Acute myeloid leukaemia (AML) affects children and adults of all ages. AML remains one of the major causes of death in children with cancer and for children with AML relapse is the most common cause of death. Here, by modelling AML in vivo we demonstrate that AML is discriminated by the age of the cell of origin. Young cells give rise to myeloid, lymphoid or mixed phenotype acute leukaemia, whereas adult cells give rise exclusively to AML, with a shorter latency. Unlike adult, young AML cells do not remodel the bone marrow stroma. Transcriptional analysis distinguishes young AML by the upregulation of immune pathways. Analysis of human paediatric AML samples recapitulates a paediatric immune cell interaction gene signature, highlighting two genes, RGS10 and FAM26F as prognostically significant. This work advances our understanding of paediatric AML biology, and provides murine models that offer the potential for developing paediatric specific therapeutic strategies. Acute myeloid leukaemia (AML) affects people of all ages. Here, the authors model AML in vivo and demonstrate that the age of the cell of origin impacts leukaemia development and the genetic signature where adult cells of origin give rise exclusively to AML and young cells of origin give rise to myeloid, lymphoid or mixed phenotype acute leukaemia. AML is characterised by impaired myeloid differentiation resulting in the accumulation of myeloid blasts in the bone marrow (BM) and peripheral blood (PB). Seminal studies in adult AML3 have led to the leukaemia stem cell (LSC) hypothesis, which postulates that leukaemias are organised into cellular hierarchies, mirroring normal haemopoiesis. LSCs have similar properties to normal adult HSCs at the apex of the haemopoietic hierarchy, which differentiate into bulk leukaemia cells. In the majority of adult human AMLs, the LSC has been identified as either the LSK or a more mature progenitor cell that has acquired self-renewal5. Current therapies fail to eradicate leukaemic cells, which are protected in the BM microenvironment, interact with the surrounding cells, and cause disease relapse7.The incidence of acute myeloid leukaemia (AML) increases with age, and in childhood accounts for 20% of all leukaemia. The current overall survival rate in children is only 60–75%, and thereafter falls progressively with age to 5–15% in the elderly. Both children and adults die from a combination of relapse  and treatment-related mortality during both induction and consolidation therapy10. In children, the vast majority of patients present with de novo AML while in adults, a significant proportion of AML arises from an underlying MPN or MDS and this characteristically increases with age. This can be explained by the significant differences in genetic landscapes of paediatric and adult AML. Only 20% of paediatric patients have a normal karyotype and the number of somatic mutations is lower than in adult AML (5 per paediatric sample versus 10–13 per adult sample). Paediatric AML has a higher frequency of cytogenetic abnormalities compared to adult, with some occurring almost exclusively in infants/children. Furthermore, the epigenetic landscapes of paediatric and adult AML are vastly different with respect to the incidence and type of mutations in epigenetic modulators11. The recent TARGET AML initiative comprehensively showed the similarities and differences in the mutational profile of >1000 AML patients across the age spectrum, demonstrating DNA methylation and miRNA profiles can stratify paediatric patients in terms of overall and progression-free survival, calling for an update to address-specific vulnerabilities of paediatric subtypes12. To progress our understanding of paediatric AML, it is important to establish models of disease that recapitulate features of the disease to develop age-specific therapies.There are major differences between paediatric and adult AML relating to (i) the frequency of de novo AML versus secondary AML subsequent to underlying myeloproliferative neoplasms (MPN) or myelodysplastic syndromes (MDS) and (ii) cytogenetic and molecular abnormalities13. This does not explain the occurrence of AML in children. Neonatal HSCs are a cycling population compared to the quiescent properties of adult HSCs. With respect to the infant haemopoietic system (where the incidence of childhood AML is at its highest), children up to the age of three retain features of foetal haemopoiesis. The equivalent switch from foetal to adult HSCs (quiescent cells) in mice occurs between 3 and 4 weeks of age15. Aged HSCs and the surrounding stromal cells possess differences in lineage output, and have altered genetic profiles  compared to their younger adult counterparts17. BM stromal cells including mesenchymal stromal cells (MSCs), osteoblasts (OBs), and endothelial cells (ECs) contribute to HSC function. Similar to HSCs, leukaemic cells depend on the BM niche, and not only co-opt normal niches but also alter them to their own advantage for propagation and treatment survival20. It is not known whether changes that occur in the leukaemic BM niche are the same in paediatric and adult AML.Aging features, such as decreased immune response, increased myeloid lineage skewing, genomic instability, reduced regenerative capacity of stem cells, and positive selection of pre-leukaemic clones driven by cell intrinsic and extrinsic factors, are all thought to contribute to the high incidence of AML in older adults23. NUP98HOXA9 (NH9) oncogene represents 11p rearrangements found in both paediatric and adult AML, and it has been exclusively associated with myeloid leukaemia both in humans and in experimental models. Although 11p rearrangements are rare, NH9 is representative of deregulated HOX leukaemia, observed in 70% of all AMLs as a result of several upstream genetic alterations that occur across all age-groups25. We have modelled the age continuum using the NH9 oncogene to address how the age of the cell of origin impacts on leukaemic disease. We show that paediatric AML is biologically different to adult AML, and that the age of the cell of origin significantly influences leukaemia latency, lineage, molecular profile, and the leukaemic niche.Given the large spectrum of genetic abnormalities found in AML, there are many examples that have been shown to recapitulate AML disease in the mouse, such as MLL and PML oncofusions, and those that present pre-leukaemic features of the disease, but not overt AML, such as AML1ETO26, we isolated murine lin-sca1+cKit+ (LSK) cells, which include the long- and short-term HSCs, and myeloid progenitor populations (CMPs and GMPs) from different ages of mice  to represent infant/prenatal origins ), childhood (BM from 3 week(w)), young adult (10 w) and middle/old age (>52w) C57BL/6 mice. These different aged populations were transduced with NH9 retrovirus and assessed for in vitro transformation by CFC assay. After the first plating (P1) colonies were enumerated and identified  p = 0.02 (spleen), FL vs 10w p = 0.015 (BM) p = 0.014 (spleen), 3w vs >52w p = 0.00003 (BM), 3w vs 10w p = 0.006 (BM) p = 0.004 (spleen). To investigate the influence of the BM niche on age-defined LSK transformability, NH9-transduced P2 LSKs from each age group were transplanted into recipient mice generating NH9FL, NH93W, NH910W and NH9>52W. No significant differences in long-term engraftment, determined by GFP expression in PB after 16w, were observed across the groups  developed leukaemia with a significantly shorter latency compared to young leukaemias (NH9FL and NH93W) (p = 0.0111)  and adult (NH910W and NH9>52W) revealed a 70 day increase in median survival (MS) in the young compared to adult groups    Fig. . Poolingly) Fig. . Further%) Figs. . There w%) Figs. . Similar%) Figs. . There wups Fig. . In addiSKs Fig. . These d+ LSKs developed AML , with low or no expression of lymphoid markers CD19, B220, CD4 and CD8  and mixed phenotype acute leukaemia (MPAL)  and >52w BM (LSK>52W) into 6–8w recipients we saw no age-dependent skewing of donor cells, with both LSKFL and LSK>52w groups having the same proportion of myeloid, B and T cells . Using markers of myeloid and lymphoid leukaemia, we identified three distinct types of acute leukaemia driven by NH9. All mice transplanted with adult NH9AML Fig.  characteCD8 Fig.  and posiCD8 Fig. . Mice trAL) Fig. . The ALLAL) Fig.  as well AL) Fig. . The MPAAL) Fig. , but posAL) Fig. —an estab+ LSKs by gene expression analysis of lineage restricted genes. In the GFP+ leukaemic blasts from the AML diseases there was upregulation of myeloid genes Cebpb, Cebpe and Fcgr3 compared with ALL blasts   of ≥1.5 and q-value of <0.05. In this comparison, we identified 795 DEGs in NH93W , 2117 DEGs in NH910W  and 1455 DEGs in NH9>52W   pathway enrichment using the MSigDB platform. The top ten most significantly enriched GO pathways revealed an enriched development signature in the NH93W leukaemic cells  Fig. . Princip2W) Fig. . Signifi3W and NH9>52W mice—as there was the greatest discrimination between those groups by PCA , MSCs (CD45−Ter119−CD31−CD51+ PDGFRa+) and OBs (CD45−Ter119−CD31−CD51+PDGFRa−) in the central marrow or compact bone (collagenase-treated bone fragments). We assessed the disease burden of transplanted mice with >30% GFP expression in the BM  or >52w (LSK>52W) origin  or >52w (LSK>52W) origin  revealed enrichment of this pathway in NH93W compared to NH9>52W leukaemic cells  and (ii)  or adult  AML samples that had been run on the same microarray platform. We corrected for batch differences using reference genes with low variance and mean (see Methods). From our DEG list we identified 19 genes which were significantly enriched in human paediatric AML samples relative to adult AML . Both FAM26F and RGS10, whose expression correlated with poor clinical outcome, were found significantly enriched in AML with t (MNX1/ETV6) and t (RUNX1/RUNX1T1)  and t . To investigate the prognostic significance of the genes in our human paediatric AML signature we used the OncoLnc platform to mine the available AML dataset with prognostic information, the TCGA L-AML dataset of 150 adult AML patients. This analysis shows patients with high expression of FAM26F or RGS10 have significantly poorer overall survival  Fig.  whereas T1) Fig. . Of the val Fig. . High CDval Fig. . PatientOur findings support the hypothesis that AMLs of paediatric origin have a distinct molecular profile impacting on innate immune cell pathways, indicating differential interactions with BM niche components compared to adult AML. Gene expression profiling in AML is a well-established way to provide valuable diagnostic insight into predicting clinical outcome and our data show that the expression of FAM26F and RGS10, which are significantly enriched in two AML subtypes, correlates with significantly poorer clinical outcome.12. This study provides a murine model that can recapitulate paediatric disease features, a model that can be used to drive forward with new modes of paediatric-specific therapies. We used an age-defined in vivo leukaemia model to address the hypothesis that the leukaemia cell age influences disease biology and aggressiveness. Our results have shown that significant biological differences exist in AML derived from a young or adult cell of origin. Transplantation of NH9+ adult (10w and >52w) LSKs resulted in AML in 100% of recipient mice. In contrast, transplantation of NH9+ young (FL and 3w) LSKs resulted in a less penetrant disease with a significantly longer latency. Whereas the self-renewal ability of HSCs decreases with age, our model uses a bulk LSK population that includes multipotent and more restricted progenitors with varying self-renewal33. It is not known how the self-renewal capacity of these cell populations changes with age. Indeed, we observed increased homing to the BM and spleen with the older NH9-transduced cells. Despite initial homing differences, however, similar levels of GFP (donor cell burden) were observed in the PB after 16 weeks. It would be interesting to see whether the age of the recipient mouse (in our case it was 6–8 wks) had an impact on the levels of homing, engraftment and disease generated from