A4. power. All these genes are up-regulated in IBM patients. have reported the PD98059 STAT1, TIMP1. Therefore, down-regulation of STAT124 will induce down- regulation of HLA-C. Hu et al. (2003) expression.inhibition ofBased IFN-gamma on these signalingresults, targeting by glucocorticoids: genes that by the cells to synthesize proteins. regulatesIFN-gamma thesignaling Interferon-gamma-mediated can be achieved by regulating Signaling STAT1 Tyrosine is one of the 20 standard amino acids used

Interferon alfa (INN) is a drug composed of Pathway holds the most promise. Other possible targets natural interferon alpha (IFN-α) obtained from tree.are the Using down-regulation the information of CD74, provided IRF9, by BTN3A3, this correlation NMI and the leukocyte fraction of human blood treated with Sendai other genes that are located in the lower branches of the virus. This drug enhances the proliferation of human B found several compounds that act on the genes25 of this cells and activates NK cells. tree and Gene Analytics (Stelzer et al., 2009) we have that counteracts viral attack by degrading viral and compound impacts the gene expression. Particularly they 2-5’-oligoadenylate synthetase is an antiviral enzyme aretree of (Table special 6). interest This software those compounds does not provide that act how on the Ribavirin is a synthetic guanosine nucleoside and header genes (highlighted in bold): host RNA. • used to treat myelodysplastic syndromes and acute hemorrhagicantiviral agent fevers. that interferes with the synthesis of myeloidDecitabine leukemia. is a Nucleic Acid Synthesis Inhibitor viral mRNA. It is used for treating hepatitis C and viral • • signal protein that stimulates the formation of blood to regulate gene expression. vessels.VEGF (Vascular Endothelial Growth Factor) is a Oligonucleotides are small RNA molecules that serve • Retinoic acid is a metabolite of Vitamin A, and • Cyclosporine is an immunosuppressant medication

Page 12 of 15 Fernández-Martínez JL, Álvarez O, De Andrés EJ, de la Viña JFS, Huergo L. Robust Sampling of Altered Pathways for Drug Repositioning Reveals Promising Novel Journal of Rare Diseases Research & Treatment Therapeutics for Inclusion Body Myositis. J Rare Dis Res Treat. (2019) 4(2): 7-15

used in rheumatoid arthritis and in organ of the poor protein degradation and recycling provoking transplants to prevent rejection. Its mechanism of an abnormal pathogenic protein accumulation in the . 14 • action consists in lowering the activity of T-cells. myofibrils (Rose, 2013) to improve the immune system function. RNA is used to treat and prevent Alzheimer and also This paper shows that a correct understanding of • Progesterone serves as an intermediate in the considerationthe altered genetic of an optimal pathways MoA is veryhas been important considered in drug as biosynthesis of steroid hormones and adrenal repositioning. The target-centric approach without corticosteroids. productivity in pharmaceutical research and development • Rosiglitazone is an anti-diabetic drug that has an the main responsible of the high. Robust attrition methods rates for and sampling the low 32 fall and inhibitor levels increase in patients on (Swinney and Jason, 2011) rosiglitazone.anti-inflammatory effect because NF-κB levels isthe the altered case of pathways the holdout and sampler dealing withdesigned the high by our intrinsic team anddegree used of uncertaintyin this paper, of thatthese has problems also provided are needed. excellent This • results in the uncertainty analysis in other technological Niclosamide is used for the treatment of most • tapeworm infections. is used to perform drug repositioning via the Connectivity fields. The knowledge issued from the pathways analysis PD98059 is a potent and selective inhibitor of Analytics serve to locate compounds that are able to MAPlipopolysaccharide kinase kinases (LPS)-induced26 (MAPKK), MEK1 production and MEK2 of actMap (and paradigm. reverse) Tools on suchthe genetic as CMAP/LC1000CDS/Gene- signature perturbed [Alesi et al., 1995] . PD98059 can inhibit. the 27 cytokines such as TNF-α (Reilin et al., 2001) by the disease in order to achieve homeostasis. These oil, curcumin, olive leaf extract, glucosamine, lithium, compounds can be considered as potential treatments. The Finally, there exist natural products such as fish- categories: muscle relaxants, calcium channel blockers, resveratrol or Omega-3 fatty acids that are recognized by drugs that were repositioned by CMAP belong to several drugs, anthelmintic agents and antibiotics to treat bacterial antimicrobial agents, non-steroidal anti-inflammatory their effect in lowering interferon gamma response in cell lines and animal models (see for instance Zang et al., 2011; of Exemestane (aromatase inhibitor) and Rimexolone . We believe that the research on rare infections. LC1000CDS highlighted different combinations Wallace et28, al., 29, 2001; 30, 31 Rowse et al. 2012; Guang-Xiang et al., 2005, etc) analysis of mechanisms of action contained in these natural (glucocorticoid steroid). The knowledge provided by diseases should benefit from both, orphan drugs and the to design target-centric approaches based on the main substances, to treat these diseases and improving the life of the robust sampling of the altered pathways is useful patients. Conclusions headeraltered genespathways of the as correlationwe have shown tree ofusing the IBMGene-Analytics. phenotype, highlightingThis package theprovided importance different of compounds compounds acting acting on theon

