Objective Some genome-wide significant SLE risk loci associate with SLE development only while other associate with other diseases, such as type 1 diabetes (T1DM) and rheumatoid arthritis (RA). Our objective: to investigate what clinical phenotype associate with high polygenic scores (PRSs) for SLE-specific and multitrait-associated SLE loci. Methods Patients with SLE (ACR-97 or SLICC-12, n=1498) and healthy controls (n=1947) were genotyped using Illumina's Global Screening Array. SLE-associated single nucleotide variants (SNVs) (European ancestry) at GWAS significance (p<5×10–8) were identified through the GWAS catalog. After filtering 112 SNVs were identified. SNVs were considered multitrait if associated with ≥1 additional disease. Two PRSs were constructed; one including SLE specific SNVs (n=79) and one including multitrait SNVs (n=33). Groups were compared using logistic regression, adjusting for age and sex. 50% of patients with the highest SLE-specific PRS were selected and from them the 50% with the lowest multitrait PRS were selected. This group (highSLE-lowMultitrait, 25% of total) was then compared with the other patients (75% of total). The same method was used for the highMultitrait-lowSLE group. Results Both PRSs were higher in patients in comparison with healthy controls, p<2×10–6. Besides SLE, the most common diseases associated with the multitrait SNVs were RA (SNV=10), T1DM (SNV=8), multiple sclerosis and ulcerative colitis (SNV=6). The highSLE-lowMultitrait group had higher prevalence of malar rash (OR 1.28(1.00–1.66), p=0.04), neurologic manifestations (OR 1.44(1.10–2.08), p=0.048), thrombocytopenia (OR 1.47(1.06–2.04), p=0.022), anti-Sm antibodies (OR 1.80(1.12–2.80), p=0.009), low complement (OR 1.70(1.25–2.30), p <0.001) and lower prevalence of hemolytic anemia (OR 0.55(0.32–0.97), p=0.038) compared with the other group. The highMultitrait-lowSLE group had higher prevalence of anti-SSA (OR 1.49 (1.14–1.94), p= 0.003) and anti-SSB antibodies (OR 1.79 (1.34–2.39), p <0.001) and lower prevalence of discoid rash (OR 0.72(0.52–1.0), p=0.038) compared with the other group. Conclusions Comparative analysis of multitrait and SLE-specific SNVs shed light on SLE heterogeneity. Leveraging data for shared genetic associations can be important for determining the genetic background influencing SLE subphenotypes, but also common disease manifestations among autoimmune diseases. Acknowledgements Supported by the Swedish Society for Medical Research (S20–0127), the Swedish Rheumatism Association, King Gustaf V's 80-Year Foundation, the Gustafsson Foundation.

Objective Genetic contribution is crucial for SLE pathogenesis, but linking risk variants to specific mechanisms in SLE is challenging. We utilize UK Biobank data and a large well defined SLE cohort to investigate associations between SLE risk loci, blood biomarkers and clinical phenotype. Our objective: to study potential combinatorial effects of multiple biomarker associated SLE SNVs in clinical SLE data. Methods We extracted SLE associated SNVs from published European ancestry GWAS data (with p<5×10–8) and selected 112 SNVs. Associations (p<5×10–8) between these SNVs and blood biomarkers in the UK Biobank were investigated and a 17 SNV cluster associated with 38 biomarkers was identified. Patients with SLE (ACR-97 or SLICC-12, European decent, n=1498) were genotyped using Illumina's Global Screening Array and clinical data was collected. A weighted polygenic risk score (PRS) including the 17 SNVs identified in the cluster analysis was calculated for each patient and clinical manifestations (ACR-97 criteria, antibodies) of patients with a high (50%) and low (50%) PRS were compared by logistic regression with age and sex covariates. Results We identified a cluster of 17 SLE risk SNVs associated with multiple blood biomarkers in the general population. The biomarkers associated with the highest number of these SNVs include eosinophil percentage (SNV=16), aspartate aminotransferase (SNV=12), apolipoprotein A (SNV=12) and cystatin C (SNV=11). Patients with high PRS had higher total ACR -97 SLE criteria score (OR 1.35 (1.06–1.69), p=0.014) and higher prevalence of anti-SSA (OR 2.71 (2.16–3.40), p<0.001) and anti-SSB antibodies OR 4.58 (3.39–6.61) p<0.001) compared with other patients. Further, high PRS was associated with lower prevalence of thrombocytopenia (OR 0.63 (0.48–0.84), p=0.001) and anti-Sm antibodies (OR 0.59 (0.39–0.89), p=0.011). Conclusions We identified a cluster of SLE risk variants associated with multiple blood biomarkers in the UK Biobank. A PRS including these loci associate with an unspecific SLE phenotype including increased number of classification criteria and presence of SSA/SSB antibodies. Further studies are needed to clarify the role of these potential pleiotropic SLE risk loci in lupus pathogenesis. Acknowledgements Supported by the Swedish Society for Medical Research(S20–0127), the Swedish Rheumatism Association, King Gustaf V's 80-Year Foundation, the Gustafsson Foundation.