the different age donor cells. In addition to AML, NH9 drove ALL and MPAL diseases from young LSKs but not adult. These findings are supported by observations in human leukaemia where lineage promiscuity has been observed more commonly in paediatric leukaemia35. Thus far the NH9 fusion oncogene has been exclusively linked with myeloid leukaemias, but other Nup98 fusion proteins have been identified in cases of human paediatric T-ALL38. NUP98-HOXD13 can induce both AML (60%) and T- and B-ALL in vivo40. The multi-lineage disease output that we observe from a young cell of origin may be accounted for by strong intrinsic lymphoid programmes inherent in younger LSKs that are only revealed in the BM microenvironment. Together our data show that the age-related transcriptional landscape of cells at the time of transformation has a significant impact on the biology of the resultant disease.Current therapy for paediatric AML has been extrapolated from adult AML treatment, which assumes that the disease in children and adults are similar. The recent TARGET AML dataset showed distinct features of age-specific AML disease, calling for increased understanding to drive paediatric-specific therapy+ LSKs. The disparity between these models suggested that the BM microenvironment plays a role in the age-related differences in leukaemia observed. Upon transplantation into secondary recipients, we observed remodeling of the BM microenvironment by adult AML blasts (NH9>52W) with a significant increase in marrow ECs, and OBs and MSCs in the compact bone. This correlates with several recent publications that have identified remodelling of the BM stroma by leukaemic blasts41. Leukaemic cells are protected and supported by interacting with the BM niche, and disease relapse is caused by the persistence of leukaemia cells that evade treatment. In humans, adult AML patients have higher relapse rates than children with AML. The ability of adult leukaemic cells to remodel the BM stroma in our model suggests that specifically targeting interactions between AML cells and the niche in adults may improve therapy outcome and reduce the rate of relapse. In contrast, AML blasts from NH93W mice had no effect on the stroma of recipient mice upon transplantation. The BM niche is a complex microenvironment consisting of multiple cell types beyond stromal ECs, MSCs and OBS, including immune cells, adipocytes and neural cells. Our data indicate that NH93W blasts may interact with non-stromal elements of the niche, and elucidating these interactions could identify druggable targets specific to paediatric AML.Contrary to our in vivo results, our in vitro data showed no difference in the lineage or transformation potential between the different ages of NH93W or NH9>52W cells, confirming our in vivo identification of differential interaction between these age-defined leukaemic blasts and the stroma. GO pathway analysis of DEGs revealed significant enrichment of metabolic pathways in NH9>52W cells compared to healthy LSK>52w, while in the young myeloid blasts (NH93W) we observed significant enrichment of immune system pathways, and upregulation of genes involved in TLR signalling compared to both healthy LSK3w and NH952w. Analysis of DEGs upregulated in NH93W AML blasts using STRING revealed a hub of innate immune cell interactions surrounding CD180. CD180 is a TLR-like receptor expressed on B cells and monocytes, but not T cells, where it forms a complex with MD-1 (Ly86) to regulate TLR2/4 LPS responses42. MD-1 was also significantly upregulated in NH93W myeloid blasts. Activation through CD180 mediates pro-survival and proliferation signals in both normal and leukaemic B cells in vitro43. CD180 has been identified as a marker of LSCs in AML44 and along with CCR2, it was also recently identified as a whole blood biomarker for BRD4 inhibitors 45.Hierarchical clustering analysis of genes encoding receptors involved in cancer-stroma interactions identified enrichment of unique gene clusters associated with either NH946 where it has been shown to play a key role in regulating inflammation. While little is known about the role of RGS10 in AML, in a meta-analysis of over 2700 AML patients across 25 published datasets RGS10 was identified in the top 25 most common differentially regulated genes—along with well-established AML associated genes such as HOXA9, MEIS1 and RUNX1T147. FAM26F is a cation channel that regulates immune response by trafficking substances into or between cells48. It has recently been proposed as an early diagnostic marker as its increased expression is indicative of IFN-γ mediated immune responses49. While AML with t is rare in children as a whole (~3%) it is most commonly seen in infant (0–1 years) AML with one-third bearing the translocation50. It is a cryptic abnormality which can’t be diagnosed using traditional karyptyping methods and is associated with very poor clinical outcome. While t is in fact considered a good risk AML, not all patients in this subgroup do well and these genes may indeed determine whether someone with t does respond well or not to treatment. Here we identify 2 genes, RGS10 and FAM26F which are significantly enriched in this subset of paediatric AML patients which could act as a biomarker for diagnoses.Comparison of paediatric and adult AML datasets revealed a human paediatric gene signature with 19 of the 164 murine DEGs (11.6%) significantly enriched in paediatric AML samples, which included several genes involved with immune cell interaction. Regardless of age, AML patients with high expression of 2 genes in our paediatric signature—FAM26F and RGS10—had significantly poorer overall survival rates. RGS10 is expressed in the brain, lymph nodes, testis and bone marrowt and t and these genes are linked with poor clinical outcome. These are potentially useful biomarkers in paediatric AML and their function and upregulation in paediatric AML of much interest. These findings underpin the necessity to advance the development of age-appropriate and biologically driven precision medicine for the eradication and cure of AML in children.The lifetime risk of developing cancer is determined by a combination of inherited predispositions, environmental factors, and random mutations arising during DNA replication. While cancer is widely considered a disease of the aged, it is the leading cause of death in children and young adults. The appropriateness of the current practice for some cancers of extrapolating treatments across the age spectrum is dependent on the assumption that the same aetiology underlies cancer in the young and old. Our results show a specific transcriptional landscape of paediatric AML that significantly distinguishes paediatric disease biology and is supported by murine modelling. We identify FAM26F and RGS10 as significantly enriched in paediatric AML associated with the AML subtypes −1 (Sigma-Aldrich) and percentage of GFP determined by flow cytometry.Plasmids were constructed in the MigR1 backbone, for the production of retrovirus. The NUP98HOXA9-MSCV-IRES-GFP and FLT3-ITD (N51)-MSCV-IRES-GFP vectors were a gift from Brian Huntly . The AML1ETO-MSCV-IRES-GFP vector was a gift from James Mulloy . Retrovirus was produced by calcium phosphate transfection of constructs with packaging vectors pCGP and pHIT123 in HEK293T (ATCC) cell line. Retrovirus containing supernatants were harvested at 24, 36 and 48 h post transfection. Viral titres were measured by the transduction of 3T3 (ATCC) cells in the presence of Polybrene 4 µg mL−1 Penicillin/Streptomycin (PS) and 2 mM L-Glu) supplemented with 10 ng ml−1 recombinant murine (rm) IL3, 10 ng ml−1 rmIL6 and 100 ng ml−1 rmSCF (Peprotech). For transduction, cells were resuspended in activation cocktail  and virus was quickly thawed and added. The final cell concentration was 0.5–2 × 106 cells/mL. Two 90 min spinoculations were performed 6–12 h apart. After 48 h transduced cKit enriched BM or FL cells were FACs sorted for LSK, CMP and GMP populations .Murine BM and FL cells were retrovirally transduced with titre-matched retrovirus to express GFP tagged oncogenes. BM and FL cells were labelled with ckit (CD117) microbeads (Miltenyi Biotec) to enrich cKit cells by passing through a MS Columns (Miltenyi Biotec) in the magnetic field of a MACS Separator (Miltenyi Biotec). cKit enriched BM or FL cells were pre-stimulated overnight in pre-stimulation cocktail . After 7–10 days, colonies were counted, categorised and images taken on an EVOS XL Core Imaging System (Fisher Scientific). Colonies were categorised based on their morphology as per StemCell Technology Methods and were of 4 distinct phenotypes: granulocyte erythroid macrophage megakaryocyte (GEMM), granulocyte macrophage (GM), granulocyte (G) and macrophage (M)  were plated onto a sub-confluent layer OP9 cells (MTA from Juan Carlos Zuniga-Pflucker) in OP9 media supplemented with 10 ng µl6 GFP+ cells were intravenously transplanted into sub-lethally irradiated 6–8w old recipient mice (450rads). For BM reconstitution experiments animals were monitored for engraftment by GFP% in PB and clinical signs of leukaemia . PB parameters were analysed on a HemaVet 950 (Drew Scientific). Animals were killed on onset of leukaemia or 12 months post BMT. For secondary transplantation, BM blasts from primary recipients that developed AML were intravenously transplanted into sub-lethally recipient mice (B6.SJL). For homing experiments, 2 × 106 GFP NH9 transduced donor cells were labelled with CellTraceTM Violet (CTV) (Invitrogen) and intravenously transplanted into sub-lethally irradiated 6–8w old recipient mice (550rads). Mice were killed 18 h post transplant, and BM, PB and spleen assessed for the presence of GFP + CTV+ donor cells by flow cytometry. Percentage of cells homed was obtained from the absolute number of donor cells, calculated from the percentage of engraftment and total cell number per organ, and the number of the cells injected.Donor LSKs transduced with GFP-tagged NH9 retrovirus and expanded in methylcellulose were collected at P2. 1 × 10−1 collagenase type IV (Gibco) and 2 mg ml−1 Dispase II (Sigma) at 37 °C, twice for 15 min with agitation. Splenic and thymic cells were filtered through a 40 µm strainer. In all tissues red blood cells (RBCs) were lysed in RBC lysis buffer . Single cell suspensions were incubated with antibody cocktail at 4 °C for 20 min.Peripheral blood was collected into an EDTA lined Microvette® capillary blood tube (Sarstedt). Bones were crushed in PBS with 2% FBS and the cells were filtered through a 40 µm strainer to isolate the central marrow. To isolate cells in the endosteal niche, the compact bone fragments were digested with 1 mg mlFor myeloid staining samples were stained with CD11b PE (eBioscience 12-0112-83) or CD11b APC (eBioscience 17-0112-83), Gr1 PerCP-Cy5.5 (eBioscience 45-5931-80) or Gr1 eFlour 450 (eBioscience 48-5931-82), F4/80 APC (eBioscience 17-4801-82), cKit ACP-Cy7 (Biolegend 105825), and CD34 biotin (eBioscience 13-0341-82) and Streptavidin-PE-Cy7 (eBioscience 25-4317-82) at dilution 1:200.For lymphoid staining samples were stained with CD4 APC (eBioscience 17-0042-83), CD8a PE (eBioscience 12-0081-82), B220 PerCP-Cy5.5 (eBioscience 45-0452-82) or B220 eFluor 450 (eBioscience 48-0452-82), CD19 APC-Fluor780 (eBioscience 47-0193-80) or CD19 APC (eBioscience 17-0193-82) and CD3e eFluor 450 (eBioscience 48-0031-82) at dilution 1:200.For progenitor cell isolation GFP-tagged cKit enriched BM or FL was stained with cKit APC (eBioscience 17-1171-82), Sca1 PE-Cy7 (eBioscience 25-5981-82), CD34 biotin and Streptavidin-PE (eBioscience 12-4317-87), CD16/32 APC-Cy7 (BD 560541) and lineage markers: eFlur®450 conjugated CD3, CD4 (eBioscience 48-0042-82), CD8a (eBioscience 48-0081-82), CD11b (eBioscience 48-0112-82) (omitted for FL and 3w), GR1, B220 (eBioscience 48-0452-82) and Ter119 (eBioscience 48-5921-82).For isolation of LSK cells , BM cells were stained with lineage cocktail with the following biotinylated antibodies: CD3 (eBioscience 13-0032-82), CD4 (eBioscience 13-0041-85), CD8a (eBioscience 13-0081-85), B220 (eBioscience 13-0452-85), CD11b (eBioscience 13-0112-85), Gr-1 (eBioscience 