Differential gene expression profiles may differentiate responder and nonresponder patients with rheumatoid arthritis for methotrexate (MTX) monotherapy and MTX plus tumor necrosis factor inhibitor combined therapy

Novel Therapeutic Mechanism of Adipose-Derived Mesenchymal Stem Cells in Osteoarthritis via Upregulation of BTG2

Background

Osteoarthritis (OA) is a debilitating and degenerative joint disease, which is characterized by progressive destruction of articular cartilage. Mesenchymal stem cells (MSCs) have been implicated in the treatment of OA. However, the function of adipose-derived MSCs (AD-MSCs) in OA and its underlying mechanism remain obscure.

Aim

We aimed to explore the function of AD-MSCs in OA and investigate its potential regulatory mechanism.

Methods

A guinea pig model of OA was constructed. AD-MSCs injected into the articular cavity of OA guinea pigs were viewed by in vivo bioluminescence imaging. The effect of AD-MSCs on the gonarthritis of OA guinea pigs was evaluated through both macroscopic and microscopic detections. The detailed molecular mechanism was predicted by GEO databases and bioinformatics tools and then verified via mechanism experiments, including ChIP assay, DNA pulldown assay, and luciferase reporter assay.

Results

AD-MSCs had a significant positive therapeutic effect on the gonarthritis of the OA model, and the overall effects of it was better than that of sodium hyaluronate (SH). B-cell translocation gene 2 (BTG2) was significantly downregulated in the articular cartilage of the OA guinea pigs. Furthermore, BTG2 was positively regulated by Krüppel-like factor 4 (KLF4) in AD-MSCs at the transcriptional level. AD-MSCs performed an effect on KLF4 expression at the transcriptional levels.

Conclusion

AD-MSCs suppresses OA progression through KLF4-induced transcriptional activation of BTG2. Our findings revealed an AD-MSCs-dominated therapeutic method for OA.

Gene Ontology Analysis Highlights Biological Processes Influencing Non-Response to Anti-TNF Therapy in Rheumatoid Arthritis

Anti-TNF therapy has significantly improved disease control in rheumatoid arthritis, but a fraction of rheumatoid arthritis patients do not respond to anti-TNF therapy or lose response over time. Moreover, the mechanisms underlying non-response to anti-TNF therapy remain largely unknown. To date, many single biomarkers of response to anti-TNF therapy have been published but they have not yet been analyzed as a system of interacting nodes. The aim of our study is to systematically elucidate the biological processes underlying non-response to anti-TNF therapy in rheumatoid arthritis using the gene ontologies of previously published predictive biomarkers. Gene networks were constructed based on published biomarkers and then enriched gene ontology terms were elucidated in subgroups using gene ontology software tools. Our results highlight the novel role of proteasome-mediated protein catabolic processes (p = 2.91 × 10⁻¹⁵) and plasma lipoproteins (p = 4.55 × 10⁻¹¹) in anti-TNF therapy response. The results of our gene ontology analysis help elucidate the biological processes underlying non-response to anti-TNF therapy in rheumatoid arthritis and encourage further study of the highlighted processes.

TNIP1 Inhibits Proliferation And Promotes Apoptosis In Clear Cell Renal Carcinoma Through Targeting C/Ebpβ

Background/Purpose

TNF-α-induced protein 3-interacting protein 1 (TNIP1) is active in various cancers, but its expression and function in renal cell carcinoma (RCC) have not been described. This study investigated the role of TNIP1 in clear cell renal cell carcinomas (ccRCC), which accounts for 75–80% of RCC and has a poor prognosis.

Methods

The expression of TNIP1 in human ccRCC tissues and cells was detected by real-time quantitative reverse transcription–polymerase chain reaction (qRT-PCR), Western blot (WB), and immunohistochemical (IHC) staining. Cell proliferation was assayed by a cell counting kit (CCK)-8 assay; cell cycle analysis and apoptosis assay were done by flow cytometry.