Background Rheumatoid arthritis (RA) is associated with aberrant epigenomic control which obstructs the proper function of CD4 T cells. Bivalent chromatin regions (BvCR), containing histone H3 tail trimethylation at lysine 4 (H3K4me3) and lysine 27 (H3K27me3), act as a major organizer of the 3D nuclear environment required for efficient T cell development. Survivin has gained importance in RA pathogenesis. Survivin is shown to interact with chromatin genome-wide and regulate gene transcription in the IFNg producing CD4 T cells [1]. Objectives This study investigates survivin cooperation with nucleosome in BvCR and functional effect of this cooperation on CD4 cell phenotype. Methods BvCR were identified in CD4 cells by annotation of H3K4me3, H3K27me3 and H3K27ac binding through chromatin immunoprecipitation and sequencing (ChIPseq). Protein binding was quantified through peak score. An overlap of the H3 peaks and Survivin ChIPseq (12 individual CD4 cultures) by at least one bp was identified through R package ChIPPeakAnno. Changes in H3 peaks in CD4 cells treated with a survivin inhibitor YM155 were assessed. Tag normalization was applied to enable comparison between different ChIPseq. Tag prevalence within the BvCR defined the dominant H3 group. Changeable BvCR were defined by alteration in the dominant-H3 group after YM155 treatment. TF ChIPseq colocalization analysis was performed through ReMap2022 database. To analyse effect of BvCR changeability on transcriptome, we performed RNAseq of YM155-treated CD4 cells (n=4). Overlap of BvCR with regulatory elements (RE) was done through GeneHancer database. TF enrichment analysis was performed through GSEA (Broad Institute). Results Integration of H3K4me3, H3K27me3 and H3K27ac ChIP-seq identified 6199 BvCR, 66% of those contained survivin peaks. Fluorescence imaging of effector T cells validated nuclear colocalization of survivin with histone proteins. Of those 6199 BvCR, 43.8% were dominated by H3K4me3, which had also the highest survivin peak scores. Complexes of histone modifiers COMPASS, responsible for H3K4 methylation, and SWI/SNF, responsible for counteracting PRC2-guided H3K27me3, colocalized with BvCR. YM155-treatment significantly increased deposition of both H3K4me3 and H3K27me3. Changeable BvCR frequently acquired a K4me3-dominant status after YM155 treatment. This indicates that survivin contributes to regulation of methylation of lysines in H3 tail within BvCR. TF enrichment analysis of genes connected to the BvCR revealed the role of histone demethylases KDM7A (FDR=1.03e-32), PHF2 (FDR=3.47e-19), KDM5D (FDR=1.51e-15) in their transcription. Strongest overall enrichment was identified in H3K4me3-dominant BvCR colocalized with survivin. Integration of BvCR with CD4 RNA-seq revealed 2469 protein-coding genes connected through RE to H3K4me3-dominant BvCR, which sustained transcriptional activity and 346 of those were differentially expressed (DEG, nom p<0.05) in YM155-treated cells. DEG transcriptionally dependent on the TF families of histone modifiers built a strong SWI/SNF-dependent interaction network acting in biological processes of immune system regulation (FDR=1.07e-6. FOXP1, KLF3, FYB1, BCL2), DNA repair (FDR=5.57e-6. MSH6, MGMT, MCM8, UPF1), and RNA polymerase transcription (FDR=1.22e-8. TCF3, ARID5A, RARA). CD4 cell transcriptomics of randomly selected RA patients demonstrated that a) DEG controlled by the H3K4me3-dominant BvCR were upregulated in survivin-high CD4 cells with proinflammatory Th1 phenotype b) DEG had altered expression in CD4 cells of patients treated with JAK-inhibitors. Conclusion This study demonstrates that survivin contributes to regulation of lysine methylation in H3 tail within BvCR, which coordinates activity of the SWI/SNF complex in chromatin remodelling and transcription. We demonstrate that survivin inhibition affects this coordinated activity, and thereby impinge on CD4 activation in RA. Reference [1]Erlandsson et al. iScience 2022;25:105526. Acknowledgements: NIL. Disclosure of Interests None Declared.

