Predicting Sustained Clinical Response to Rituximab in Moderate to Severe Systemic Manifestations of Primary Sjögren Syndrome.

OBJECTIVE: To assess outcomes of repeat rituximab cycles and identify predictors of sustained clinical response in systemic manifestations of primary Sjögren syndrome (pSS). METHODS: An observational study was conducted in 40 rituximab-treated patients with pSS. Clinical response was defined as a 3-point or more reduction in the European League Against Rheumatism (EULAR) Sjögren Disease Activity Index (ESSDAI) at 6 months from baseline. Peripheral blood B cells were measured using highly sensitive flow cytometry. Predictors of sustained response (within two rituximab cycles) were analyzed using penalized logistic regression. RESULTS: Thirty-eight out of 40 patients had moderate to severe systemic disease (ESSDAI >5). Main domains were articular (73%), mucocutaneous (23%), hematological (20%), and nervous system (18%). Twenty-eight out of 40 (70%) patients were on concomitant immunosuppressants. One hundred sixty-nine rituximab cycles were administered with a total follow-up of 165 patient-years. In cycle 1 (C1), 29/40 (73%) achieved ESSDAI response. Of C1 responders, 23/29 received retreatment on clinical relapse, and 15/23 (65%) responded. Of the 8/23 patients who lost response, these were due to secondary non-depletion and non-response (2NDNR; 4/23 [17%] as we previously observed in systemic lupus erythematosus with antirituximab antibodies, inefficacy = 2/23, and other side effects = 2/23). Within two cycles, 13/40 (33%) discontinued therapy. In multivariable analysis, concomitant immunosuppressant (odds ratio 7.16 [95% confidence interval: 1.37-37.35]) and achieving complete B-cell depletion (9.78 [1.32-72.25]) in C1 increased odds of response to rituximab. At 5 years, 57% of patients continued on rituximab. CONCLUSION: Our data suggest that patients with pSS should be co-prescribed immunosuppressant with rituximab, and treatment should aim to achieve complete depletion. About one in six patients develop 2NDNR in repeat cycles. Humanized or type 2 anti-CD20 antibodies may improve clinical response in extra-glandular pSS.

Kinobead Profiling Reveals Reprogramming of BCR Signaling in Response to Therapy within Primary CLL Cells.

PURPOSE: B-cell receptor (BCR) signaling is critical for the pathogenesis of chronic lymphocytic leukemia (CLL), promoting both malignant cell survival and disease progression. Although vital, understanding of the wider signaling network associated with malignant BCR stimulation is poor. This is relevant with respect to potential changes in response to therapy, particularly involving kinase inhibitors. In the current study, we describe a novel high-resolution approach to investigate BCR signaling in primary CLL cells and track the influence of therapy on signaling response. EXPERIMENTAL DESIGN: A kinobead/mass spectrometry-based protocol was used to study BCR signaling in primary CLL cells. Longitudinal analysis of samples donated by clinical trial patients was used to investigate the impact of chemoimmunotherapy and ibrutinib on signaling following surface IgM engagement. Complementary Nanostring and immunoblotting analysis was used to verify our findings. RESULTS: Our protocol isolated a unique, patient-specific signature of over 30 kinases from BCR-stimulated CLL cells. This signature was associated with 13 distinct Kyoto Encyclopedia of Genes and Genomes pathways and showed significant change in cells from treatment-naïve patients compared with those from patients who had previously undergone therapy. This change was validated by longitudinal analysis of clinical trials samples where BCR-induced kinome responses in CLL cells altered between baseline and disease progression in patients failing chemoimmunotherapy and between baseline and treatment in patients taking ibrutinib. CONCLUSIONS: These data comprise the first comprehensive proteomic investigation of the BCR signaling response within CLL cells and reveal unique evidence that these cells undergo adaptive reprogramming of this signaling in response to therapy.

A seven-gene expression panel distinguishing clonal expansions of pre-leukemic and chronic lymphocytic leukemia B cells from normal B lymphocytes.