Results

TNIP1 is downregulated in both ccRCC human tissues and cells. Besides, TNIP1 downregulation promoted cell proliferation with more cell cycle entry, and inhibited apoptosis. TNIP1 downregulation was associated with increased of expression of the Bcl-2 anti-apoptosis gene and decreased expression of the Bax apoptosis-promoting gene and cleaved-caspase-3 by negatively regulating C/EBPβ expression.

Conclusion

TNIP1 acted as a tumor-inhibitor in ccRCC by targeting C/EBPβ. The results warrant study of TNIP1 as a potential diagnostic marker and therapeutic target of ccRCC.

Increased baseline RUNX2, caspase 3 and p21 gene expressions in the peripheral blood of disease-modifying anti-rheumatic drug-naïve rheumatoid arthritis patients are associated with improved clinical response to methotrexate therapy

OBJECTIVE

To investigate the potential of the baseline gene expression in the whole blood of disease-modifying anti-rheumatic drug-naïve rheumatoid arthritis (RA) patients for predicting the response to methotrexate (MTX) treatment.

METHODS

Twenty-six control subjects and 40 RA patients were examined. Clinical, immunological and radiographic parameters were assessed before and after 24 months of follow-up. The gene expressions in the whole blood were measured using real-time reverse transcription polymerase chain reaction. The protein concentrations in peripheral blood mononuclear cells were quantified using enzyme-linked immunosorbent assay. Receiver operating characteristic curve analyses were used to suggest thresholds that were associated with the prediction of the response.

RESULTS

Decreases in the disease activity at the end of the study were accompanied by significant increases in joint space narrowing score (JSN). Positive correlations between the expressions of the Unc-51-like kinase 1 (ULK1) and matrix metalloproteinase 9 (MMP-9) genes with the level of C-reactive protein and MMP-9 expression with Disease Activity Score of 28 joints (DAS28) and swollen joint count were noted at baseline. The baseline tumor necrosis factor (TNF)α gene expression was positively correlated with JSN at the end of the follow-up, whereas p21, caspase 3, and runt-related transcription factor (RUNX)2 were correlated with the ΔDAS28 values.

CONCLUSIONS

Our results suggest that the expressions of MMP-9 and ULK1 might be associated with disease activity. Increased baseline gene expressions of RUNX2, p21 and caspase 3 in the peripheral blood might predict better responses to MTX therapy.

Understanding Human Autoimmunity and Autoinflammation Through Transcriptomics

Transcriptomics, the high-throughput characterization of RNAs, has been instrumental in defining pathogenic signatures in human autoimmunity and autoinflammation. It enabled the identification of new therapeutic targets in IFN-, IL-1- and IL-17-mediated diseases. Applied to immunomonitoring, transcriptomics is starting to unravel diagnostic and prognostic signatures that stratify patients, track molecular changes associated with disease activity, define personalized treatment strategies, and generally inform clinical practice. Herein, we review the use of transcriptomics to define mechanistic, diagnostic, and predictive signatures in human autoimmunity and autoinflammation. We discuss some of the analytical approaches applied to extract biological knowledge from high-dimensional data sets. Finally, we touch upon emerging applications of transcriptomics to study eQTLs, B and T cell repertoire diversity, and isoform usage.

Gene Expression Analysis before and after Treatment with Adalimumab in Patients with Ankylosing Spondylitis Identifies Molecular Pathways Associated with Response to Therapy