This study investigates the role of survivin in epigenetic control of gene transcription through interaction with the polycomb repressive complex 2 (PRC2). PRC2 is responsible for silencing gene expression by trimethylating lysine 27 on histone 3. We observed differential expression of PRC2 subunits in CD4+ T cells with varying levels of survivin expression, and ChIP-seq results indicated that survivin colocalizes with PRC2 along DNA. Inhibition of survivin resulted in a significant increase in H3K27 trimethylation, implying that survivin prevents PRC2 from functioning. Peptide microarray showed that survivin interacts with peptides from PRC2 subunits, and machine learning revealed that amino acid composition contains relevant information for predicting survivin interaction. NMR and BLI experiments supported the interaction of survivin with PRC2 subunit EZH2. Finally, protein-protein docking revealed that the survivin-EZH2 interaction interface overlaps with catalytic residues of EZH2, potentially inhibiting its H3K27 methylation activity. These findings suggest that survivin inhibits PRC2 function.

Proper physiological functioning of any cell type requires ordered chromatin organization. In this context, cohesin complex performs important functions preventing premature separation of sister chromatids after DNA replication. In partnership with CCCTC-binding factor, it ensures insulator activity to organize enhancers and promoters within regulatory chromatin. Homozygous mutations and dysfunction of individual cohesin proteins are embryonically lethal in humans and mice, which limits in vivo research work to embryonic stem cells and progenitors. Conditional alleles of cohesin complex proteins have been generated to investigate their functional roles in greater detail at later developmental stages. Thus, genome regulation enabled by action of cohesin proteins is potentially crucial in lineage cell development, including immune homeostasis. In this review, we provide current knowledge on the role of cohesin complex in leukocyte maturation and adaptive immunity. Conditional knockout and shRNA-mediated inhibition of individual cohesin proteins in mice demonstrated their importance in haematopoiesis, adipogenesis and inflammation. Notably, these effects occur rather through changes in transcriptional gene regulation than through expected cell cycle defects. This positions cohesin at the crossroad of immune pathways including NF-kB, IL-6, and IFNγ signaling. Cohesin proteins emerged as vital regulators at early developmental stages of thymocytes and B cells and after antigen challenge. Human genome-wide association studies are remarkably concordant with these findings and present associations between cohesin and rheumatoid arthritis, multiple sclerosis and HLA-B27 related chronic inflammatory conditions. Furthermore, bioinformatic prediction based on protein-protein interactions reveal a tight connection between the cohesin complex and immune relevant processes supporting the notion that cohesin will unearth new clues in regulation of autoimmunity.

In this study, we explore the role of nuclear survivin in maintaining the effector phenotype of IFNγ-producing T cells acting through the transcriptional control of glucose utilization. High expression of survivin in CD4+T cells was associated with IFNγ-dependent phenotype and anaerobic glycolysis. Transcriptome of CD4+ cells and sequencing of survivin-bound chromatin showed that nuclear survivin had a genome-wide and motif-specific binding to regulatory regions of the genes controlling cell metabolism. Survivin coprecipitates with transcription factors IRF1 and SMAD3, which repressed the transcription of the metabolic check-point enzyme phosphofructokinase 2 gene PFKFB3 and promoted anaerobic glycolysis. Combining transcriptome analyses of CD4+ cells and functional studies in glucose metabolism, we demonstrated that the inhibition of survivin reverted PFKFB3 production, inhibited glucose uptake, and reduces interferon effects in CD4+ cells. These results present a survivin-dependent mechanism in coordinating the metabolic adaptation of CD4+T cells and propose an attractive strategy to counteract IFNγ-dependent inflammation in autoimmunity.