13-5931-85) and Ter119 (eBioscience 13-5921-82), followed by anti-biotin MicroBeads staining for lineage cells depletion in LS Columns (Miltenyi Biotec) in the magnetic field of a MACS Separator (Miltenyi Biotec). The lineage-negative population were stained with Sca1 PE-Cy7, cKit ACP-Cy7 and Streptavidin V450 (BD 560797) at dilution 1:200.For identification BM stromal cells were stained with CD45 bio (eBioscience 13-0451-82), Streptavidin PerCP-Cy5.5 (eBioscience 45-4317-82), Ter119 eFluor 450, CD31APC (eBioscience 17-0311-80), CD51PE (eBioscience 12-0512-82), PDGRa PE-Cy7 (eBioscience 25-1401-80) at dilution 1:200.Where applicable dead cells were also excluded using either a 4’,6-diamidino-2- phenylindole (DAPI) at dilution 1:1000 (Sigma-Aldrich D9542). Flow cytometry data were acquired using a FACSCanto II (BD Biosciences) and cells were sorted using a BD FACSAria III (BD Biosciences). Flow cytometry data were analysed using FlowJo software v7 (Treestar Inc).2O2) in PBS for 5 min.Sternal sections were decalcified with 5.5% EDTA solution containing 10% formaldehyde for 7–8 days. Decalcified sterna were embedded in paraffin and sections cut at 2.5 µm and fixed onto microscopy slides. Immunohistochemistry (IHC) was performed with anti-MPO antibody (Dako Agilent A0398) at dilution 1:3000 or anti-CD3 (Dako Agilent A0452) antibody at dilution 1:100. Tissue sections were dewaxed in xylene and descending alcohols and rehydrated in distilled water; endogenous peroxidase was quenched by immersion in 3% hydrogen peroxide (Hhttps://www.stemformatics.org/Stemformatics_data_methods.pdf). Differential gene expression was performed using limma, voom and Glimma packages in R (https://f1000research.com/articles/5-1408/v2). Significance determined by adjusting for false discovery rate using Benjamini-Hochberg method as used by limma. List of DEGs are provided in supplementary data (Supplementary Data https://f1000research.com/articles/6-2010/v1). Raw data are available at GEO with ID GSE107662 (AML) and GSE122066 , and can be accessed on the Stemformatics platform at https://www.stemformatics.org/datasets/search?ds_id=7127# and https://www.stemformatics.org/datasets/search?ds_id=7311#.RNA was isolated using either the RNeasy Mini kit (Qiagen) or Arcturus PicoPure kit (Fisher Scientific) and total RNA converted to cDNA using the High Capacity cDNA Reverse Transcription Kit (Invitrogen) as per manufacturers’ instructions. Targeted gene expression was performed on a 48.48 dynamic array (Fluidigm) in accordance with manufactures’ protocol and gene expression analyzed using standard techniques. For RNA sequencing, RNA libraries were prepared by polyA selection using the TruSeq stranded mRNA kit (Illumina). Paired end RNA-seq was performed on a NextSeq™ 500 platform (Illumina) with a read and fragment length of 75 bp and 150 bp, respectively, to a depth of 33 million reads. Reads were aligned using the standard Stemformatics RNA-Seq data processing pipeline  q-value below 0.05 using the C5 GO module. Where indicated, analysis was carried out using Stemformatics data analysis platform30. When analyzing GSE17855 and GSE6891 standard batch correcting methods sva52 and ruv53 over-or-under corrected the data. Instead an alternative approach was used. A set of reference genes common to both datasets, with low variance and mean within each datasets were identified and used for normalization. First the datasets were quantile normalised so that their value ranges were compatible, and the probes with low variance and mean were identified to be used as the reference genes. The 164 DEGs upregulated in NH93W compared to NH9>52W were then mapped to their human orthologues and corresponding probe identifiers in each dataset. Comparing the difference between each probe and the reference probe identified genes significantly enriched in the human paediatric AML dataset .Gene lists of DEGs were interrogated for GO pathway enrichment using the Molecular Signatures Database (MSigDB) (Broad Institute)http://www.oncolnc.org/) which links to TCGA survival data54. Selected genes were analysed within the L-AML dataset of 150 AML patients. Patients were filtered for high  or low  expression of each gene. AML subtype graphs were generated using ggplot2 package in R (http://www.R-project.org/). For multiple groups comparison one-way ANOVA and t-test were calculated using the ggpubr package in R and each of the genes’ mean expression was compared to the base-mean of the rest.Prognostic significance was determined using the OncoLnc platform (RNA was extracted from P1 and P3 NH9 and P1 MigR1 cells from different ages using the RNeasy® Mini kit (Qiagen). Reverse Transcriptase PCR was performed following the protocol from High Capacity cDNA Reverse Transcription Kit. Primer names and sequences provided in Supplementary Table F-test was performed to determine sample variance, then an unpaired, two-tailed Student’s t-test was used to determine significance. When more than 2 groups with 1 variable were compared, a one-way ANOVA with Bonferroni post-test for FDR was used to determine significance. When more than 2 groups with two variables were compared, a two-way ANOVA with Bonferroni post-test for FDR was used to determine significance. For comparison of survival curves the Log-rank test was used. Significance was attained with a p-value  of <0.5 (*), <0.01 (**), <0.001 (***) and <0.0001 (****).GraphPad Prism v7 (GraphPad Software Inc.) was used for statistical analysis and production of graphs. When 2 groups were compared and C57BL/6  mice were purchased from Charles River UK. B6.SJL-Ptprca/BoyAiTac  mice bred and housed in the Beatson Biological Service and Research Units. All animal experiments have been carried out at the University of Glasgow and were approved by United Kingdom (UK) Animal Ethical Committees and performed according to UK Home Office project license 60/4512  guidelines.Supplementary InformationDescription of Additional Supplementary FilesSupplementary Data 1Supplementary Data 2Supplementary Data 3Supplementary Data 4Supplementary Data 5Supplementary Data 6Supplementary Data 7Supplementary Data 8Supplementary Data 9Supplementary Data 10Peer Review File


Equine infectious anemia virus (EIAV) is one of the most important threats to the equine industry globally. This is due to the poor performance of the affected horses, which requires euthanization of the infected animals upon the infection confirmation. Infected animals remain carriers throughout their life. EIAV infection has been reported in many parts of the world, including North America, Europe, Asia, and Africa. However, the EIAV status is never assessed in horses in the Gulf area, especially in the Kingdom of Saudi Arabia (KSA).This study aimed to perform molecular and serological surveillance among some horse populations in Eastern and Central Saudi Arabia.Sera and whole blood were collected from 361 horses and 19 donkeys from the eastern and central regions of Saudi Arabia during January 2014-December 2016. Sera were tested by the commercial EIAV enzyme-linked immunosorbent assay kits. Moreover, the collected blood samples were tested by the commercial real-time polymerase chain reaction kits.Our serological surveillance revealed the absence of any antibodies against EIAV in the tested animals. Similar results were reported for the tested horses’ plasma. This study confirms the absence of EIAV in horses and donkeys from Eastern and Central Saudi Arabia during the tenure of the current study. However, careful monitoring of the EIAV is highly recommended to avoid the emergence of such a virus in the horse population in Saudi Arabia.To the best of our knowledge, this is the first EIAV surveillance conducted not only in Saudi Arabia but also in the Gulf area. This study confirms the absence of EIAV in the tested equine population in the eastern and central regions of Saudi Arabia during 2014-2016. Retroviridae and genus Lentivirus. EIAV was reported in many parts of the world, including North America [in vivo in donkeys (DV117), in primary donkey monocyte-derived macrophages, and in fetal donkey dermal cells.Equine infectious anemia virus (EIAV) is one of the most devastating and notifiable viral diseases of the family Equidae . EIAV in America , South A America , Europe  America , and Asi America -11. UnfoThe prevalence of EIAV in China was controlled by nationwide utilization of EIAV DLV121 . The onlThe current study was designed to evaluate the status of some horse and donkey population in two major regions in the KSA. Meanwhile, some serum and whole blood from horses and donkeys were collected from the eastern and central regions of KSA, which have the most intensive horse population across the country. The collected sera were tested by the commercial ELISA kits. The whole blood was tested by the commercial quantitative polymerase chain reaction (q-PCR). To our knowledge, this is the first study investigating the molecular and serological prevalence of the EIAV among horses and donkeys in the eastern and central regions of Saudi Arabia.All animal experiments and sample collection were conducted as per the King Abdulaziz City for Science and Technology guidelines. This animal utilization protocol was amended by the King Faisal’s University Animal Ethics and the National Committee of Bioethics.The current study focused on two major regions from Saudi Arabia with dense equine populations, the eastern and the central regions. These two regions are homes of the majority of equine population in the KSA. Several horse stables were selected on Al-Hasa, Dammam, Al-Qatif, and Al-Jubail in the eastern region. Furthermore, other horse populations from Riyadh and Al-Qassim regions representing the central region were sampled . These sThree hundred and eighty serum samples were collected from horses and donkeys in various regions in Eastern and Central Saudi Arabia . All aniThe 380 whole blood samples out of the 361 from horses and 19 from donkeys sampled were collected via venipuncture. The blood samples were collected in the tubes containing ethylenediaminetetraacetic acid (EDTA), and gentle shaking was applied to mix the whole blood with the EDTA. The samples were transferred on ice to the authors’ laboratory. The whole blood was processed as previously described [® ID Screen® Equine Infectious Anemia Double Antigen ELISA kit, Cat No: EIAED-4P, Innovative Diagnostics, Montpelier, France) according to the manufacturer’s instructions and as previously described elsewhere [The collected serum samples were tested in duplicate using the commercially available ELISA kits  were extracted from the collected whole blood by the QIA-amp Viral Mini Kit  as per the manufacturer’s instructions. The viral NA concentration was assessed by the Nanodrop machine , and the NA samples were stored at −80® Easy Kit, Path-EIAV-Standard, PrimerDesign Ltd., Chandler’s Ford, United Kingdom). The real-time PCR technique was conducted according to the manufacturer’s instructions. Initially, the DNAs were denatured as previously described [™ qPCR master mix, 1 µl of EIAV probe, and 4 µl of DNAase/RNase-free water. 15 µL of master mix was transferred to each well of the real-time PCR plates. To the master mix, 5 µl of each NA sample was added to the assigned well. The PCR reaction conditions were reverse transcription at 55○C for 10 min, activation of the enzymes at 95○C for 2 min, denaturation at 95○C for 10 s, and then data collection at 60○C for 60 s. These parameters were repeated for 50 cycles. The test was valid when the positive control generated a cycle threshold (Ct) between cycles 16 and 23. The tested sample was considered positive if the Ct <35. This test was carried out in the ABI 7500 thermal cycler .The extracted viral NAs from the collected whole blood were evaluated for the EIAV proviral DNA with the commercial real-time PCR kits . Continuous surveillance of the equine population for the EIV is highly recommended not only in the Gulf area but also worldwide.MGH and AAA collected specimens, performed the laboratory techniques, data analysis, and drafted and revised the manuscript. Both authors read and approved the final manuscript.