The etiology of Ankylosing spondylitis (AS) is still unknown and the identification of the involved molecular pathogenetic pathways is a current challenge in the study of the disease. Adalimumab (ADA), an anti-tumor necrosis factor (TNF)-alpha agent, is used in the treatment of AS. We aimed at identifying pathogenetic pathways modified by ADA in patients with a good response to the treatment. Gene expression analysis of Peripheral Blood Cells (PBC) from six responders and four not responder patients was performed before and after treatment. Differentially expressed genes (DEGs) were submitted to functional enrichment analysis and network analysis, followed by modules selection. Most of the DEGs were involved in signaling pathways and in immune response. We identified three modules that were mostly impacted by ADA therapy and included genes involved in mitogen activated protein (MAP) kinase, wingless related integration site (Wnt), fibroblast growth factor (FGF) receptor, and Toll-like receptor (TCR) signaling. A separate analysis showed that a higher percentage of DEGs was modified by ADA in responders (44%) compared to non-responders (12%). Moreover, only in the responder group, TNF, Wnt, TLRs and type I interferon signaling were corrected by the treatment. We hypothesize that these pathways are strongly associated to AS pathogenesis and that they might be considered as possible targets of new drugs in the treatment of AS.

Transcriptional profiling of leukocytes from rheumatoid arthritis patients before and after anti-tumor necrosis factor therapy: A comparison of anti-nuclear antibody positive and negative subsets

Anti-nuclear antibodies (ANAs) may be induced in patients with rheumatoid arthritis (RA) receiving anti-tumor necrosis factor (TNF) therapy with TNF inhibitors (TNFi), etanercept, infliximab or adalimumab. In the present study, 11 patients who were TNFi drug naive were started on TNFi at a time of high disease activity. Of these, all cases were positive for rheumatoid factor and 9 cases tested were positive for anti-citrullinated peptide (anti-CCP) antibodies prior to TNFi treatment. Peripheral blood mononuclear cells (PBMCs) and serum were collected from all patients before and after TNFi therapy. Serum was assayed for ANAs over time. Total cellular RNA was extracted from PBMCs and assessed using Illumina arrays. Gene expression profiles were examined for alterations in key effector pathways. After 3 or more months on TNFi, 6 patients converted to ANA-positivity. Analysis of transcripts from patients with RA who converted to ANA-positivity after 3 months on TNFi identified complex gene expression profiles that reflected a reduction in cell adhesion, cell stress and lipid metabolism transcripts. In summary, unique transcriptional profiles in PBMCs from patients with RA were observed after TNFi therapy. This pilot study suggests that transcriptional profiling is a precise method of measuring the impact of TNFi therapies and reveals novel pathways that likely influence the immune response.

HtrA2 suppresses autoimmune arthritis and regulates activation of STAT3

Rheumatoid arthritis (RA) is an autoimmune disease that is related to the induction of T helper (Th)17 cells, which secrete interleukin-17, and activation of the signal transducer and activator of transcription (STAT) 3. The expression of high-temperature requirement protein A (HtrA) 2, a serine protease involved in apoptosis, was decreased in RA patients nonresponsive to drug treatment of RA. The aim of this study was to determine whether overexpression of HtrA2 has a therapeutic effect on RA. Th17 differentiation, osteoclastogenesis, and lymphocyte activation are increased in motor neuron degeneration (mnd)2 mice, which lack HtrA2 activity because of a missense mutation (Ser276Cys) in the protease domain of HtrA2. The inhibitor of HtrA2 also increased Th17 differentiation. On the other hand, HtrA2 induced cleavage of STAT3 and overexpression of HtrA2 attenuated CIA in a mouse model. HtrA2 overexpression inhibited plaque development as well as the differentiation of Th17 in ApoE^-/- mice after immunization with proteoglycans to induce a hyperlipidemia-based RA animal model. The therapeutic function of HtrA2 in inflammatory diseases is linked with Th17 development and the STAT3 pathway in splenocytes. These results suggest that HtrA2 participates in immunomodulatory activity where the upregulation of HtrA2 may shed light on therapeutic approaches to RA and hyperlipidemia.

Integration of known DNA, RNA and protein biomarkers provides prediction of anti-TNF response in rheumatoid arthritis: results from the COMBINE study

OBJECTIVE

In rheumatoid arthritis (RA) several recent efforts have sought to discover means of predicting which patients would benefit from treatment. However, results have been discrepant with few successful replications. Our objective was to build a biobank with DNA, RNA and protein measurements to test the claim that the current state-of-the-art precision medicine will benefit RA patients.