Background Bivalent chromatin (BvCR) is characterized by the presence of simultaneous active and repressive modifications on histone H3 proteins. Influencing expression of the genes, BvCR determine cell fate and direct differentiation and lineage commitment in primary T cells and contribute to autoimmunity. Survivin is highly expressed during cell division and in effector Th1 cells contributing to aggravation of autoimmune inflammation. Survivin can physically bind to DNA, specifically to Threonine-3 of histone H3 (1). Thus, functional, and mechanistic data point to a potential chromatin regulatory role for survivin, potentially acting in combination with histone epigenetic modifications (EMs). Objectives The goal of our study is to establish the colocalization of survivin with BvCRs and to deduce functional effects of this collaboration on chromatin organization and gene expression. Methods Chromatin from CD4+ T cells of 14 female subjects was immunoprecipitated with survivin antibodies and histone H3K27ac, H3K27me3, H3K4me3 antibodies, and coupled with DNA sequencing (ChIPseq, Hiseq2000, Illumina). BvCR were identified as exact overlaps of the three histone EM peaks and the overlapping regions were searched for co-localization with survivin using the ‘ChIPPeakAnno’ Bioconductor package. Tag counts K27me3>K27ac were defined as inactive/poised BvCR, while tag count K27me310e-5 were selected and scanned through the HOCOMOCO database to identify consensus transcription factor (TF) motifs. TFs co-localized with the BvCD were identified through ReMap database. To identify survivin sensitive genes, CD4 + T cells were treated with survivin inhibitor YM155 and a list of reproducible DEG (log2FC>[0.4], >1 experiment) was mapped and analysed for clustering with BvCR. Results Co-localization of survivin ChIP peaks with individual H3-peaks was significantly less frequent compared to overlap with all three (a3)-H3 BvCR (7.1 vs 29.8%, p=8.9e-13). Overlap of a3-H3 peaks not containing survivin was less frequent (34%) compared to those which contained survivin (66%). Notably, survivin peak size was 5.5-fold higher when colocalized with a3-H3 peaks, compared to no, or any single H3 (p<2.2e-16). In contrast, no size difference for any of the H3 EM peaks was found. Further analysis of two non-redundant groups of BvCR that contain (survivin-a3H3, n=4085), and not containing survivin (a3H3noSurv, n = 2131) demonstrated that survivin was mostly associated with inactive BvCR (OR1.29, p=6.6e-6), while no such specificity was found for BvCR with no survivin. Additionally, survivin containing BvCR contained abundant binding sites matching known consensus TF motifs. No sequence-specific motifs were identified in BvCR with no survivin. Comparison of results obtained through HOCOMOCO and ReMap databases resulted in a list of 68 unique TFs. Many of those are key regulators of adaptive immune responses, cellular metabolism, and pluripotency. Differentially expressed genes mapped to BvCR demonstrated enrichment for cellular hormone metabolic processes, regeneration and DNA biosynthesis. Conclusion This study provides experimental evidence that survivin defines binding specificity in bivalent chromatin regions being associated with regulation of cellular metabolism and renewal of CD4 + T cells that are functionally important to resist autoimmunity. References [1]Kelly AE, Ghenoiu C, Xue JZ, Zierhut C, Kimura H, Funabiki H. Survivin reads phosphorylated histone H3 threonine 3 to activate the mitotic kinase Aurora B Science. 2010 Oct 8; 330(6001): 235–239. Disclosure of Interests None declared