Therapeutic approaches which aim to target Acute Myeloid Leukaemia through enhancement of patients’ immune responses have demonstrated limited efficacy to date, despite encouraging preclinical data. Examination of AML patients treated with azacitidine (AZA) and vorinostat (VOR) in a Phase II trial, demonstrated an increase in the expression of Cancer‐Testis Antigens  on blasts and that these can be recognised by circulating antigen‐specific T cells. Although the T cells have the potential to be activated by these unmasked antigens, the low arginine microenvironment created by AML blast Arginase II activity acts a metabolic brake leading to T cell exhaustion. T cells exhibit impaired proliferation, reduced IFN‐γ release and PD‐1 up‐regulation in response to antigen stimulation under low arginine conditions. Inhibition of arginine metabolism enhanced the proliferation and cytotoxicity of anti‐NY‐ESO T cells against AZA/VOR treated AML blasts, and can boost anti‐CD33 Chimeric Antigen Receptor‐T cell cytotoxicity. Therefore, measurement of plasma arginine concentrations in combination with therapeutic targeting of arginase activity in AML blasts could be a key adjunct to immunotherapy. What's new?To date, cellular immunotherapy strategies against acute myeloid leukaemia (AML) have demonstrated limited efficacy. Here, arginine concentrations in AML patients were shown to be significantly lower than in healthy controls, both at diagnosis and during immunomodulatory treatment. Although T cells were able to recognise and be activated by antigens expressed on AML blasts, the low arginine microenvironment acted as a metabolic brake on T cell function and expansion. Targeting arginine metabolism in AML patients should be an adjunct to current treatment strategies in order to enhance host anti‐leukaemia immunity and boost the activity of CAR‐T or adoptive T cell therapies. Versus Host Disease.T cell immunity plays a key role in the body's defence through the recognition of foreign antigens, expansion in T cells, and signalling through cytokines and cell surface molecules. However, in cancer patients, despite large numbers of abnormal cells being present, immune surveillance is subverted such that T cells fail to recognise the malignant cells or are inhibited in their proliferation or function. A resurgence of cellular immunotherapy strategies has shown the potential for T cells to eradicate leukaemia. Indeed, even relatively crude immune approaches such as allogeneic stem cell transplant in patients with high risk or relapsed AML demonstrate the clinical benefit of T cell activity, despite the risk of Graft Only a few new drugs have been developed for AML that have significantly altered patient outcomes—of these epigenetic modifiers such as azacitidine and vorinostat appear amongst the most promising.Recently the interaction between cancer cell metabolism and immunity has become a focus in understanding cancer‐immune evasion. The consumption of amino acids such as arginine have been shown to impact T cell responses in the laboratory setting, yet the translational importance of this mechanism in patients has not been explored.Blood samples were obtained from 80 AML patients ineligible for intensive chemotherapy treated with either azacitidine or azacitidine and vorinostat in a multi‐centre, randomised phase II trial .‐ΔT method plotted as arbitrary units of mRNA relative to GAPDH.RT‐Q‐PCR was used to detect Cancer‐Testis Antigens and Arginase II in purified patient‐derived AML blasts and cell lines. RNA was extracted using an RNeasy Mini kit . cDNA was prepared using SuperScriptTM III Reverse Transcriptase  after the manufacturer's instructions. RT‐Q‐PCR was done in duplicate using FAST SYBR Green Master Mix  and the Applied Biosystems 7500 Fast Real‐Time PCR system. Analysis of gene expression was calculated according to 2*02+ AML patients were identified by flow cytometry staining  of the whole blood. To identify AML patients which contained CTAG responsive T cells IFN‐γ release was measured by ELISPOT . In brief, 96‐well PDVF plates were coated with IFN‐γ capture antibody. PBMCs were thawed and plated in the presence of CTAG peptides (20 ng/ml). Influenza GIL and EBV YVL peptides were used as positive controls. After 36 hr, the plates were washed and biotinylated detection antibody added. Avidin‐HRP solution was added and the plate incubated for 45 min after a further wash, substrate solution was added, and left to develop until spots developed, at which point the reaction was terminated by washing, and the plate was left to dry. Spots were counted using a ELISPOT reader.HLA‐At‐Tests (parametric) were used to determine the statistical significance of the difference in paired observations between two groups . p values are two‐tailed and where values were <0.05,they were considered statistically significant. A Kaplan–Meier survival curve was generated using GraphPad PRISM.Methodological information regarding cell lines, flow cytometric analysis, mixed lymphocyte reactions, our AML murine models, ELISA and engineered T cells can be found in the supplements.a). Recently we investigated the clinical efficacy of combining azacitidine with vorinostat in a Phase II trial in AML and high risk MDS patients.Epigenetic modifying drugs such as azacitidine and vorinostat may boost the anti‐leukaemia T cell immune response by upregualting Cancer‐Testis Antigens expression.a) confirming our hypothesis. On recognition of target antigens, classically T cells respond through cell division, IFN‐γ release and cytotoxicity. Patient‐derived PBMC from 30 HLA‐A*02 patients were isolated before and during treatment , and pulsed with relevant CTAG peptides ex vivo. Increased activated anti‐CTAG T cells for MAGE, LAGE, and SSX2 antigens were particularly prominent as assessed by release of IFN‐γ release after AZA/VOR . However, although the drugs led to significant increase in antigen‐specific T cell activation compared to baseline, surprisingly, these responses are not greater than those of healthy donors .CTAGs are expressed in the context of HLA‐A*02. Analysis of AML blasts from HLA‐A*02 patients on the AZA/VOR clinical trial after three and six cycles of therapy identifies upregulation of the five families of CTA expression  compared to before drug administration in individual patients Fig. a confirp = 0.0078) compared to those from healthy donors . Phenotyping demonstrated upregulated PD1 expression (p = 0.0001) throughout treatment, with no changes in LAG3 or TIM3 . Thus, the expected physiological expansion of activated T cells in response to antigens on AML blasts is absent.We hypothesised that T cells in patients may be functionally exhausted—a state characterised by a failure to expand in response to stimulation and upregulation of cell surface inhibitory receptors such as PD1, LAG3 and TIM3.d and e). AML bearing mice showed significant reductions in the percentage of T cells in the bone marrow (p = 0.0002) and spleens  which also expressed increased PD1  consistent with our human findings . The mice had significant reductions in plasma arginine compared to controls .Arginine metabolism is a pathway which is aberrant in AML blasts and can influence the immune microenvironment.in vitro that T cell expansion in response to allogeneic dendritic cells was profoundly inhibited by the addition of recombinant human arginase to mimic AML blast activity  with a corresponding reduction in activation‐induced IFN‐γ release . Next equal numbers of human T cells (10 × 106) were engrafted into NOG‐SCID mice. T cells rapidly engrafted in the spleen (n = 14 days). Analogous to the arginine deplete microenvironment found in patients at diagnosis, administration of recombinant arginase led to a significant reduction in serum arginine  and a failure of T cells to expand . Notably overall survival was prolonged by the effects of arginine deprivation on T cells in these mice which otherwise develop Graft Versus Host Disease lethality from T cell responses to allo‐antigens .Nonself‐antigen presentation by an allogeneic MHC is a profound model of T cell stimulation and proliferation. To investigate the specific impact of plasma arginine concentrations, we first identified ity Fig. a with aase Fig. b. Next f) or supernatant arginine concentrations . Consistent with this, analysis of patients’ AML blasts demonstrated no change in Arginase II over time . Patients maintained an increase in plasma Arginine II enzyme  and significant reduction in arginine concentrations  throughout the trial. Therefore, the arginine deplete environment remains throughout therapy and can inhibit antigen‐dependent T cell responses in vitro and in vivo.Next we investigated the contribution of arginine metabolism on T cell responses in the trial patients. Arginase II can be regulated by histone deacetylases in nonmalignant cells, therefore we hypothesised that the AZA/VOR may also downregulate arginase activity in AML blasts.ons Fig. g. Consiime Fig. a. Patiein vitro. L‐NMMA and NOHA are two arginine analogues which can lead to reversible inhibition of arginine metabolism in vitro. Human T cells and purified AML blasts were first co‐cultured, in the presence of stimulatory allogeneic dendritic cells. AML blasts inhibited T cell proliferation replicating our murine findings. However, inhibition of arginase activity with L‐NMMA and L‐NOHA led to restoration of T cell proliferation. .Arginine catabolism appears to be a critical factor in holding back the immune response to antigen on AML blasts. We therefore investigated if targeting Arginase II enzyme activity could enhance the T cell response b).ex vivo, a process latterly used to generate adoptive immunotherapy. In co‐cultures engineered anti‐NY‐ESO T cells alone had no effect on K562 AML viability, including after K562 cells were pretreated with azacitidine and vorinostat . Although no additional upregulation of NY‐ESO was detected on K562 .NY‐ESO‐1 is an established AML‐associated cancer‐testis antigen that can be presented by HLA‐A2 positive blasts . Incubation of anti‐CD33 CAR‐T cells with K562 led to a reduction in the number of viable AML cells . Inhibition of arginine metabolism enhanced CAR‐T cell cytotoxicity against the AML cells and led to a further significant reduction in viable AML cells  Azacitidine and vorinostat did not affect CAR‐T cell cytotoxicity. Therefore, like autologous immune responses, engineered T cells have the capacity to recognise and kill AML blasts but their full potential is not realised until arginine metabolism is