Fetuin-A and thyroxin binding globulin predict rituximab response in rheumatoid arthritis patients with insufficient response to anti-TNFα.

OBJECTIVES: Rheumatoid arthritis (RA) is a debilitating disease, but patient management and treatment have been revolutionized since the advent of bDMARDs. However, about one third of RA patients do not respond to specific bDMARD treatment without clear identified reasons. Different bDMARDs must be tried until the right drug is found. Here, we sought to identify a predictive protein signature to stratify patient responsiveness to rituximab (RTX) among patients with an insufficient response to a first anti-TNFα treatment. METHODS: Serum samples were collected at baseline before RTX initiation. A proteomics study comparing responders and nonresponders was conducted to identify and select potential predictive biomarkers whose concentration was measured by quantitative assays. Logistic regression was performed to determine the best biomarker combination to predict good or nonresponse to RTX (EULAR criteria after 6 months' treatment). RESULTS: Eleven biomarkers potentially discriminating between responders and nonresponders were selected following discovery proteomics. Quantitative immunoassays and univariate statistical analysis showed that fetuin-A and thyroxine binding globulin (TBG) presented a good capacity to discriminate between patient groups. A logistic regression analysis revealed that the combination of fetuin-A plus TBG could accurately predict a patient's responsiveness to RTX with an AUC of 0.86, sensitivity of 80%, and a specificity of 79%. CONCLUSION: In RA patients for whom a first anti-TNFα treatment has failed, the serum abundance of fetuin-A and TBG before initiating RTX treatment is an indicator for their response status at 6 months. ClinicalTrials.gov identifier: NCT01000441. Key Points • Proteomic analysis revealed 11 putative predictive biomarkers to discriminate rituximab responder vs. nonresponder RA patients. • Fetuin-A and TBG are significantly differentially expressed at baseline in rituximab responder vs. nonresponder RA patients. • Algorithm combining fetuin-A and TBG accurately predicts response to rituximab in RA patients with insufficient response to TNFi.

Calprotectin discriminates septic arthritis from pseudogout and rheumatoid arthritis.

OBJECTIVE: We aimed to determine whether calprotectin and α-defensins could discriminate septic from other inflammatory arthritides. METHODS: Synovial fluids with a predominance of neutrophils from patients with septic arthritis, pseudogout and RA were prospectively collected. Neutrophil-related proteins calprotectin and human neutrophil α-defensins levels were assessed in synovial fluids. Demographic parameters and biomarkers with P-value ⩽0.05 for differentiating septic from non-septic arthritis were included in a multivariable model. Multivariable logistic regression with stepwise selection was performed to build the final combined model. RESULTS: A total of 74 patients were included: septic arthritis (n = 26), pseudogout (n = 28) and RA (n = 20). Patients with septic arthritis were more likely to be male and young, and to display higher synovial neutrophil count. Calprotectin was significantly increased in patients with septic arthritis. The multivariable model included calprotectin, synovial fluid neutrophil count and gender. Calprotectin was the only biomarker that discriminated septic arthritis from non-septic inflammatory arthritides, with 76% sensitivity, 94% specificity and a positive likelihood ratio = 12.2 at the threshold for calprotectin of 150 mg/l. CONCLUSION: Synovial fluid calprotectin is a relevant biomarker to discriminate septic arthritis from other inflammatory arthritides. This biomarker should be tested in an independent cohort.

Systemic calprotectin and chronic inflammatory rheumatic diseases.

Calprotectin is a calcium binding protein produced by neutrophils and monocytes locally at the site of inflammation in order to trigger the innate immunity receptors. This unique characteristic makes it a good proxy for evaluation of local inflammation in chronic inflammatory rheumatic diseases. Complete data suggest, in inflammatory rheumatic diseases, a relevant role of calprotectin in the inflammatory process. The interest of serum or plasma calprotectin dosage has been studied intensively, in the current years, especially in rheumatoid arthritis, spondyloarthritis, juvenile idiopathic arthritis and ANCA associated vasculitis. Calprotectin seems to be a great candidate as biomarker to assess and monitor disease activity, to predict structural progression or response to the treatment. Calprotectin showed its ability to predict radiological progression in rheumatoid arthritis and ankylosing spondylitis. Serum calprotectin can predict the risk of relapse in ANCA associated vasculitis and the risk of inflammatory bowel disease in spondyloarthritis. Nevertheless, studies report controversial result requiring replication in other large cohort. The lack of assay standardization between studies is a problem to replicate and compare studies. In this review, we discuss on the interest of systemic calprotectin in chronic inflammatory rheumatic disease as a diagnostic, activity or prognostic biomarker.