In conclusion this paper shows a simple and fast antiviral agents and on the interferon pathways. We hope methodology to reposition drugs for drug diseases that works myopathies (IBM) help to improve the understanding of that the results provided in this paper on inflammatory forwith pre-clinical very few patient validation samples. and clinical The methodology test, accelerating serves the to generate new therapeutic targets and repositioning drugs this methodology can be easily applied to other rare and non-rarethis disease diseases. in order to guide future clinical trials. Finally, to IBM using publicly available transcriptomic data. finding of new therapies. We have shown the application Computational methods drugs used in IBM clinical trials and the results that have Interestingly, only weak relationships exist among the genes that are perturbed by the diseases are: The computational methods used to establish the list of myopathies,been shown suchhere. asThis the research Major Histocompatibility highlights some pathways Complex 1. (MHC)that are class widely I molecules accepted and to transcription play a role infactors inflammatory involved The holdout9. In each sampler holdout the combined discriminatory with genes filter arereduction those methodsthat are differentially (Fernández-Martínez expressed et and al., alsoin MHC the classimportance I presentation, of some genes showing involved the relevance in protein of 2018a) the cytotoxic CD8 T cell-mediated immune response and is used are also common to Polymyositis. We make the hypothesis haveto establish the highest the cross-validation Fisher’s ratio. accuracy A k-NN 7,8classifier of these degradation in inflammatory myopathies. These pathways (DeAndrés Galiana et al., 2016a, 2016b) or bacteria is taking place, and might be also responsible that an inflammation-immune reaction triggered by viruses genetic networks. This approach is named in this paper as Robust Pathways Sampling, since it serves Page 13 of 15 Fernández-Martínez JL, Álvarez O, De Andrés EJ, de la Viña JFS, Huergo L. Robust Sampling of Altered Pathways for Drug Repositioning Reveals Promising Novel Journal of Rare Diseases Research & Treatment Therapeutics for Inclusion Body Myositis. J Rare Dis Res Treat. (2019) 4(2): 7-15

References

1. DiMasi JA, Grabowski HG, Hansen RW, 2016. Innovation in the pharmaceutical industry: New estimates of R&D costs. J Health Econ. 2016; 47, pp. 20-33. 2. NIH, 2010. Rare Diseases and Orphan Products. Accelerating Research and Development. National Academies Press, ISBN-10: 0-309-15806- 3. 0. Swinney DC, Xia S., The discovery of medicines for rare diseases. 4. Future Med Chem. 2014; 6, pp. 987-1002. Fernández-Martínez JL, deAndrés-Galiana EJ, Sonis ST. Genomic data integration in chronic lymphocytic leukemia. J Gene Med. 2017; 19, 5. pp. e2936.

ofChen head P, Manciniand neck M, cancer Sonis andST, Fernandez-Martinez mitigation of oral mucositis. J, Liu J, Cohen PLoS EEW,One. Toback FG. A novel peptide for simultaneously enhanced treatment