targeted and inhibited.We hypothesised that arginine metabolism may be similarly contributing to the failure of other antigen‐specific T cell immune therapies. Clinical responses with CAR‐T cell therapy for AML have lagged behind the notable successes in Acute Lymphoblastic Leukaemia, despite the presence of viable antigenic targets.The aberrant expression of Cancer‐Testis Antigens offers the potential to use a patient's immune system, or engineered immune therapies, to target AML. A number of CTAs including SCP1, MAGE, SPAN‐Xb, SLLP1 and PRAME CTAs have been identified in unmanipulated AML blasts and may correlate with an improved overall survival.Our findings are the first to report the clinical impact of the low arginine microenvironment on immune therapy approaches in patients, and extend our preclinical findings on the role of tumour arginine metabolism in suppressing immunity.Our study has important translational implications and help to explain the functional impairment in T cells seen in trials of peptide vaccines in AML patients or more recently with CAR‐T cells.F.M. and C.D.S designed the study, performed research, analysed data and wrote the study. R.W., S.B., L.F., E.S., V.S., T.P., K.K. performed research. C.C. provided access to patient samples as Chief Investigator of the RAVVA trial. F.M., C.C., K.K., and P.K. secured ethical approval for the study.Supplementary Figure 1 (a) Upregulation of CTAG expression in AML cell lines after AZA/VOR treatment as assessed by qPCR. Baseline expression illustrated with red line. (b) Example flow cytometry gating for HLA‐A*02 identification on AML blasts from patients. (c) NY‐ESO and SART3 antigen‐specific T cells from patients treated with azacitidine and vorinostat demonstrated increased IFN‐γ release in response to peptide stimulation ex vivo. IFN‐γ positive T cells were measured by ELISPOT. (d) MAGE‐specific T cells from patients treated with azacitidine and vorinostat demonstrated increased IFN‐γ release in response to CTAG peptide stimulation ex vivo. IFN‐γ positive T cells were measured by ELISPOT.Click here for additional data file.Supplementary Figure 2 (a) Antigen‐specific T cells from patients treated with azacitidine and vorinostat have comparable IFN‐γ release in response to CTAG peptide stimulation ex vivo compared to healthy donors. IFN‐γ positive T cells were measured by ELISPOT. (b) LAG3 and TIM3 (c) were assessed on CD3+ T cells from the blood of AML patients during treatment. (d) Flow cytometric gating strategy for the detection of CD45.2(AML blasts) and CD45.1 (CD3+ T cells) in the spleens of MLL‐AF9 syngeneic AML murine model. (e) Percentage of AML blasts in the bone marrow and spleens of MLL‐AF9 syngeneic murine model.Click here for additional data file.Supplementary Figure 3 (a) T cell proliferation is suppressed when co‐cultured with AML blasts from patients. Inhibition of arginine catabolism with LNMMA and NOHA rescues T cell proliferation in the allogeneic mixed leukocyte reactions. 7 representative patients shown. (b) Expression of HLA‐A2 in K562 cells before and after treatment with AZA/VOR. (c) Example flow cytometry gating for HLA‐A*02 identification on K562 after treatment with azacitidine and vorinostat.Click here for additional data file.Appendix S1: Supporting informationClick here for additional data file.


In pace with the development of gene sequencing technology and transcriptome research, it has been found that 70 to 90% of the human genome is transcribed into RNAs, while only 2% of RNAs encode proteins. This implies that non-coding RNAs (ncRNAs) may exert vital biological functions and a full analysis of non-coding transcriptomes is needed. Over the past decade, the advance in high-throughput sequencing and transcriptome profiling has enabled the identification of circular RNAs (circRNAs) involved in many biological processes and the occurrence and development of diseases. Accumulating evidence has revealed that circRNAs may serve as new biomarkers for diagnosis as well as provide promising therapeutic approaches and novel drug screening strategies for leukemia. A comprehensive understanding of circRNAs in leukemia is a prerequisite for the development of clinical translational research. In this review, we will discuss the general information of circRNAs and focus on the current advances in understanding the association between dysregulated circRNAs and leukemia. In 1976, since Sanger  extracteCircRNAs, a family of single-strand ncRNAs with covalently closed circular isoforms, are generated from precursor mRNAs (pre-mRNAs)  and can Based on present study, widespread presence of circRNAs derived from various types of human samples is elucidated . It laysLeukemia is a life-threatening cancer with cloned hematopoietic stem cells and most often diagnosed in adults (mid 60s). The most common types of leukemia are acute myeloid leukemia (AML), acute lymphoblastic leukemia (ALL), chronic myeloid leukemia (CML) and chronic lymphocytic leukemia (CLL). With no clear preventive or control measures at present, leukemia is still a malignant disease and a threat to public health. Several studies have noted the important role of ncRNAs, such as microRNAs (miRNAs) and long non-coding RNAs (lncRNAs) in the pathogenesis of leukemia –43. CircAML is the most common acute leukemia in adults. The incidence of AML increases with age and patients show significantly multifaceted biological and clinical heterogeneity. Recent studies have revealed the value of circRNAs in AML. While the expression pattern of circRNAs might be impaired anomalous in leukemia cells, altered circRNAs could be involved in leukemogenesis as well .The cytogenetic and molecular genetic characteristics are significant prognostic factors for AML patients. In some cases, circRNAs make us better understand the pathogenic mechanism of AML. Despite the fact that some genomic amplicons are related to poor prognosis, the internal structures of amplicon formation and their potential mechanisms in AML have not yet been clarified yet. 8q24 amplifications are associated with aberrant chimeric genes and could generate oncogenic lncRNAs that play functional roles in leukemia . Circ-PVNPM1) was regarded as one of the most frequently mutated genes in AML. Bearing both proto-oncogene and tumor-suppressing properties, NPM1 could be involved in ribosomal biogenesis, apoptosis, and cell proliferation by encoding a multifunctional chaperone protein. The mutation of NPM1 might contribute to AML [NPM1 in AML and aiming to deepen the understanding of multifaceted gene, Hirsch [NPM1 through RNA-Seq-based transcriptome analysis. In NPM1 wild-type and mutated AML patients, circNPM1 75001 was highly expressed in AML patients. Although circNPM1 75001 was independent of the NPM1 mutational status, a positive correlation was found between the expression of circNPM1 and total NPM1. Li’s study also suggested an independent relationship between circRNAs and their linear host mRNAs [Nucleophosmin , which always corresponds with relapse and refractory, is relatively common in AML . Given tThe majority of circRNAs were reported to alleviate the effects induced by miRNAs. Regulatory relationships between circRNAs, miRNA and their target genes were deciphered in ALL is a lymphoid malignancy affecting the B or T lineages. Its incidence peaks are between ages 2 and 5 years and the elders . EmerginJAK2, PAX5, IKZF1, ETV6 and EBF1) are prevalently present in hyperdiploid leukemia compared with normal leukocytes samples [Based on RNA-seq results in hyperdiploid B-cell precursor ALL samples, circRNAs were found to be produced from one specific gene and differentially expressed in cells and diseases . For exa samples .Adults and senile patients of AML are often companied with poor outcomes. Although most children with ALL can be cured, a small number of patients who relapse after treatment have poor prognosis . Given tBCR-ABL1 which encodes a hyperactive tyrosine kinase is the major molecular factor for the pathogenesis of CML [Chronic myeloid leukemia (CML) is a clonal myeloproliferative neoplasm originating from abnormal pluripotent stem cells. The oncogene s of CML . Imatinis of CML . RecentlBCR-ABL1 fusion genes was analyzed. Of note, circBA9.3 which increased the protein expression levels of ABL1 and BCR-ABL1 was associated with TKI resistance. Over-expressed in leukemia cells, circBA9.3 could facilitate cell proliferation and drug resistance. It is inspiring that circBA9.3 may serve as a promising diagnostic biomarker and therapeutic target for CML patients [To explore the internal mechanism of chemo-resistance and remove the obstacles to cure patients, f-circRNA circBA9.3 derived from the patients .CLL is a heterogeneous disease characterized by the monoclonal expansion of B cells. It is the most common adult leukemia in the West and the median age at diagnosis is 71 years ,75. BecaCBFB on chromosome 16 and aberrantly over-expressed in CLL patients, was determined to promote cell proliferation and suppress apoptosis through miR-607/FZD3/Wnt/β-catenin pathway [Based on the RNA-seq data, 52 circRNAs were identified and the role of one circRNA in distinguishing different B-cell malignancies was suggested . Hsa_cir pathway . Given t pathway  has elucAlthough the molecular mechanisms of circRNAs are poorly understood in leukemia, they are indeed implicated in cellular processes and leukemia progression. Encouragingly, the exploration of aberrant circRNAs has provided us with valuable insight into the pathogenesis of hematological malignancies.Originated from human cancer xenografts, circRNAs could enter the circulation by exosomes and be easily detected in serum or plasma. Exosomes are small extracellular vesicles (EVs) (30–150 nm in size)  that areA big step has been taken toward understanding the pathogenesis of leukemia since f-circRNAs have been identified and verified to promote leukemogenesis and other diseases ,90. ChroIn this review, we summarize the latest research progress of circRNAs and highlight their biological significance and clinical values in leukemia. CircRNAs have been shown to play nonnegligible roles as gene regulators and perform crucial biological functions via ceRNA mechanism in leukemia. Other than indicating the occurrence of leukemia, circRNAs have the potential to be indicators of disease stage and progression and could be developed as medication for clinical use. With more in-depth study, we expect that circRNAs can be more appropriately and precisely used in clinical diagnosis and treatment in the future.