Chronic lymphocytic leukemia (CLL) is a clonal disease of B lymphocytes manifesting as an absolute lymphocytosis in the blood. However, not all lymphocytoses are leukemic. In addition, first-degree relatives of CLL patients have an ~15 % chance of developing a precursor condition to CLL termed monoclonal B cell lymphocytosis (MBL), and distinguishing CLL and MBL B lymphocytes from normal B cell expansions can be a challenge. Therefore, we selected FMOD, CKAP4, PIK3C2B, LEF1, PFTK1, BCL-2, and GPM6a from a set of genes significantly differentially expressed in microarray analyses that compared CLL cells with normal B lymphocytes and used these to determine whether we could discriminate CLL and MBL cells from B cells of healthy controls. Analysis with receiver operating characteristics and Bayesian relevance determination demonstrated good concordance with all panel genes. Using a random forest classifier, the seven-gene panel reliably distinguished normal polyclonal B cell populations from expression patterns occurring in pre-CLL and CLL B cell populations with an error rate of 2 %. Using Bayesian learning, the expression levels of only two genes, FMOD and PIK3C2B, correctly distinguished 100 % of CLL and MBL cases from normal polyclonal and mono/oligoclonal B lymphocytes. Thus, this study sets forth effective computational approaches that distinguish MBL/CLL from normal B lymphocytes. The findings also support the concept that MBL is a CLL precursor.

Repeat cycles of rituximab on clinical relapse in ANCA-associated vasculitis: identifying B cell biomarkers for relapse to guide retreatment decisions.

OBJECTIVE: To assess clinical and B cell biomarkers to predict relapse after rituximab in antineutrophil cytoplasmic antibody (ANCA)-associated vasculitis (AAV) using retreatment on clinical relapse strategy. METHODS: 35 patients with AAV received treatment with 2×1000 mg rituximab, repeated on clinical relapse (up to 5 cycles). Disease activity was assessed by Birmingham Vasculitis Activity Score (BVAS) and peripheral B cell subsets using highly sensitive flow cytometry (HSFC) as previously described; both performed at baseline and every 3 months. RESULTS: Response rates were high: >83%, with median time-to-relapse of 82 weeks for cycle 1 (C1) and >54 weeks for all cycles. Prior to rituximab, AAV was characterised by naïve B-lymphopenia compared to healthy controls. This dysregulation was more marked in patients with raised C-reactive protein (CRP) (p<0.05). In C1, no clinical feature predicted relapse. However, repopulation of naïve B cell at 6 months was associated with a reduced risk of relapse (HR: 0.326, 95% 0.114 to 0.930, p=0.036). Relapse rates at 12 and 18 months were 0% and 14% with naïve repopulation at 6 months, and 31% and 54% without naïve repopulation. CONCLUSIONS: Responses to B cell depletion therapy are long-lasting and relapse post-treatment may be predicted by absence of naïve B cell repopulation at 6 months. Naïve B-lymphopenia may be a biomarker of disease activity in AAV.

An extra dose of rituximab improves clinical response in rheumatoid arthritis patients with initial incomplete B cell depletion: a randomised controlled trial.

OBJECTIVES: Since clinical non-response to 2×1000 mg rituximab has previously been found to be associated with incomplete B cell depletion, we determined, in a randomised controlled proof of concept study, whether patients with initial incomplete B cell depletion would benefit from an additional infusion of rituximab at week 4. METHODS: Patients with active rheumatoid arthritis despite methotrexate received a first infusion of rituximab 1000 mg and were tested for persistent B cells using highly sensitive flow cytometry on day 15. All received a second infusion of 1 g (according to license), but patients with persistent B cells were subsequently randomised double-blind to receive, 2 weeks later, either a third infusion of 1000 mg rituximab or placebo. Clinical response was determined by European League Against Rheumatism (EULAR) and American College of Rheumatology (ACR) criteria. RESULTS: Baseline characteristics were balanced between groups. Treatment with 3×1000 mg rituximab resulted in significantly greater depletion (lower B cell and plasmablast numbers between 8 and 28 weeks) paralleled by significantly better EULAR and ACR20 response rates at 40 weeks (p=0.035 and p=0.027, respectively) and 52 weeks (p=0.021 and p=0.043, respectively) compared with 2×1000 mg. Immunoglobulin titres remained stable in both arms, and adverse event rates were balanced. CONCLUSIONS: In rituximab-treated patients with incomplete B cell depletion (predictive of poor response), an extra 1000 mg infusion of rituximab at 4 weeks produced both better depletion and clinical responses than placebo with no worsening of safety. Degree of depletion is an important, but modifiable, determinant of response.