6. 2016; 11, pp. e0152995. Reinbolt RE, Sonis S, Timmers CD, Fernández-Martínez JL, Cernea A, de Andrés-Galiana EJ, Hashemi S, Miller K, Pilarski R, Lustberg MB (2018). Genomic risk prediction of aromatase inhibitor-related arthralgia in patients with breast cancer using a novel machine- learning algorithm. Cancer Med. 2018; 7, pp. 240–253. Biomedical Robots for Phenotype Prediction Problems. J Comp Biol. 7. deAndrés-Galiana EJ, Fernández-Martínez JL, Sonis ST. Design of Figure 2: The Holdout Sampler workflow used to perform the robust sampling of altered genetic pathways (from Fernández- 8. 2016a; 23, pp. 678-692. analysis of gene ranking methods in phenotype prediction. J Biomed Martínez et al., 2018) deAndrés-Galiana EJ, Fernández-Martínez JL, Sonis ST. Sensitivity

to unravel different high discriminatory genetic 9. Inf, 2016b, 64, pp. 255-264. Fernández-Martínez J.L., A. Cernea, E.J. deAndrés-Galiana, F.J. phenotypeFernández-Ovies, prediction Z. problems Fernández-Muñiz, via the Holdout O. Álvarez-Machancoses, sampler. In: Rojas I., networks, instead of using just the one with the Saligan L.N., Stephen Sonis (2018a). Sampling defective pathways in 2. highest accuracy (see figure 2). sampled genes in the uncertainty space of the Ortuño F. (eds) Bioinformatics and Biomedical Engineering. IWBBIO The posterior analysis of the most frequently 2018. Lecture Notes in Computer Science, vol 10814. Springer, Cham. phenotype prediction, Mtol, consists in a frequency analysis of the most frequently sampled genes in 10. applicationFernández-Martínez to concrete JL, strength Fernández-Muñiz estimation, Inverse Zulima, Problems Breysse in Science Denys. The uncertainty analysis in linear and nonlinear regression revisited:

have been sampled. Based on this analysis, and and Engineering, 2018b, DOI: 10.1080/17415977.2018.1553969. the different high discriminatory networks that establishing a cut-off frequency that depends on 11. Fernández-Muñiz Z, Hassan K, Fernández-Martínez JL. Data kit the problem, the lists of over-expressed and under- inversion and uncertainty analysis. J Appl Geophys, 2019, 161, pp. expressed genes is selected. 228-238. 12. Lamb, J. The Connectivity Map: Using Gene-Expression Signatures 3. to Connect Small Molecules, Genes, and Disease. Science, 2006, 313, algorithms using the most-frequently sampled pp.1929–1935. The pathway enrichment and drug repositioning 13. Ghannam, K., et al.., Upregulation of immunoproteasome subunits in . myositis indicates active inflammation with involvement of antigen genes (Lamb12,17, 252006; Stelzer et al. 2009; Kuleshov et presenting cells, CD8 T-cells and IFNGamma. PLoS One, 2014. 9, p. Acknowledgmentsal., 2016) e104048. 14. Rose MR. 188th ENMC International Workshop: Inclusion Body Myositis, 2-4 December 2011, Naarden, The Netherlands. We acknowledge Dr. Gonzalo Gómez-López from CNIO Neuromuscul Disord. 2013, 23, pp. 1044-1055. (Spain) and the CLUE Team at the Broad Institute clue. 15. Greenberg SA, Sanoudou D, Haslett JN, Kohane IS, Kunkel LM, Beggs (Universityio) for their of help Oviedo) orienting for ushelping about us the to use interpret of CMAP02; the AH, Amato AA (2002). Molecular profiles of inflammatory myopathies. Dr. Segundo González and Christian Sordo-Bahamonde Neurology. 2002, 22, pp. 1170-1182. 16. Greenberg SA, E. M. Bradshaw, J. L. Pinkus, G. S. Pinkus, T. altered pathways in IBM, and finally Dr. Stephen T. Sonis Burleson, B. Due, L. S. Bregoli, K. C. O’Connor, A. A. Amato. NeurologyKuleshov MV, Dec Jones 2005, MR, 65, Rouillard pp. 1782-1787. AD, et al.. Enrichr: a comprehensive (Brigham and Women’s Hospital and Biomodels) and Dr. Andrzej Andrzej Kloczkowski (The Research Institute 17. unconditional support. gene set enrichment analysis web server 2016 update. Nucleic Acids at Nationwide Children’s Hospital) for their inspiring Res. 2016; 44, pp. W90-7.