METHODS

We collected 451 blood samples from 61 healthy individuals and 185 RA patients initiating treatment, before treatment initiation and at a 3 month follow-up time. All samples were subjected to high-throughput RNA sequencing, DNA genotyping, extensive proteomics and flow cytometry measurements, as well as comprehensive clinical phenotyping. Literature review identified 2 proteins, 52 single-nucleotide polymorphisms (SNPs) and 72 gene-expression biomarkers that had previously been proposed as predictors of TNF inhibitor response (∆DAS28-CRP).

RESULTS

From these published TNFi biomarkers we found that 2 protein, 2 SNP and 8 mRNA biomarkers could be replicated in the 59 TNF initiating patients. Combining these replicated biomarkers into a single signature we found that we could explain 51% of the variation in ∆DAS28-CRP. This corresponds to a sensitivity of 0.73 and specificity of 0.78 for the prediction of three month ∆DAS28-CRP better than -1.2.

CONCLUSIONS

The COMBINE biobank is currently the largest collection of multi-omics data from RA patients with high potential for discovery and replication. Taking advantage of this we surveyed the current state-of-the-art of drug-response stratification in RA, and identified a small set of previously published biomarkers available in peripheral blood which predicts clinical response to TNF blockade in this independent cohort.

MeDiA: Mean Distance Association and Its Applications in Nonlinear Gene Set Analysis

Probabilistic association discovery aims at identifying the association between random vectors, regardless of number of variables involved or linear/nonlinear functional forms. Recently, applications in high-dimensional data have generated rising interest in probabilistic association discovery. We developed a framework based on functions on the observation graph, named MeDiA (Mean Distance Association). We generalize its property to a group of functions on the observation graph. The group of functions encapsulates major existing methods in association discovery, e.g. mutual information and Brownian Covariance, and can be expanded to more complicated forms. We conducted numerical comparison of the statistical power of related methods under multiple scenarios. We further demonstrated the application of MeDiA as a method of gene set analysis that captures a broader range of responses than traditional gene set analysis methods.

Modular analysis of peripheral blood gene expression in rheumatoid arthritis captures reproducible gene expression changes in tumor necrosis factor responders

OBJECTIVE

To establish whether the analysis of whole-blood gene expression is useful in predicting or monitoring response to anti-tumor necrosis factor (anti-TNF) therapy in patients with rheumatoid arthritis (RA).

METHODS

Whole-blood RNA (using a PAXgene system to stabilize whole-blood RNA in the collection tube) was obtained at baseline and at 14 weeks from 3 independent cohorts, consisting of a combined total of 240 RA patients who were beginning therapy with anti-TNF. We used an approach to gene expression analysis that is based on modular patterns of gene expression, or modules.

RESULTS

Good and moderate responders according to the European League Against Rheumatism criteria exhibited highly significant and consistent changes in multiple gene expression modules after 14 weeks of therapy, as demonstrated by hypergeometric analysis. Strikingly, nonresponders exhibited very little change in any modules, despite exposure to TNF blockade. These patterns of change were highly consistent across all 3 cohorts, indicating that immunologic changes after TNF treatment are specific to the combination of both drug exposure and responder status. In contrast, modular patterns of gene expression did not exhibit consistent differences between responders and nonresponders at baseline in the 3 study cohorts.

CONCLUSION

These data provide evidence that using gene expression modules related to inflammatory disease may provide a valuable method for objective monitoring of the response of RA patients who are treated with TNF inhibitors.

Gene expression analysis in RA: towards personalized medicine

Gene expression has recently been at the forefront of advance in personalized medicine, notably in the field of cancer and transplantation, providing a rational for a similar approach in rheumatoid arthritis (RA). RA is a prototypic inflammatory autoimmune disease with a poorly understood etiopathogenesis. Inflammation is the main feature of RA; however, many biological processes are involved at different stages of the disease. Gene expression signatures offer management tools to meet the current needs for personalization of RA patients' care. This review analyses currently available information with respect to RA diagnostic, prognostic and prediction of response to therapy with a view to highlight the abundance of data, whose comparison is often inconclusive due to the mixed use of material source, experimental methodologies and analysis tools, reinforcing the need for harmonization if gene expression signatures are to become a useful clinical tool in personalized medicine for RA patients.