Acute myeloid leukemia (AML) is a malignant hematological disease in which nearly half have normal cytogenetics. We have tried to find some significant molecular markers for this part of the cytogenetic normal AML, which hopes to provide a benefit for the diagnosis, molecular typing and prognosis prediction of AML patients. In the present study, we calculated and compared the gene expression profiles of cytogenetically normal acute myeloid leukemia (CN-AML) patients in database of The Cancer Genome Atlas (TCGA), Gene Expression Omnibus (GEO) and dataset Vizome , and we have demonstrated a correlation between PDE7B gene and CN-AML. Then we proceeded to a survival analysis and prognostic risk analysis between the expression levels of PDE7B gene and CN-AML patients. The result showed that the event-free survival (EFS) and overall survival (OS) were significantly shorter in CN-AML patients with high PDE7B levels in each dataset. And we detected a significantly higher expression level of PDE7B in the leukemia stem cell (LSC) positive group. The Cox proportional hazards regression model showed that PDE7B is an independent risk predictor for CN-AML. All results indicate that PDE7B is an unfavorable prognostic factor for CN-AML. In 1976, the French-America-Britain (FAB) classification based on traditional bone marrow cell morphology and cytochemical staining divided AML into 8 subtypes of M0 ~ M75. However, the classification criteria have certain limitations on the role of clinical prognosis and guiding treatment. In 2001, the international hematology community launched the WHO diagnostic classification system for hematopoietic malignancies, namely the MICM  standard6. This standard further systematically and comprehensively classified AML, which has important guiding significance for clinical treatment.Acute myeloid leukemia (AML) is a group of malignant clonal hematological diseases that originate from hematopoietic stem cells (HSC) and is highly heterogeneous7. Mutant genes obtained from 200 samples can be classified into a total of 9 categories according to biological function definitions, including transcription-factor fusions genes , the gene encoding nucleophosmin (NPM1), tumor-suppressor genes , DNA-methylation-related genes , signal transduction pathway-related genes , chromatin-modifying genes , myeloid transcription-factor genes , cohesin-complex genes , and spliceosome-complex genes . The discovery of these genes makes an important contribution to the accurate diagnosis of AML.In recent years, the role of gene mutations in the pathogenesis of AML has been increasingly revealed, which has become a new marker of molecular diagnosis and a potential therapeutic target. In 2013, it has been reported that after the genome-wide or whole-exome sequencing analysis of 200 adult patients of de novo AML, 23 genes  with a higher-than-expected mutation prevalence were summarized, and 57 novel fusion genes were identified8. Although cytogenetic examination is important for patient outcomes and the choice of individualized treatment regimens9, while nearly half of AML patients lack clonal chromosomal abnormalities10 and it may not be effective for this subset of patients. Therefore, it is necessary to find more potential biomarkers for prognosis prediction and treatment of AML patients with normal cytogenetic.With the continuous development of precision medicine, it has enriched the treatment of AML. However, even with high-dose combination chemotherapy and hematopoietic stem cell transplantation, the recurrence rate of AML is still high and the 5-year overall survival rate is less than 40%12. A number of studies have shown that PDE7B may play a role in a variety of central nervous system diseases by affecting cAMP levels, and found that PDE7B may be involved in dopaminergic signaling in striatal neurons and play a key role in memory function15. PDE7B also has been found to have prognostic significance in a variety of cancers, such as chronic lymphocytic leukemia 16, mantle cell lymphoma (high expression level of PDE7B is a poor prognostic indicator)17, glioblastoma (high expression level of PDE7B has a worse prognosis)18 and breast cancer (high expression level of PDE7B predicts poor prognosis)19. In addition, PDE7B is overexpressed in glioblastoma and serves as an important cell growth medium18. cAMP promotes growth arrest and/or apoptosis of various types of lymphoma, particularly CLL, and PDE7 inhibitors can increase cAMP concentration and kill CLL cells21, which is suggesting that PDE7B may act as a therapeutic target in CLL. Intracellular cAMP levels are critical for the differentiation of leukemia cells22, which shows the potential of PDE7B as a cAMP-specific hydrolase in the prognostic significance and treatment of leukemia, including AML.PDE7B is a phosphodiesterase (PDE) with high affinity and specificity for cAMP (cyclic adenosine monophosphate), which reduces intracellular cAMP concentration by hydrolysisHowever, there have been no reports to date on the expression of PDE7B in AML patients and its relationship with the prognosis of AML patients. Therefore, we investigated the expression level of PDE7B in CN-AML patients and systematically analyzed its relationship with the prognosis of CN-AML patients. As the results presented in our research, we found that CN-AML patients with high expression of PDE7B had shorter survival times, suggesting that the PDE7B gene is an unfavorable prognostic marker for CN-AML.We performed a survival analysis of 75 CN-AML patients from the TCGA database and found that EFS  play an important role in the occurrence and development of AML, and CD34First, we divided 75 CN-AML patients from the TCGA database into PDE7B high group (40 patients) and PDE7B low group (35 patients) according to the expression level of PDE7B. Then, the difference of the baseline characteristics of CN-AML between the PDE7B high group and the PDE7B low group were analyzed. White blood cell (WBC) counts were significantly higher in the PDE7B high group than in the PDE7B low group  was shortened by several years compared with the low level PDE7B mRNA16. And then it has been suggested that cAMP can inhibit the growth of various types of lymphoma , while PDE7 inhibitors (nonselective for PDE7A and PDE7B) can kill CLL cells by increasing cAMP concentration, which may be a useful treatment for such diseases21. cAMP is an important second messenger in cell signaling, and intracellular cAMP levels are critical for the maturation and differentiation of leukemia cells22. Moreover, it was also found that elevated levels of cAMP lead to arrest of G1 phase in acute promyelocytic leukemia cells24. Therefore, it is not difficult to speculate that PDE7B, as a specific hydrolase of cAMP, may play an important role in the development of leukemia cells by regulating the concentration of cAMP.In 2000, J. M. Hetman +/CD38+ group.AML is a type of malignant hematological disease originating from hematopoietic progenitor cells, nearly half of which is CN-AML. And more and more mutant genes have been found to contribute to the diagnosis and prognosis prediction of CN-AML patients. In the present study, we calculated and compared the gene expression profiles of CN-AML patients in multiple datasets, followed by survival analysis and prognostic risk analysis. And we have demonstrated a correlation between PDE7B gene and AML. The correlation is shown in the following points. 1) PDE7B is an independent prognostic predictor of CN-AML patients. 2) high expression level of PDE7B predicts a shorter survival time in either CN-AML patients or AML patients who have received Allo-HSCT or chemotherapy. 3) PDE7B is high expressed in LSC positive group and CD3426. As showed in our results, we compared the difference in the expression level of PDE7B between the LSC positive group and the LSC negative group and found that it was higher in the LSC positive group. It is currently accepted that CD34+/CD38− is a molecular phenotype of the LSC27. In addition, acute leukemia is partially composed of immature progenitor cells with undetermined lineage25, and CD34+/CD38+ is a surface marker of hematopoietic progenitor cells28. Our results showed that the expression level of PDE7B gene was significantly elevated in the CD34+/CD38+ group. CD34−/CD38− identifies differentiated mature cells in which PDE7B expression is reduced. As mentioned earlier, PDE7B is a specific hydrolase for cAMP which is critical for leukemia cell differentiation. So that might explain why PDE7B is higher in the CD34+/CD38+ group and lower in the CD34−/CD38− group. Therefore, we can speculate that high expression of PDE7B may lead to a decrease in intracellular cAMP levels, which in turn prevents leukemia cells from further differentiation and maturation. In short, high levels of PDE7B may favor LSCs and produce a poor prognosis for AML.LSCs are a group of tumor stem cells that have the ability to self-renew and produce heterogeneous leukemia cell populations. LSCs are an important cause of leukemia recurrence after different treatment regimens. And numerous studies have shown that LSC may be a new therapeutic target for hematological tumorsAlthough genetic alterations are an important part of the pathogenesis of AML, many of the mutant genes  which have been identified in recent years have contributed a lot to it. It is especially important for the diagnosis, prognosis prediction and targeted therapy of CN-AML patients. In our Cox proportional hazards regression model, we have calculated many AML-associated mutant genes and found that DNMT3A and FLT3 are high risk factors for CN-AML patients , while NPM1 and NRAS are favorable genes , and the PDE7B gene is the most significant one (unfavorable gene) by comparing the P value. In addition, we analyzed the relationship between those mutant genes and the expression level of PDE7B, and found that the three states  of IDH1 gene are significant difference between the PDE7B high group and the PDE7B low group.Althoug our study have demonstrated that high level of PDE7B gene indicates poor prognosis in CN-AML patients. The mechanism of action of PDE7B in CN-AML is not clear and we just speculated that it may play a role by affecting the concentration of cAMP in CN-AML. In addition, how the PDE7B gene regulates LSC is also unknown. In general, more in-depth and sophisticated research needs to be done in the next step.In conclusion, we found in our study that PDE7B gene is an independent prognostic predictor of CN-AML, and that high expression level of PDE7B gene is an unfavorable prognostic factor for CN-AML. The high expression of PDE7B gene has a significant correlation with leukemia stem cells. Anyway, this study reflects the potential and prospects of the PDE7B gene in the prognosis, targeted therapy, and risk stratification of AML patients.29 U133B (162 CN-AML samples), GSE7101430 (104 CN-AML samples), GSE2277831 GPL8653 (54 CN-AML samples) GSE22778, GPL10107 (34 CN-AML samples), and a recently published study 32. To understand the relationship between the expression level of PDE7B and the prognosis of patients with treated AML, we collected 67 AML samples who had received allogeneic hematopoietic stem cell transplantation (Allo-HSCT) and 92 AML samples who had received chemotherapy from the database TCGA and compared their survival time between the high expression level of PDE7B and the low level PDE7B group. Event-free survival time (EFS) was defined as from registration to death (for any reason), disease progression or recurrence, or last contact. Overall survival time (OS) was defined as from registration to death (for any reason) or last contact. And the expression levels of PDE7B under four molecular groups in GSE7600433  were compared. In addition, samples in this dataset were classified according to LSC positive (138 samples) or LSC negative (89 samples), and the difference in expression of PDE7B between the two groups was compared. The study complies with the Helsinki Declaration.By performing the survival analysis of each gene with the data of gene expression and EFS (and OS) from The Cancer Genome Atlas (TCGA) CN-AML samples, the P value and hazard ratio (HR) of each gene were calculated. The PDE7B gene was in the top position by ranking the P value of each gene. Subsequently, we further analyzed the relationship between PDE7B expression levels and survival time of CN-AML patients, including TCGA (75 CN-AML samples), GSE12417We calculated the gene expression with the robust multiarray averaging (RMA) algorithm in the GEO database and detected the gene expression with RPKM from the RNA-seq datas in the TCGA database. The value of PDE7B gene expression was log transformed (log2). We used maximally selected rank statistics algorithm from survminer package to divide the test samples in each dataset into PDE7B high expression group and PDE7B low expression group.Statistical analysis used R software v3.1.3 (ggplot2 and survminer package). Measurement data between the two groups were analyzed by unpaired t test (such as the difference of PDE7B expression between LSC positive group and LSC negative group), and multiple groups were tested by ANOVA test (such as the difference of PDE7B expression in different molecular types). Fisher’s exact test was used to analyze the numeration data (such as the deference of some baseline features of AML between high expression level of PDE7B and low level PDE7B). Kaplan-Meier survival curves and Log-rank test were used for survival analysis in AML patients. The Cox proportional hazards regression model for multivariate analysis was used to analyze the prognosis of multivariates associated with CN-AML. In any case, P < 0.05 was considered statistically significant.Supplementary data