IFNG , TBX21 , Eomes , IL2RA , IL2RB , IL12RB2 , TNF , IL18RAP (all, adj. p < 0.05). Conclusion: This study shows that accumulation of Rho-proteins in CD4 + cells results in pro-inflammatory IFN-γ dependent phenotype in mice and human RA. Accumulation of RhoA, Rac1 and Cdc42 proteins trigger the migration of CD4 + cells into joint draining LN and facilitates arthritis. Inhibiting M ø /T cell contact in GLC mice did not suffice to prevent migration of Rho-protein expressing cells

Breast cancer (BC) histological and molecular classifications significantly improved the treatment strategy and prognosis. Inhibitor of apoptosis BIRC5/survivin is often overexpressed in cancers, however, indications of its importance in BC are inconsistent. We integrate BIRC5 protein and mRNA measures with clinical associates and long-term outcome in three independent cohorts Protein levels of BIRC5 were measured in primary lysates of 845 patients of the West Swedish BC cohort (VGR-BC) and linked to 5- and 27-years survival. The results were externally validated in transcriptomic data from METABRIC and SCAN-B cohorts. Survival analysis showed that high levels of BIRC5 were consistently associated with a poor probability of 5-year overall survival. High BIRC5 in VGR-BC contributed negatively to the disease-specific survival at 5 and 27 years. Subsets with different status by ER (estrogen receptor) expression and presence of nodal metastasis supported independent association of high BIRC5 with poor prognosis in all cohorts. In METABRIC and SCAN-B cohorts, high levels of BIRC5 mRNA were associated with the basal-like and luminal B molecular BC subtypes and with increasing histologic grade. BIRC5 is a sensitive survival marker that acts independent of ER and nodal status, and its levels need to be considered when making treatment decisions.

Abstract Upon activation, CD4+ T cells adapt metabolically to fulfill their effector function in autoimmunity. Here we show that nuclear survivin is essential for transcriptional regulation of glucose utilization. We found that the glycolytic switch in interferon (IFN) g–producing CD4+ cells is dependent on a complex of survivin with interferon regulatory factor 1 (IRF1), and Smad3 and was reversed by survivin inhibition. Transcriptome analysis of CD4+ cells and sequencing of survivin-bound chromatin identified a hub of metabolism regulating genes whose transcription depended on survivin. Direct binding of survivin to IRF1 and SMAD3 promoted IRF1-mediated transcription, repressed SMAD3 activity, and lowered PFKFB3 production. Inhibiting survivin upregulated PFKFB3, restored glycolysis, and reduced glucose uptake, improving control over IFNg-dependent T-cell functions. Thus, IRF1-survivin-SMAD3 interactions are important for metabolic adaptation of CD4+ cells and provide an attractive strategy to counteract IFNg-dependent inflammation.

Glioblastoma is the most aggressive type of brain tumors resistant to a number of antitumor drugs. The problem of therapy and drug treatment course is complicated by extremely high heterogeneity in the benign cell populations, the random arrangement of tumor cells, and polymorphism of their nuclei. The pathogenesis of gliomas needs to be studied using modern cellular technologies, genome- and transcriptome-wide technologies of high-throughput sequencing, analysis of gene expression on microarrays, and methods of modern bioinformatics to find new therapy targets. Functional annotation of genes related to the disease could be retrieved based on genetic databases and cross-validated by integrating complementary experimental data. Gene network reconstruction for a set of genes (proteins) proved to be effective approach to study mechanisms underlying disease progression. We used online bioinformatics tools for annotation of gene list for glioma, reconstruction of gene network and comparative analysis of gene ontology categories. The available tools and the databases for glioblastoma gene analysis are discussed together with the recent progress in this field.