Pharmacogenetics and pharmacogenomics for rheumatoid arthritis responsiveness to methotrexate treatment: the 2013 update

Rheumatoid arthritis (RA) is a complex, systemic autoimmune disease characterized by chronic inflammation of multiple peripheral joints, which leads to serious destruction of cartilage and bone, progressive deformity and severe disability. Methotrexate (MTX) is one of the first-line drugs commonly used in RA therapy owing to its excellent long-term efficacy and cheapness. However, the efficacy and toxicity of MTX treatment have significant interpatient variability. Genetic factors contribute to this variability. In this review, we have summarized and updated the progress of RA response to MTX treatment since 2009 by focusing on the fields of pharmacogenetics and pharmacogenomics. Identification of genetic factors involved in MTX treatment response will increase the understanding of RA pathology and the development of new personalized treatments.

Targeting BCL2 family in human myeloid dendritic cells: a challenge to cure diseases with chronic inflammations associated with bone loss

Rheumatoid arthritis (RA) and Langerhans cell histiocytosis (LCH) are common and rare diseases, respectively. They associate myeloid cell recruitment and survival in inflammatory conditions with tissue destruction and bone resorption. Manipulating dendritic cell (DC), and, especially, regulating their half-life and fusion, is a challenge. Indeed, these myeloid cells display pathogenic roles in both diseases and may be an important source of precursors for differentiation of osteoclasts, the bone-resorbing multinucleated giant cells. We have recently documented that the proinflammatory cytokine IL-17A regulates long-term survival of DC by inducing BCL2A1 expression, in addition to the constitutive MCL1 expression. We summarize bibliography of the BCL2 family members and their therapeutic targeting, with a special emphasis on MCL1 and BCL2A1, discussing their potential impact on RA and LCH. Our recent knowledge in the survival pathway, which is activated to perform DC fusion in the presence of IL-17A, suggests that targeting MCL1 and BCL2A1 in infiltrating DC may affect the clinical outcomes in RA and LCH. The development of new therapies, interfering with MCL1 and BCL2A1 expression, to target long-term surviving inflammatory DC should be translated into preclinical studies with the aim to increase the well-being of patients with RA and LCH.

Differential effects of decoy receptor- and antibody-mediated tumour necrosis factor blockage on FoxP3 expression in responsive arthritis patients

Our aim was to clarify if anti-tumour necrosis factor (TNF) drugs have effect on expression of three splice forms of FoxP3 mRNA in blood CD4+ T cells from rheumatoid arthritis (RA) patients compared with healthy controls. Forty-five rheumatoid arthritis patients treated with anti-TNF therapy were investigated in a 12-week prospective cohort study. FoxP3 isoforms, CD25 and CTLA-4 mRNA in blood CD4+ T cells were measured with quantitative real-time PCR. Patients benefitting from the treatment, based on changes in DAS28 scores, revealed a significant decrease in expression of full-length FoxP3 following 12 weeks treatment with TNF receptor 2 fusion protein (Etanercept), but not following treatment with anti-TNF antibodies (Adalimumab or Infliximab). A partial normalization of the CTLA-4/FoxP3fl ratio and a correlation between clinical improvement and change in FoxP3 mRNA expression were also seen in Etanercept responders. These changes were not observed in responsive patients treated with the antibody therapies. Our data suggest that TNF decoy receptor and anti-TNF antibodies differ in their effect on FoxP3 expression in responsive patients. As Etanercept binds both TNF-α and Lymphotoxin-α (LT-α), whereas the antibodies only target TNF-α, LT-α may regulate FoxP3 expression in a subset of RA patients. Our findings support the view that anti-TNF treatment is mainly symptomatic.