Integration of different cyber-physical systems involves a development process that takes into account some solutions for intercommunicating and interoperating heterogeneous devices. Each device can be managed as a thing within the Internet-of-Things concept by using web technologies. In addition, a “thing” can be managed as an encapsulated component by applying component-based software engineering principles. Based on this context, we propose a solution for integrating heterogeneous systems using a specific component-based technology. Specifically, we focus on enabling the connection of different types of subsystems present in smart home solutions. This technology enables interoperability by applying a homogeneous component representation that provides communication features through web sockets, and by implementing gateways in proprietary network connections. Furthermore, our solution eases the extension of these systems by means of abstract representations of the architectures and devices that form part of them. The approach is validated through an example scenario with different subsystems of a smart home solution. With the increasing development of technological devices, more and more communication capabilities are being provided. Most devices  are now or will be soon connected to the Internet  and someIn this kind of system, sensors are the main source of information and, therefore, the obtained data should be shared with the rest of the parts that require it . In addiRegardless of the domain, we can find examples of interoperability solutions based on common operating systems , supported by a middleware in terms of a programming language , offerinWe can see this heterogeneity in an example scenario of remotely monitoring the fitness activity of a person who is in his/her house see . This chAll the mentioned systems use different technologies and communication protocols and they cannot be easily connected to perform a common task. In this case, the goal of the scenario is to connect the customer (the character at home) with a personal trainer  the smart home applications.A back-end infrastructure offering the available operations as web services supports the management of the architectures and components.The communication between devices is accomplished through an homogeneous layer by using web technologies.Modularity properties (coupling and cohesion) have been analyzed to determine the division of a smart home solution into different subsystems.Architecture and component models for defining this kind of the solution are described by an example scenario.Different alternatives of communication in these solutions are identified and exemplified with the corresponding data flows.Implementation examples of gateways which enable the communication with proprietary technologies are described.This article proposes an approach based on CBSE and modeling techniques to develop solutions of CPSs in general and smart homes in particular. The proposal is focused on enabling the interoperability between heterogeneous devices belonging to the same system and also between heterogeneous CPSs. In particular, our approach includes design and implementation principles based on a component technology called COScore , which aThe rest of the paper is organized as follows. As discussed in the previous section, to support the extension and inclusion of different types of CPS, we have developed our own technological infrastructure . Its development is based on CBSE, Model-Driven Engineering (MDE), and Cloud Computing-based technology, and it is widely described in . In ordehttps://kodi.tv/). In this case, we can create three components: KodiController, SenderController, and SenderInterface (right side of SenderInterface), and the other (SenderController) is responsible for sending the information to KodiController so that the URL of the resource can be transmitted. This division of these last two components allows us to build different interface components  and have a single controller component. Regarding the technological aspects, the user application components are implemented as web components using the Polymer technology [https://github.com/acgtic211/nha_video_viewer_interface.Let us consider the chnology , which ohttp://wildfly.org) in COScore for providing the services that are valid for all the platforms. Its functionalities are based on the component descriptions and their relationships, regardless of the platform on which they are deployed. This application server offers a set of RESTful web services developed with JAX-RS, which are called up by HTTP requests.All user application components are grouped forming an architecture  the core content; (3) the interaction interface; and (4) the controller interface. Regarding the functionality, a component includes the interaction content that is used for implementing the business logic of the interaction with the user, and the core content (which is the main part of a component) to store the methods implementing the rest of a component behavior. The two interfaces are the interaction interface storing the methods for handling interaction events with the user, and the controller interface that is used for managing the communication with other components. In our approach, the operations of a component are accessible from the outside through both the interaction and controller interfaces.Each component is structured internally in four parts to define its functionality and interfaces see : (1) thecontainer component, which identifies a component that contains other components, making it possible to build complex components from more basic ones; (b) the functional component (with core content), which is used to construct functional components without user interaction, and therefore, can be built to execute background code; (c) the user interaction component, which is used to build components that include user interaction (using interaction interface and interaction content) or simply display information (with interaction interface); and finally, (d) the normal component , which is the union of functional and user interaction component types, and therefore, it is a component that includes interaction with the user and the internal functionality of the component.All the components need to use the controller interface, but depending on the rest of implemented parts, we can pick out different types of components: (a) the KodiController are: (1) host, used to identify the host where KODI is installed; (2) port, used to indicate the port for the remote control of KODI via HTTP; (3) username and (4) password, used to indicate the user name and password to get control of KODI.Also, each component contains a list of properties. Properties may provide information on non-functional properties (NFPs) , component appearance, such as width, height, etc.) and any dependencies on other components. Some of these properties can be modified and should be taken into account at run-time. For example, four properties defined by the component SenderInterface defines the required interface ManageItem to send a resource selected by the user to KODI. In order to receive the resource, the component SenderController defines the provided interface ManageItem. Next, the required interface ManageItem belonging to this component will send the resource to the provided interface ManagePlayer belonging to the component KodiController. With this summary of the most relevant aspects of our infrastructure, we can now describe how we achieve interoperability between different CPSs.As indicated above, the controller interface is used for managing the communication with other components. It is comprised of a set of provided and required interfaces, with the condition that each component must have at least one provided interface. The provided interfaces define all the component functionalities visible to the outside world, i.e., it describes methods that can be invoked to initiate the execution of some operation. The required interfaces describe the operations belonging to other components invoked by a component for its proper operation. In the example, the component The communication between heterogeneous CPSs requires the use of mechanisms supporting the connection of the different protocols and technologies related to the devices forming each system. With this aim, our component-based technology provides the models and abstract definitions needed to describe the architectural structure and the involved components. In addition to these models, it is necessary to formally define a set of principles and rules to enable the interoperability in CPSs thus driving the development and maintenance of such systems. To describe these principles, this section comes back to the previous example scenario of As shown in gateway if the system has a device which involves the use of a specific communication protocol different from the message exchange through the components’ input and output ports. If, on the contrary, the components can communicate with each other by using this port mechanism, the data is sent and received with the use of Web sockets through the communication web service of the COScore, as explained in Low coupling connection from a CPS to the COScore. This type occurs when a component (or a system) is intended to send data to another component (belonging to the same or to other system) through the COScore. In the example scenario, the multimedia UI of the personal trainer sends the video data to the TV system of the monitored customer with this kind of connection.Low coupling connection from the COScore to a CPS. This connection is focused on solving the reception of data from another component (or a system) through the COScore. In the scenario, the UI showing the heart rate is connected in this manner.High coupling connection between a CPS and the COScore. This connection is used when a component of a CPS is required to establish a bidirectional communication with another component or it establishes a unidirectional communication with it but the COScore sends some feedback information. For example, the UI of the security system needs to (1) send the information about the alarm activation and (2) receive the trigger event if the window detects an intruder.Previous connection types but using a gateway as intermediary. As mentioned, a gateway is required if a component needs to communicate with a specific communication protocol. For example, the home automation sensor establishes a bidirectional communication with the UI of the same system through a gateway because the sensor is deployed on a KNX network .Moreover, the connection may require the presence of a In our approach, gateways are implemented as software components conforming the definitions of the background technology. Furthermore, this kind of component includes some communication methods which are not exposed by means of ports and therefore such operations are not represented in the models within provided or required interfaces. These methods are included as part of the code implementation with the aim of communicating with a physical device (or network) through a specific protocol. Nevertheless, these operations are usually invoked from the execution of the functionality related to the sending and receiving actions of the ports.HFitbitIonicController).The SW-Gateway of the scenario is a software component intended to communicate (a) with the heart rate sensor of the smart watch; and (b) with the UI that shows a graphical representation of the heart rate. The first interoperability process is performed through the gateway implementation and it includes POST messages between the smart watch and the gateway software component to obtain the value of the heart rate. The second interoperability process is accomplished by using the COScore services as intermediate through a communication port of a required interface , but it is pro-active for sending the value to other components periodically. To this end, the output communication port sendHRS of the required interface emits a message through a web socket (lines 1–10 of Listing 1). When the COScore receives the message, it is routed to the CPS with the UI which shows the heart rate. The function of this output port is activated when it receives a POST request from the smart watch (lines 12–21). This request can be answered because a proxy server is created to this end (lines 23–29).The required interface of the controller interface contains the methods implementation of the functional interfaces of a component. Thus, parameter entries and return data from these methods are solved by input and output ports by using WebSockets [sender component emits a message through an output port, it is received by the COScore. Then, the COScore checks the architectural representation of the solution, which describes the connection of all the components from the different CPSs. Next, the COScore emits a new message through a web socket to be received by the component connected with the sender .Apart from gateways, the generic behavior to solve the interoperability between the devices of a solution formed by different CPSs is related to the controller interfaces