Page 14 of 15 Fernández-Martínez JL, Álvarez O, De Andrés EJ, de la Viña JFS, Huergo L. Robust Sampling of Altered Pathways for Drug Repositioning Reveals Promising Novel Journal of Rare Diseases Research & Treatment Therapeutics for Inclusion Body Myositis. J Rare Dis Res Treat. (2019) 4(2): 7-15

st mitogen-activated protein kinase kinase in vitro and in vivo. J. Biol. 18. Bezerianos A, Dragomir A, Balomenos P (2017). Computational 26. Alessi DR. et al.. PD 098059 is a specific inhibitor of the activation of methods for processing and analysis of biological pathways, 1 Edition, Springer Brief in Computer Science, 2017. Chem., 1995, 270, pp. 27489-27494. by human macrophages is differentially regulated at the level of 19. Ganley, Ian G.; Wong, Pui-Mun; Gammoh, Noor; Jiang, Xuejun. 27. Reiling N. et al.. Mycobacteria-induced TNF-alpha and IL-10 formation Distinct Autophagosomal-Lysosomal Fusion Mechanism Revealed 3339-3345. by Thapsigargin-Induced Autophagy Arrest. Molecular cell, 2011, 42, mitogen-activated protein kinase activity. J Immunol., 2001, 167 pp. pp.731 – 743. … Liu, E. Resveratrol-mediated gamma interferon reduction prevents 20. Cai Z, Wang C, Yang W. Role of berberine in Alzheimer’s 28. Zang, N., Xie, X., Deng, Y., Wu, S., Wang, L., Peng, C., Li, S., Ni, K., Luo, Y., disease. Neuropsychiatr Dis Treat. 2016, 12, pp. 2509-2520. syncytial virus-infected immunocompromised mice. Journal of airway inflammation and airway hyperresponsiveness in respiratory 21. Tilstra, J. S., Gaddy, D. F., Zhao, J., Davé, S. H., Niedernhofer, L. J., Plevy, S. E., & Robbins, P. D. Pharmacologic IKK/NF-κB inhibition causes antigen presenting cells to undergo TNFα dependent ROS-mediated virology, 2011, 85, pp. 13061-13068. programmed cell death. Scientific reports, 2014, 4, p. 3631. 29. Wallace, F. A., Miles, E. A., Evans, C., Stock, T. E., Yaqoob, P. and Calder, 22. Nunes MJ, Moutinho M, Gama MJ, Rodrigues CMP, Rodrigues E. Histone P. C., Dietary fatty acids influence the production of Th1‐ but not Th2‐ Deacetylase Inhibition Decreases Cholesterol Levels in Neuronal Cells type cytokines. Journal of Leukocyte Biology, 2001, 69, pp. 449-457. by Modulating Key Genes in Cholesterol Synthesis, Uptake and Efflux. 30. Rowse, A. L., Naves, R., Cashman, K. S., McGuire, D. J., Mbana, T., Kruskal, J. B. On the shortest spanning subtree of a graph and PLoS ONE, 2013, 8, p. e53394. Raman, C., & De Sarno, P. Lithium controls central nervous system the traveling salesman problem. Proceedings of the American 23. autoimmunity through modulation of IFN-γ signaling. PloS one, 2012, 7, p. e52658. Abrogates the Acute Phase of Experimental Autoimmune Mathematical Society, 1956, 7, pp. 48–50. 31. Guang-Xian Z., Shuo Yu, Bruno G., Abdolmohamad R., Glucosamine 24. Xiaoyu Hu, Wai-Ping Li, Charis Meng and Lionel B. Ivashkiv. Inhibition of IFN-γ Signaling by Glucocorticoids. J Immunol, 2003, 170, pp. 4833-4839. Encephalomyelitis by Induction of Th2 Response. The Journal of Immunology, 2005, 175, pp. 7202-7208. 25. Stelzer G., Inger A., Olender T., Iny-Stein T., Dalah I., Harel A., et al.. GeneDecks: paralog hunting and gene-set distillation with GeneCards 32. Swinney, D. C and Jason TI. How were new medicines discovered? annotation. OMICS, 2009, 13, p. 477. Nature Reviews Drug Discovery, 2011, 10, pp. 507–519.

Page 15 of 15