Inherited genetic susceptibility to monoclonal gammopathy of unknown significance.

Monoclonal gammopathy of undetermined significance (MGUS) is present in ∼2% of individuals age >50 years. The increased risk of multiple myeloma (MM) in relatives of individuals with MGUS is consistent with MGUS being a marker of inherited genetic susceptibility to MM. Common single-nucleotide polymorphisms (SNPs) at 2p23.3 (rs6746082), 3p22.1 (rs1052501), 3q26.2 (rs10936599), 6p21.33 (rs2285803), 7p15.3 (rs4487645), 17p11.2 (rs4273077), and 22q13.1 (rs877529) have recently been shown to influence MM risk. To examine the impact of these 7 SNPs on MGUS, we analyzed two case-control series totaling 492 cases and 7306 controls. Each SNP independently influenced MGUS risk with statistically significant associations (P < .02) for rs1052501, rs2285803, rs4487645, and rs4273077. SNP associations were independent, with risk increasing with a larger number of risk alleles carried (per allele odds ratio, 1.18; P < 10(-7)). Collectively these data are consistent with a polygenic model of disease susceptibility to MGUS.

Abatacept or tocilizumab after rituximab in rheumatoid arthritis? An exploratory study suggests non-response to rituximab is associated with persistently high IL-6 and better clinical response to IL-6 blocking therapy.

OBJECTIVES: To evaluate the efficacy and safety of two different targeted approaches-abatacept or tocilizumab-after rituximab therapy in rheumatoid arthritis, and to explain observed difference in efficacy using blood and synovial studies of interleukin 6 (IL-6) and B cells in patients receiving rituximab therapy. METHODS: Consecutive series of patients who had discontinued rituximab therapy owing to inefficacy or toxicity were treated with abatacept (n=16) or tocilizumab (n=35). Clinical response and reasons for discontinuation were evaluated. Serial blood and synovial samples were obtained from a group of 57 and 25 rituximab-treated patients, respectively, and were analysed for B cells and IL-6 using flow cytometry, immunohistochemistry and quantitative real-time PCR. RESULTS: In the abatacept group, mean (SEM) Disease Activity Score in 28 joints calculated using the erythrocyte sedimentation rate (DAS28-ESR) reduced from 5.69 (0.42) at baseline to 4.94 (0.44) at 6 months (p=0.12). In the tocilizumab group: mean (SEM) DAS28- ESR reduced from 5.75 (0.21) at baseline to 3.28 (0.26) at 6 months (p<0.001). This was paralleled by a significant swollen joint count reduction in the tocilizumab (5.47 (0.70) to 2.70 (0.61), p=0.033), but not abatacept (6.23 (1.3) to 4.15 (1.2), p=0.26), group. In the synovium, despite complete depletion of B cells in 19/22 patients, IL-6 mRNA expression was not significantly reduced after rituximab. Blood B cell numbers remained low 12 months after rituximab. Serum IL-6 was raised at baseline and significantly higher in rituximab clinical non-responders (p=0.035) than responders. A significant reduction in serum IL-6 was seen in rituximab clinical responders (p=0.005) but not in non-responders (p=0.237). CONCLUSION: In patients with rheumatoid arthritis for whom rituximab therapy failed despite adequate B cell depletion, IL-6-directed therapy might be a more logical and effective treatment choice than T cell costimulation blockade. Further controlled studies investigating other possible mechanisms are needed to validate these initial findings.

B cell biomarkers of rituximab responses in systemic lupus erythematosus.