Prealbumin, platelet factor 4 and S100A12 combination at baseline predicts good response to TNF alpha inhibitors in rheumatoid arthritis.

OBJECTIVES: Tumour necrosis factor-alpha inhibitors (TNFi) are effective treatments for Rheumatoid Arthritis (RA). Responses to treatment are barely predictable. As these treatments are costly and may induce a number of side effects, we aimed at identifying a panel of protein biomarkers that could be used to predict clinical response to TNFi for RA patients. METHODS: Baseline blood levels of C-reactive protein, platelet factor 4, apolipoprotein A1, prealbumin, α1-antitrypsin, haptoglobin, S100A8/A9 and S100A12 proteins in bDMARD naive patients at the time of TNFi treatment initiation were assessed in a multicentric prospective French cohort. Patients fulfilling good EULAR response at 6 months were considered as responders. Logistic regression was used to determine best biomarker set that could predict good clinical response to TNFi. RESULTS: A combination of biomarkers (prealbumin, platelet factor 4 and S100A12) was identified and could predict response to TNFi in RA with sensitivity of 78%, specificity of 77%, positive predictive values (PPV) of 72%, negative predictive values (NPV) of 82%, positive likelihood ratio (LR+) of 3.35 and negative likelihood ratio (LR-) of 0.28. Lower levels of prealbumin and S100A12 and higher level of platelet factor 4 than the determined cutoff at baseline in RA patients are good predictors for response to TNFi treatment globally as well as to Infliximab, Etanercept and Adalimumab individually. CONCLUSION: A multivariate model combining 3 biomarkers (prealbumin, platelet factor 4 and S100A12) accurately predicted response of RA patients to TNFi and has potential in a daily practice personalized treatment.

Peripheral Blood TCR Repertoire Profiling May Facilitate Patient Stratification for Immunotherapy against Melanoma.

Many metastatic melanoma patients experience durable responses to anti-PD1 and/or anti-CTLA4; however, a significant proportion (over 50%) do not benefit from the therapies. In this study, we sought to assess pretreatment liquid biopsies for biomarkers that may correlate with response to checkpoint blockade. We measured the combinatorial diversity evenness of the T-cell receptor (TCR) repertoire (the DE50, with low values corresponding to more clonality and lack of TCR diversity) in pretreatment peripheral blood mononuclear cells from melanoma patients treated with anti-CTLA4 (n = 42) or anti-PD1 (n = 38) using a multi-N-plex PCR assay on genomic DNA (gDNA). A receiver operating characteristic curve determined the optimal threshold for a dichotomized analysis according to objective responses as defined by RECIST1.1. Correlations between treatment outcome, clinical variables, and DE50 were assessed in multivariate regression models and confirmed with Fisher exact tests. In samples obtained prior to treatment initiation, we showed that low DE50 values were predictive of a longer progression-free survival and good responses to PD-1 blockade, but, on the other hand, predicted a poor response to CTLA4 inhibition. Multivariate logistic regression models identified DE50 as the only independent predictive factor for response to anti-CTLA4 therapy (P = 0.03) and anti-PD1 therapy (P = 0.001). Fisher exact tests confirmed the association of low DE50 with response in the anti-CTLA4 (P = 0.041) and the anti-PD1 cohort (P = 0.0016). Thus, the evaluation of basal TCR repertoire diversity in peripheral blood, using a PCR-based method, could help predict responses to anti-PD1 and anti-CTLA4 therapies.

Peripheral T cell receptor diversity is associated with clinical outcomes following ipilimumab treatment in metastatic melanoma.