Background: The insulin-like growth factor 1 receptor (IGF1R) signalling mediates numerous developmental processes acting through downstream adaptor molecules IRS1/2, which activate Akt and inhibit the family of forkhead box class O (FoxO). Inhibition of IGF1R signalling alleviates rheumatoid arthritis (RA) (Erlandsson et al., 2017), however, the role of IGF1R signalling in the regulation of immune function is poorly understood. Objectives: To investigate the link between IGF1R signalling and antigen presentation in experimental arthritis. Methods: Arthritis was induced by immunising Balb/c mice with methylated bovine serum albumin (mBSA, n=18) and DBA/1 mice with type II collagen (CII, n=18). The mice were treated with a synthetic IGF1R inhibitor NT157 or with short hairpin RNA targeting IGF1R (shIGF1R) from the day prior to immunisation. Controls were treated with cyclodextrine vehicle/ non-targeting (nt)RNA, respectively. Flow cytometry was used for spleen cell phenotype. Antibody levels were measured by ELISA. Immunohistochemistry (IHC) of spleen was performed for assessment of marginal zone (MZ) and location of pS 612 IRS1+ and pS 256 FoxO1+ cells. IHC images were acquired by fluorescent confocal microscopy, and analysed using ZEN2009 and Cell Profiler soft ware. Results: The inhibition of IGF1R resulted in an 80% increase in MZ area in NT157-treated mice compared to controls (p=0.0001). This was supported by a significant increase of CD21+ (p=0.034) and CD23+ cell populations (p=0.00059), both among the CD19+ B cells and antigen-presenting MHCII+CD19- cells, implying that IGF1R expression regulates the populations of MZ and follicular cells. Additionally, there was a strong positive correlation between the decrease of IGF1R+ and ICOSL+ population on CD21+ cells (r=0.70, p=0.0071), which retained them in the MZ and prolonged communication with macrophages. Insufficient feedback from ICOSL- B cells limited expression of CXCR5 on CD4 cells. The IHC analysis displayed that, IGF1R inhibition led to abundance of inactivate pS 612 IRS1+ and pS 256 FoxO1+ cells within the MZ, compared with controls (p=0.0002). Alongside the increase of IgM+ B cell population (p=0.0022), we observed significant increase in number of antigen-presenting F4/80+ cells (p=0.043) and MARCO expression (p=0.043) after IGF1R intervention. Finally, the NT157- treated mice displayed a significant pleiotropic increase in IgM autoantibody production, with anti-CCP IgM (p=0.027), RF-IgM (p=0.0085), anti-DNA IgM (p=0.066) and in total IgM (p=0.027) levels, which correlated positively with pS 256 FoxO1 + cells (r=0.51, p=0.03). Levels of IgG were not changed. Conclusion: We show that IGF1R signalling is important for immune cell communication after antigen challenge. IGF1R controls ICOSL dependent trafficking of B cells through the MZ and facilitates interaction with T cells. Retention of B cells in the MZ tips the balance from T cell to macrophage-dependent processes, which permits the formation of autoantibody producing B cells. References: [1]Erlandsson, M., et.al., 2017. IGF-1R signalling contributes to IL-6 production and T cell dependent inflammation in rheumatoid arthritis. Biochimica et Biophysica Acta (BBA) - Molecular Basis of Disease , 1863(9), pp.2158-2170. Disclosure of Interests: None declared