OBJECTIVE: Rituximab appears to be effective in many studies of systemic lupus erythematosus (SLE), with variable initial clinical response and time to relapse. However, results of a randomized controlled trial of rituximab were negative. This study was undertaken to evaluate the effectiveness of rituximab in SLE, using highly sensitive flow cytometry (HSFC), which can define B cell numbers 50-100 times lower than conventional techniques and predicts responses in rheumatoid arthritis. METHODS: Thirty-nine patients with active SLE were started on a standard regimen of rituximab with intravenous and oral steroids. Clinical response and relapse were defined using the British Isles Lupus Assessment Group (BILAG) index with criteria for major clinical response, partial clinical response, and nonresponse. HSFC, including analysis of B cell subsets, was performed. RESULTS: There was a significant reduction from baseline in global BILAG score at all time points analyzed (P<0.0001), and major clinical response and partial clinical response rates were 51% and 31%, respectively. Time to relapse was highly variable. Fifty percent of the patients relapsed after 6-18 months (earlier relapse); the remainder relapsed at a slower rate (later relapse). B cell depletion and repopulation were variable and were predictive of these clinical outcomes. There was a persistent B cell presence in 21 patients after 2 infusions of rituximab, which included all 7 patients with no response (P=0.012 versus patients with complete depletion of B cells). Memory B cell (P=0.02) and plasmablast (P<0.001) repopulation after 26 weeks was markedly faster in patients with earlier relapse versus patients with later relapse. CONCLUSION: Our findings indicate that rituximab is effective in SLE, and clinical responses are supported by close correlation with B cell numbers. HSFC is a valuable tool in the assessment and prediction of response in SLE.

Reduced-dose rituximab in rheumatoid arthritis: efficacy depends on degree of B cell depletion.

OBJECTIVE: Studies comparing 500 mg rituximab and 1,000 mg rituximab doses in rheumatoid arthritis have yielded conflicting data on clinical outcomes, but in all of these studies a subgroup of patients has had excellent responses at the lower dose. Historically, it was considered that rituximab uniformly depleted B cells at both doses. Using highly sensitive assays, we have shown that B cell depletion is variable and predictive of clinical response. Using the same techniques, we undertook the present study to test the hypothesis that the level of B cell depletion, rather than the rituximab dose, determines clinical response. METHODS: Nineteen patients were treated with two 500-mg infusions of rituximab, and 61 patients were treated with two 1,000-mg infusions of rituximab. Highly sensitive flow cytometry was performed at 0, 2, 6, 14, and 26 weeks. European League Against Rheumatism (EULAR) response rates at 6 months were compared between patients with and those without complete depletion at each dose. RESULTS: The median B cell count was numerically higher at all time points following therapy in the 500 mg rituximab group. Twenty-five percent of patients in the 500 mg rituximab group had complete depletion at 2 weeks, compared with 49% of those in the 1,000 mg rituximab group. Complete depletion at 2 weeks after treatment with 500 mg rituximab was associated with lower baseline preplasma cell counts (P = 0.047). Most patients responded after either dose, but response was related to B cell depletion. Notably, in the 500 mg rituximab group all patients with complete depletion had a EULAR good response (P = 0.011). CONCLUSION: This pilot study suggests that the degree of B cell depletion, rather than the dose of rituximab, determines clinical response. It may be possible to predict which patients will respond to lower-dose rituximab, and this may allow more cost-effective treatment.

A global expression-based analysis of the consequences of the t(4;14) translocation in myeloma.

PURPOSE: Our purpose in this report was to define genes and pathways dysregulated as a consequence of the t(4;14) in myeloma, and to gain insight into the downstream functional effects that may explain the different prognosis of this subgroup. EXPERIMENTAL DESIGN: Fibroblast growth factor receptor 3 (FGFR3) overexpression, the presence of immunoglobulin heavy chain-multiple myeloma SET domain (IgH-MMSET) fusion products and the identification of t(4;14) breakpoints were determined in a series of myeloma cases. Differentially expressed genes were identified between cases with (n = 5) and without (n = 24) a t(4;14) by using global gene expression analysis. RESULTS: Cases with a t(4;14) have a distinct expression pattern compared with other cases of myeloma. A total of 127 genes were identified as being differentially expressed including MMSET and cyclin D2, which have been previously reported as being associated with this translocation. Other important functional classes of genes include cell signaling, apoptosis and related genes, oncogenes, chromatin structure, and DNA repair genes. Interestingly, 25% of myeloma cases lacking evidence of this translocation had up-regulation of the MMSET transcript to the same level as cases with a translocation. CONCLUSIONS: t(4;14) cases form a distinct subgroup of myeloma cases with a unique gene signature that may account for their poor prognosis. A number of non-t(4;14) cases also express MMSET consistent with this gene playing a role in myeloma pathogenesis.

