To study the role of the JAK2-V617F mutation in leukemic transformation, we examined 27 patients with myeloproliferative disorders (MPDs) who transformed to acute myeloid leukemia (AML). At MPD diagnosis, JAK2-V617F was detectable in 17 of 27 patients. Surprisingly, only 5 of 17 patients developed JAK2-V617F–positive AML, whereas 9 of 17 patients transformed to JAK2-V617F–negative AML. Microsatellite analysis in a female patient showed that mitotic recombination was not responsible for the transition from JAK2-V617F–positive MPD to JAK2-V617F–negative AML, and clonality determined by the MPP1 polymorphism demonstrated that the granulocytes and leukemic blasts inactivated the same parental X chromosome. In a second patient positive for JAK2-V617F at transformation, but with JAK2-V617F–negative leukemic blasts, we found del(11q) in all cells examined, suggesting a common clonal origin of MPD and AML. We conclude that JAK2-V617F–positive MPD frequently yields JAK2-V617F–negative AML, and transformation of a common JAK2-V617F–negative ancestor represents a possible mechanism.

We determined the allelic frequency of the JAK2-V617F mutation in DNA and assessed the expression levels of the mutant and wild-type JAK2 mRNA in granulocytes from 60 patients with essential thrombocythemia (ET) and 62 patients with polycythemia vera (PV) at the time of diagnosis. Using allele-specific quantitative polymerase chain reaction (qPCR), we detected JAK2-V617F in 75% of ET and 97% of PV at diagnosis. The total JAK2 mRNA levels were elevated in ET, PV, and secondary and idiopathic erythrocytosis, suggesting that hyperactive hematopoiesis alters JAK2 expression. The expression levels of JAK2-V617F mRNA were variable but strongly correlated with the allelic ratio of JAK2-V617F determined in DNA. Thus, differences in JAK2-V617F expression, markedly lower in ET than in PV, reflected different percentages of granulocytes carrying the mutation. Moreover, allelic ratios higher than 50% JAK2-V617F, indicating the presence of granulocytes homozygous for JAK2-V617F, were found in 70% of PV at diagnosis but never in ET.

RA is a complex disease that develops as a series of events often referred to as disease continuum. RA would benefit from novel biomarker development for diagnosis where new biomarkers are still needed (even if progresses have been made with the inclusion of ACPA into the ACR/EULAR 2010 diagnostic criteria) and for prognostic notably in at risk of evolution patients with autoantibody-positive arthralgia. Risk biomarkers for rapid evolution or cardiovascular complications are also highly desirable. Monitoring biomarkers would be useful in predicting relapse. Finally, predictive biomarkers for therapy outcome would allow tailoring therapy to the individual. Increasing numbers of cytokines have been involved in RA pathology. Many have the potential as biomarkers in RA especially as their clinical utility is already established in other diseases and could be easily transferable to rheumatology. We will review the current knowledge’s relation to cytokine used as biomarker in RA. However, given the complexity and heterogeneous nature of RA, it is unlikely that a single cytokine may provide sufficient discrimination; therefore multiple biomarker signatures may represent more realistic approach for the future of personalised medicine in RA.

Autoantibodies have been associated with human pathologies for a long time, particularly with autoimmune diseases (AIDs). Rheumatoid factor (RF) is known since the late 1930s to be associated with rheumatoid arthritis (RA). The discovery of anticitrullinated protein antibodies in the last century has changed this and other posttranslational modifications (PTM) relevant to RA have since been described. Such PTM introduce neoepitopes in proteins that can generate novel autoantibody specificities. The recent recognition of these novel specificities in RA provides a unique opportunity to understand human B-cell developmentin vivo. In this paper, we will review the three of the main classes of PTMs already associated with RA: citrullination, carbamylation, and oxidation. With the advancement of research methodologies it should be expected that other autoantibodies against PTM proteins could be discovered in patients with autoimmune diseases. Many of such autoantibodies may provide significant biomarker potential.

Objectives The therapeutic goal for patients with rheumatoid arthritis (RA) is clinical remission. This is best achieved by early diagnosis and appropriate therapeutic intervention. RA is associated with dysregulation of T-cell subsets (naïve, regulatory (Treg) and inflammation-related cells (IRC)) early in the disease. Our aim was to test the hypothesis that T-cell subset quantification can predict the achievement of clinical remission with early treatment in RA. Methods T-cell subsets were quantified in 108 drug-naïve, early RA patients commencing methotrexate (MTX) or MTX+antitumor necrosis factor (anti-TNF) and in 105 healthy controls (HC). The primary outcome assessed was remission (DAS28<2.6). A pilot study used frozen cells (38 patients and 35 HCs, see online supplementary material) and was validated with fresh blood (70 patients and 70 HCs). Results Immune dysregulation in early RA was confirmed with an association between age and reduced naïve cells compared with HCs (p=0.006), a lower age-adjusted Treg and higher IRC frequency (p=0.001). Anticitrullinated peptide antibody (ACPA) positivity was associated with lower naïve (p=0.031) and Treg frequencies (p=0.039). In 50 patients treated with MTX, ACPA/age-adjusted analysis demonstrated that higher naïve cell frequency (relative to HC) was associated with remission (OR 5.90 (1.66 to 20.98), p=0.006, sensitivity/specificity 62%/79%, Positive Predictive Value (PPV)/Negative Predictive Value (NPV) 66%/76%). Remission with MTX+anti-TNF (n=20) was not found to be associated with naïve cell frequency, and for patients with reduced naïve cells the remission rate increased from 24% (MTX) to 42% (MTX+anti-TNF). Conclusions Baseline T-cell subset analysis has a value in predicting early RA remission with first therapy with MTX. Immunological analysis could be used in conjunction with clinical/serological features to predict response to MTX and help select the most appropriate therapy at disease presentation.

Background: Glioblastoma is the most aggressive primary brain tumor, and is associated with a very poor prognosis. In this study we investigated the potential of microRNA expression profiles to predict survival in this challenging disease.Methods: MicroRNA and mRNA expression data from glioblastoma (n = 475) and grade II and III glioma (n = 178) were accessed from The Cancer Genome Atlas. LASSO regression models were used to identify a prognostic microRNA signature. Functionally relevant targets of microRNAs were determined using microRNA target prediction, experimental validation and correlation of microRNA and mRNA expression data.Results: A 9‐microRNA prognostic signature was identified which stratified patients into risk groups strongly associated with survival (p = 2.26e−09), significant in all glioblastoma subtypes except the non‐G‐CIMP proneural group. The statistical significance of the microRNA signature was higher than MGMT methylation in temozolomide treated tumors. The 9‐microRNA risk score was validated in an independent dataset (p = 4.50e−02) and also stratified patients into high‐ and low‐risk groups in lower grade glioma (p = 5.20e−03). The majority of the 9 microRNAs have been previously linked to glioblastoma biology or treatment response. Integration of the expression patterns of predicted microRNA targets revealed a number of relevant microRNA/target pairs, which were validated in cell lines.Conclusions: We have identified a novel, biologically relevant microRNA signature that stratifies high‐ and low‐risk patients in glioblastoma. MicroRNA/mRNA interactions identified within the signature point to novel regulatory networks. This is the first study to formulate a survival risk score for glioblastoma which consists of microRNAs associated with glioblastoma biology and/or treatment response, indicating a functionally relevant signature.