Background: Survivin, coded by BIRC5 gene, is a multitasking protein essential for cell renewal and homeostasis. In autoimmune conditions as rheumatoid and psoriasis arthritis, survivin was associated with inflammation severity and joint damage. Importantly, inhibition of survivin alleviated experimental arthritis in mice. We have recently shown survivin to be essential for T cell differentiation and micro-RNA processing. The known anti-apoptotic and proliferation facilitating functions of survivin does not explain the nuclear localization of survivin in interphase. Objectives: We aimed to uncover nuclear functions of BIRC5/survivin in CD4 cell of RA patients and healthy. Methods: CD4 T cells were isolated from the peripheral blood using positive selection on magnetic beads (EasySep) and activated for 48h with ConA+LPS. Chromatin immunoprecipitation (ChIP) with polyclonal anti-survivin antibodies was done in four independent samples of healthy donors (n=5), healthy smokers (n=3), rheumatoid arthritis (n=3) and breast cancer (n=2). Pooled libraries were constructed for each group and ChIPseq was carried out (Illumina). For comparative RNAseq analysis, activated CD4 T cells were incubated with or without survivin inhibitor (YM155) for 24h. State-of-the-art bioinformatics pipelines were applied for NGS data and the survivin-binding peaks were used for comparison with genes, chromatin state annotation and functional gene- and regulatory regions-based functional analysis. Co-localization of peaks in the whole genome and in vicinity of the differentially expressed genes (DEG) was done using ReMap integrated ChIPseq datasets for all human cells and tissues. Results: We identified 13 thousands non-overlapping survivin ChIP-peaks (>3000 peaks were present in at least 3 samples). Survivin-bound regions were enriched near the genes and promoters (p=e-30 and p=e-8), which implied that survivin role in transcription could be mediated by known transcription factors. Thus, we analyzed survivin peaks vs binding regions of 1135 transcription regulators (TR) available in ReMap. Potential partner proteins of survivin were selected based on the enrichment of the overlapping peaks in the whole genome and in CD4-active regulatory areas. Both, strict overlaps and location within 10 and 100kb survivin peak vicinity were analyzed. This approach allowed us to select >150 TRs enriched in all tests. The enriched TRs were involved in immunity and RA-relevant pathways including cytokine response and production, JAK-STAT signaling, etc. Among the TRs co-localized with survivin were CHD8, MAX, EP300, BRD2, CTCF and RAD21, all responsible for chromatin architecture. Several TRs were massively enriched in the vicinity of DEGs after survivin depletion including MAX, AR, CTCF, MYC and IRF1. Search for TR binding motifs in survivin peaks supported over-representation of binding sites for IRFs (p=e-5) and several proteins of the bZIP-family (p=e-5). Conclusion: Analysis of the survivin bound DNA in CD4 cells demonstrated the nonrandom distribution with specific enrichment within the regulatory elements of the genes and co-localizeation with protein partners to regulate their transcription. Disclosure of Interests: None declared

Interferon-gamma (IFNγ) producing T cells develop metabolic adaptation required for their effector functions in tumour biology, autoimmunity and antiviral defence. Using sorted CD4 + cells we demonstrated that glycolytic switch and high glucose uptake in IFNγ-producing cells was associated with survivin expression. Inhibition of survivin restored glycolysis by upregulating the transcription of phosphofructokinase PFKFB3 and reducing glucose uptake. Integration of the whole-genome sequencing of the chromatin immunoprecipitated with survivin with transcription changes in CD4 + cells after survivin inhibition revealed co-localization of survivin, IRF1 and SMAD3 in the regulatory elements paired to the differentially expressed genes. Western blot demonstrated direct binding of survivin to IRF1 and SMAD3. Functionally, inhibition of survivin repressed IFNγ signalling and activated SMAD3-dependent protein remodelling, which resulted in the effector-to-memory transition of CD4 + cells. These findings demonstrate the key role of survivin in IFNγ-dependent metabolic adaptation and identify survivin inhibition as an attractive strategy to counteract these effects.

Background: Survivin is an integral part of the Chromosomal Passenger Complex (CPC) which plays a vital role in mitosis. Experiments have demonstrated that survivin can physically bind to DNA. Crystallographic studies show that survivin binds to Threonine-3 of histone H3. In patients with autoimmune diseases, increased survivin expression contributes to an aggravated disease phenotype. Thus, functional, and mechanistic data point to a potential chromatin regulatory role for survivin, possibly in combination with the established gene regulatory function carried out by histone epigenetic modifications (EM). Objectives: The objective of the study was to analyse the co-localization of chromatin bound survivin with three histone H3 epigenetic modifications – acetylated lysine 27 (K27ac) and trimethylated lysine 4 (K4me3) and lysine-27 (K27me3). The second objective was to analyse if survivin-bound DNA sequences overlapped with sequences in the vicinity of 106 GWAS SNPs that are associated with a risk of developing rheumatoid arthritis (RA). Methods: Chromatin from CD4 T cells of 14 female subjects was immunoprecipitated with survivin antibodies and each of the histone H3 antibodies, and coupled with sequencing (ChIPseq, Hiseq2000, Illumina). After mapping the annotations of sequenced regions to the human reference genome hg38, enriched peaks were identified through Homer software. The identified survivin ChIP peaks were analysed for colocalization with peaks of the three histone H3 EMs and with RA risk loci, using the Bioconductor package ‘ChIPPeakAnno’ through RStudio. Results: Among the total of ~13,000 individual survivin ChIP-peaks, 33% colocalized with histone H3 EM peaks. The overlapping peaks show a linear increase in average peak size compared with the peaks showing no colocalization with any H3 EM peak. A maximum of 5.5-fold increase in average peak size was observed when survivin bound peaks overlap with peaks of all three H3 EMs. A major proportion (86%) of top RA risk SNPs was associated with either binding of survivin or H3 EMs. In this subset, 63% of RA risk SNPs were found within an area of 100 kilobases from survivin ChIP-peaks, with preferential enrichment of high-scoring peaks when survivin colocalizes with all 3 H3 EMs. Survivin was bound to risk SNPs annotated to, among others, the major immunological genes CD83, IRF4, CD28, ICOS and IL2RA Conclusion: This study presents experimental evidence that survivin binding to DNA preferentially occurred in regions with high density of histone EMs. The increased aggregation of survivin around histone H3 EMs point to its potential regulatory function in gene transcription. Since regions around RA risk SNPs overlap with survivin peaks, survivin’s nuclear function could have immunologically important effects in mechanisms of autoimmune diseases. Disclosure of Interests: None declared