BACKGROUND: Ipilimumab improves overall survival in a subset of patients with metastatic melanoma. Peripheral blood T cell receptor (TCR) repertoire diversity has been associated with favorable outcomes in patients with cancer, but its relevance as a biomarker for ipilimumab outcomes remains unknown. FINDINGS: In this pilot study, we analyzed the pre-treatment peripheral blood TCR repertoire in 12 patients with metastatic melanoma who received ipilimumab at 3 mg/kg (clinical benefit, n = 4; no clinical benefit, n = 8). TCR diversity was evaluated using a polymerase chain reaction assay which measures TCR combinatorial diversity between V and J genes from genomic DNA. TCR repertoire diversity was studied through richness (observed V-J rearrangements) and evenness (similarity between the frequencies of specific V-J rearrangements). The Wilcoxon rank sum test was used to compare patients with clinical benefit and those without. Association with benefit in a dichotomized analysis was assessed through a Fisher's exact test. Overall survival was studied through log-rank analysis. There was a significant difference in richness (p = 0.033) and evenness (p = 0.028) between patients with and without clinical benefit. Dichotomized analysis showed that none of the patients with low richness (n = 0/5, p = 0.081) nor low evenness (n = 0/7, p = 0.01) achieved clinical benefit. There were no significant differences in overall survival. CONCLUSIONS: In this small group of patients, baseline TCR diversity in the peripheral blood was associated with clinical outcomes. Further investigation is ongoing in larger cohorts of patients to explore these preliminary findings and determine whether TCR diversity can be used as a predictive biomarker in cancer immunotherapy.

Clonal restriction and predominance of regulatory T cells in coronary thrombi of patients with acute coronary syndromes.

AIMS: Regulatory T cells (Treg) exert anti-inflammatory and atheroprotective effects in experimental atherosclerosis. Treg can be induced against specific antigens using immunization strategies associated with clonal restriction. No data exist on Treg in combination with clonal restriction of T cells in patients with acute coronary syndromes (ACS). METHODS AND RESULTS: Among T cell subsets characterized by flow cytometry, Treg (CD4(+) CD25(+) CD127(low)) were twice as frequent in coronary thrombi compared with peripheral blood. Treg prevailed among T cell subsets identified in coronary thrombi. To evaluate clonal restriction, genomic DNA was extracted from coronary thrombi and peripheral blood in order to evaluate T cell receptor (TCR) ß chain diversity by means of Multi-N-plex PCR using a primer specific for all TCR ß V gene segments and another primer specific for TCR ß J gene segments. T cell receptor diversity was reduced in thrombi compared with peripheral blood (intra-individual comparisons in 16 patients) with 8 gene rearrangements in the TCR common in at least 6 out of 16 analysed coronary thrombi. Compared with age-matched healthy controls (n = 16), TCR diversity was also reduced in peripheral blood of patients with ACS; these findings were independent of peripheral T cell numbers. CONCLUSION: We provide novel evidence for a perturbed T cell compartment characterized by clonal restriction in peripheral blood and coronary thrombi from patients with ACS. Our findings warrant further studies on Treg as novel therapeutic targets aimed at enhancing this anti-inflammatory component of adaptive immunity in human atherothrombosis.

Lymphopenia combined with low TCR diversity (divpenia) predicts poor overall survival in metastatic breast cancer patients.

Lymphopenia (< 1Giga/L) detected before initiation of chemotherapy is a predictive factor for death in metastatic solid tumors. Combinatorial T cell repertoire (TCR) diversity was investigated and tested either alone or in combination with lymphopenia as a prognostic factor at diagnosis for overall survival (OS) in metastatic breast cancer (MBC) patients. The combinatorial TCR diversity was measured by semi quantitative multi-N-plex PCR on blood samples before the initiation of the first line chemotherapy in a development (n = 66) and validation (n = 67) MBC patient cohorts. A prognostic score, combining lymphocyte count and TCR diversity was evaluated. Univariate and multivariate analyses of prognostic factors for OS were performed in both cohorts. Lymphopenia and severe restriction of TCR diversity called "divpenia" (diversity ≤ 33%) were independently associated with shorter OS. Lympho-divpenia combining lymphopenia and severe divpenia accurately identified patients with poor OS in both cohorts (7.6 and 10.6 vs 24.5 and 22.9 mo). In multivariate analysis including other prognostic clinical factors, lympho-divpenia was found to be an independent prognostic factor in the pooled cohort (p = 0.005) along with lack of HER2 and hormonal receptors expression (p = 0.011) and anemia (p = 0.009). Lympho-divpenia is a novel prognostic factor that will be used to improve quality of MBC patients' medical care.