Insights into the multistep transformation of MGUS to myeloma using microarray expression analysis.

To define specific pathways important in the multistep transformation process of normal plasma cells (PCs) to monoclonal gammopathy of uncertain significance (MGUS) and multiple myeloma (MM), we have applied microarray analysis to PCs from 5 healthy donors (N), 7 patients with MGUS, and 24 patients with newly diagnosed MM. Unsupervised hierarchical clustering using 125 genes with a large variation across all samples defined 2 groups: N and MGUS/MM. Supervised analysis identified 263 genes differentially expressed between N and MGUS and 380 genes differentially expressed between N and MM, 197 of which were also differentially regulated between N and MGUS. Only 74 genes were differentially expressed between MGUS and MM samples, indicating that the differences between MGUS and MM are smaller than those between N and MM or N and MGUS. Differentially expressed genes included oncogenes/tumor-suppressor genes (LAF4, RB1, and disabled homolog 2), cell-signaling genes (RAS family members, B-cell signaling and NF-kappaB genes), DNA-binding and transcription-factor genes (XBP1, zinc finger proteins, forkhead box, and ring finger proteins), and developmental genes (WNT and SHH pathways). Understanding the molecular pathogenesis of MM by gene expression profiling has demonstrated sequential genetic changes from N to malignant PCs and highlighted important pathways involved in the transformation of MGUS to MM.

A molecular study of the t(4;14) in multiple myeloma.

The t(4;14) translocation is found in approximately 10% of myeloma patients and results in the deregulation of at least two genes, MMSET and fibroblast growth factor receptor 3 (FGFR3), with the formation of a fusion product between MMSET and the immunoglobulin heavy chain (IgH) locus and overexpression of FGFR3. We have analysed a series of 80 patient samples, comprising 67 multiple myeloma (MM) cases and 13 monoclonalgammopathy of undetermined significance (MGUS) cases, using RT-PCR to detect IgH-MMSET fusions. The t(4;14) translocation was detected in 7/67 (10%) myeloma cases and all seven expressed FGFR3 which was not seen in t(4;14)-negative myeloma cases. In the MGUS cases, a similar proportion of t(4;14)-positive cases was found (2/13; 15%), but none of these expressed FGFR3. All patients with detectable FGFR3 expressed both the FGFR3 IIIb and FGFR3 IIIc isoforms, the result of alternative splicing in the ligand binding domain, and exon-deleted variants of FGFR3. We also identified a cryptic splice site in MMSET which results in a 277 amino acid deletion downstream of the breakpoint on der(4). FGFR3 mutation analysis revealed no mutations in the presenting myeloma or MGUS samples. However, we also had access to paired presentation and relapse samples which had been taken from a patient 13 months apart. Both samples had the t(4;14) translocation and overexpressed FGFR3, but only the relapse sample possessed the K650E mutation in the kinase domain of FGFR3. This suggests that targeted mutation in the translocated FGFR3 gene when under the control of the immunoglobulin promoters can occur and may provide one mechanism for disease progression.

Minimal residual disease monitoring in multiple myeloma.

Traditionally, response to treatment in multiple myeloma has been measured by the serum or urinary paraprotein and the percentage of plasma cells in the bone marrow. The use of allogeneic and autologous transplantation has increased the complete response rate and overall survival in patients with myeloma, and in order to assess the effects of such treatments accurately more sensitive methods for assessing residual disease have been introduced. The aim of this chapter, therefore, is to describe the available techniques to assess response, monitor residual disease and predict relapse in myeloma. The traditional techniques of paraprotein measurement using electrophoresis and immunofixation are compared with more sensitive approaches involving the polymerase chain reaction for detecting rearrangements of the immunoglobulin heavy-chain region and flow cytometry for detecting malignant plasma cells. Emphasis is placed on the advantages and disadvantages of each method and its utility in the clinical setting.