Interferon-gamma (IFNg) producing effector T cells play the leading role in triggering and perpetuation of inflammation in rheumatoid arthritis. Inflammation leads to metabolic reprogramming of T cells and high energy consumption supporting proliferation and IFNg production. Being a part of chromosomal passenger complex, oncoprotein survivin is essential for cell proliferation. It has also been identified as a marker of severe therapy-resistant rheumatoid arthritis. Thus, we aimed to explore the association between survivin and IFNg producing phenotype of CD4 T cells.We study if survivin mediates the glucose dependent mechanism of IFNg production in CD4 T cells.CD4 cells were sorted from the peripheral blood of RA patients and healthy controls, activated with aCD3, cultured in presence of survivin inhibitor YM155 and subjected to RNA sequencing (Illumina, Life Science). IFNg levels in supernatants were measured by ELISA. To study glucose uptake in presence of YM155, CD4 cells were treated with IFNg+aCD3 overnight followed by 2NBD-glucose challenge for 30 min. Uptake of fluorescent 2NBD-glucose probe was measured by flow cytometry. Statistical analysis of RNAseq was performed in R-studio using the Bioconductor package DESeq2.Comparison of the whole-genome transcription profile of CD4 cells different by levels of BIRC5, coding for survivin, demonstrated that the BIRC5hi group expressed significantly higher levels of IFNg (mRNA, p=10-26 and protein, p=10-4). Also, BIRC5hi CD4 cells had higher expression of glucose transporter GLUT1 (SLC2A1, p=0.0064) and of glycolytic enzymes glucose-6-phosphate dehydrogenase (G6PD, p=10-6), pyruvate kinase (PFKP, p=10-6), and lactate dehydrogenase (LDHA, p=10-14). On the contrary, expression of the key regulator of glycolysis 6-phosphofructo-2-kinase (PFKFB3) was significantly lower in the BIRC5hi group (p=4.4x10-5). Notably, expression of glycolytic enzymes G6PD and PFKFB3 correlated strongly to IFNg (r=0.880 and -0.698, respectively), TBX21 (r=0.811 and -0.698) and perforin (r=0.781 and -0.698). To demonstrate functional relevance of the connection between BIRC5 and glucose metabolism, survivin was inhibited in CD4 cell cultures. Survivin inhibition resulted in significant increase of PFKFB3 (p=7x10-6) and LDHA (p=0.0089), leading to inhibition of phosphoglycerate mutase PGAM1 and ATF citrate lyase ACLY (p=0.021 and p=0.0074, respectively), which dignify the restoration of aerobic glycolysis. Importantly, inhibition of survivin decreased 2NBD-glucose uptake by CD4 cells (p=0.031) and reduced expression of GLUT1 (p=0.034). These changes in glucose metabolism were followed by decreased IFNg production in supernatants (p=0.037).The study demonstrates a strong connection between IFNg production and glucose metabolism in CD4 cells. Survivin emerges as an important regulator of glycolysis acting through expression of glycolytic enzymes and glucose transport.None declared.