of the components implementing the behavior of such devices. The bSockets  and the bSockets . When a Listing 1: Chunks of code of the SW-Gateway component implementation.With this approach, a sender can be connected with multiple receivers and vice versa. Furthermore, input ports belonging to both types can be activated from the COScore with the need of waiting to the normal execution of the components’ business logic. As a consequence, component operations can be invoked as an API, considering and managing the indirect communications that may occur as a result of the activation of a certain operation.Interoperability must be ensured even when the Internet connection is not available. For this reason, we have developed a local version of the COScore called ECOScore (from Embedded COScore). This version is not offered as a cloud service but is deployed in a single board computing (SBC) which must be installed in each cyber-physical system or in a common local network connecting different CPSs. As a consequence, the access to centralized cloud service will be filtered by the ECOScore: if the Internet is accessible, the requests are solved by the COScore and, in the other case, they are responded by the ECOScore.As previously described in the Introduction, the proposed scenario comprises various CPS systems. This scenario has been built through the utilization of a diversity of devices and technologies to illustrate the capacity of developed technology. Logically, as addressing comprehensive set-up in detail would be extensive, this example scenario focuses on certain elements of each system and of two possible interactions: (1) interaction between the devices belonging to two different cyber-systems in which human intervention does not figure and; (2) interaction between two humans with the support of several CPSs. The first kind of interaction is utilized to validate the application of our approach when two devices or subsystems communicate with each other. Both cyber-physical parts can use their own communication protocol but the software components  enable the interaction by using a common communication layer. The second kind of interaction allows us to validate how our approach is useful for enabling communication between users. In this sense, users are provided with software components, including interfaces with or without graphical representation, which establish communication channels between humans and smart home devices, and also between different humans acting as clients of a shared system.The first interaction is related to the security system. Capacitive sensors are used on the exterior windows and doors of the house connected to Raspberry Pi boards. These sensors are connected through an electro-conductive paint that extends over the surface of the window or door, thus enabling potential difference to be measured and using the measurement to detect the presence of an individual; allowing it to act as an intrusion detector. In the event that this happens, the system should set off a sound alarm (a device belonging to a multimedia system), to signal the alert of an unwanted presence and act as a deterrent effect. ConductiveSwitchController, BuzzerController and KNXZennioACTinBOXClassicHybridController) and, moreover, the corresponding interface components are linked (ConductiveSwitchInterface and BuzzerInterface). Also, in the figure, one can observe the different relationships between the components across their corresponding provided and required interfaces. Let us describe what happens since an intrusion is detected until an alarm sounds. In this situation, the following process takes place:(1)ConductiveSwitchInterface component transmits the data across the port of the required interface ManageChange.change to the connected port of the provided interface ManageChange.change of the ConductiveSwitchController.Each time a modification in the potential difference is produced, the (2)ManageInput.setInput, transmits the data through the port of the provided interface ManageInput.setInput1 of the component KNXZennioACTinBOXClassicHybridController in order to activate the corresponding input.This, exceeding a true pre-established threshold and by means of the port of the required interface (3)KNXZennioACTinBOXClassicHybridController activates the output, thus communicating across the port of the required interface ManageStatus.setStatus1 with the port of the provided interface ManageBuzzer.playPause of the BuzzerController component.Next, the component (4)BuzzerController component communicates through the output port of the required interface ManageBuzzer.playPause with input port of the provided interface ManageBuzzer.playPause of the component BuzzerInterface signaling it to playback the alarm sound.Finally, the Focusing attention on the security system of installation 1, it can be seen that a controller component has been incorporated into each of the physical devices . Moreover, the user has a smart watch (Fitbit Ionic model) which has a heart rate sensor to measure heart rate. The personal trainer can select and preview a video from among a series of videos from the installation 2  in order to send it directly to the television of the customer through the multimedia center. Furthermore, the system permits the monitoring of heart rate in real time and thus prevents whatever risk. DHKodiController component has been incorporated into the installation 1, which enables communication with the API JSON-RPC of KODI, and the previously mentioned HFitbitIonicController, which receives information and also permits its transmission to the watch. It is essential to highlight the infrastructure used to obtain the data from the watch sensors. On the one hand, it has been necessary to develop an application for the watch and the mobile phone  to which it is paired. On the other hand, the installation of a web server with a digital certificate has also been necessary (to provide secure connections) which acts as a proxy. The personal trainer’s installation  is made up of the controller components DHKodiItemSenderController and HHeartRateSensorController, together with their interface components DHKodiItemSenderInterface, DHVideoViewerInterface and HHeartRateSensorInterface, which interact as shown in (1)DHKodiItemSenderInterface component communicates through the port of the required interface ManageItem.previewVideo with the provided interface ManageVideo.setVideo of the component DHVideoViewerInterface if the trainer decides to preview a video (this last component will be charged with its reproduction).Optionally, the (2)DHKodiItemSenderInterface interface component indicates the video to the DHKodiItemSenderController component, through the connection between the port of the required interface ManageItem.sendItem of the former and the port of the provided interface ManageItem.sendItem of the latter.Once the decision to send the exercise video to the user is performed, the (3)ManageItem.openItem to the port of the provided interface ManagePlayer.openItem of the DHKodiController component in the customer installation.Next, this last component sends the command to playback the video across the port of the required interface (4)–(5)DHKodiController component interacts with the API JSON-RPC of KODI (executing a GET operation and obtaining the response with the result) and the video starts on the user’s television.To finalize, the Returning to the architecture of the components in (6)The smart watch obtains the sensor data and sends it to the mobile.(7)This device executes a POST request to the web server with the digital certificate, which includes the data read by the sensor.(8)HFitbitIonicController component.The server redirects the request to the REST web service offered by the (9)–(11)ManageHRS.sendHRS) with the port of the provided interface ManageGraph.appendMeasure of the HHeartRateSensorController.Now, this component sends a response (steps #9–#11) and communicates (through the port of the required interface (12)It sends the value read by the sensor to the trainer’s UI.(13)ManageGraph.appendMeasure, sends the new readings to the port of the provided interface ManageGraph.appendMeasure of the HHeartRateSensorInterface component.This last component, through the port of the required interface The user views the video and, just before beginning the exercise, starts the application on the watch such that the trainer is able to monitor heart rate :(6)The sFinally, this interface component will modify the graph visualized by the trainer. Through this example it is shown how the software components, as well as the interconnection of different devices and technologies within the same system, offer us the possibility of performing communication and interoperation processes between different systems.In the literature, there are different types of middleware solutions for the Internet of Things , although some approaches use a combination of these types to integrate heterogeneous devices . In the The use of Internet-based middlewares can be oriented to resolve the interoperability between IoT devices that use different communication protocols. For example, we can use abstract representations of the systems and the communication protocols to create and deploy run-time solutions to IoT interoperability using only high-level models. For example, in  authors The concept of adaptive middlewares for cyber-physical systems highlights the need for a holistic view considering horizontal and vertical aspects that can be described through abstractions to solve the interoperability and integration of heterogeneous devices . We alsoThe concept of the Web-of-Things (WoT) is based on IoT and tries to integrate the networked devices  into the Web by means of web technologies . For exaInteroperability is a major problem related not only to those cyber-physical systems formed by heterogeneous IoT devices that use different communication protocols, but also to installations composed by a set of CPSs interconnected and sharing information. Some mechanisms concerning CBSE and MDE paradigms have proven their usefulness to develop this kind of system and ease the interoperability, and moreover, to maintain them and adapt their behavior to new requirements. Smart homes are a particular case of CPS and their application is growing in normal houses from the integration of existing subsystems that are working separately. This specific domain is an ideal scenario where different types of devices (with proprietary protocols) are interconnected and new elements are added to include new functionality. As a main part of these solutions, sensors are in charge of capturing the input information and sharing it with the rest of the elements of an installation. Furthermore, sensors are not only present as physical devices, but also are implemented as software components to (1) supplement the actions of existing physical elements; (2) emulate their actions if these devices are not installed; and (3) provide another sort of information that cannot be acquired by a physical sensor .In this paper we define a solution focused on enabling the interoperability between heterogeneous devices  that form part of the same system and also between different CPSs. To this end, our approach proposes a set of design and implementation principles based on a component technology. Such technology includes the application of cloud service called COScore, which manages the software architectures that implement the cyber-physical systems. This management consists of the manipulation of the models representing the architectures and their realization to specific platforms. In this case, the technology also includes a platform-specific model to build and deploy the software architectures by using web components, in particular, implemented with Polymer. The solution for interoperability gathers (1) the unified communication through web sockets between all the software components that implement, control and show the behavior of the heterogeneous devices that form part of the CPSs; and (2) the use of gateways when a device or a system requires the utilization of a communication protocol different from the message exchange through the web sockets. Furthermore, we ensure the interoperability when there is no Internet connection by deploying a local version of the COScore called ECOScore. It is a reduced version of the cloud service which enables the communication between devices in the same network.This approach is not valid for all cyber-physical systems and there are certain constraints (not too restrictive) to be able to apply our solution to any smart home installation. In the first place, the behavior of each device must be susceptible of being encapsulated in a black-box component which exposes their required and provided functionality by means of interfaces. Second, we need a repository containing the most common devices or, otherwise, developers must implement each new device as a Polymer component. Finally, for each specific network or communication protocol, we need to implement a gateway that allows us to interact with the connected devices.As future work, we intend to develop and provide a set of tools supporting the design and development of interconnected CPSs that automatically generate  the implementation of the components according to our approach. This generation can be addressed by applying techniques of model-to-model (M2M) and model-to-text (M2T) transformations . With th