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Center for Global Research Data

Investigating the effects of rituximab on specific cell subsets and cytokine levels in systemic lupus erythematosus patients and constructing a prediction model of treatment response

Research Proposal Summary in Plain English

Systemic lupus erythematosus (SLE) is a chronic autoimmune disease that primarily affects women of child-bearing age and can be life threatening. Currently, many patients are unable to attain adequate disease control with existing treatments. Numerous attempts have been made to develop more effective therapies for SLE, however most trials have failed. This is in part due to the complexity of the disease, which makes it hard to select appropriate patients for a trial, and due to the use of preexisting medications during the trial, which can mask the benefit of a new treatment. In 2010 and 2012, two clinical trials were conducted using a drug called rituximab, which depletes a specific immune cell in the body known as the B cell. These cells are responsible for making antibodies, which normally protect the body against foreign invaders such as bacteria and viruses, however in SLE patients, these antibodies attack the person’s own tissues. Thus, it makes rational sense that eliminating these cells could improve disease activity. Neither trial was successful, however, likely due to the aforementioned issues. However, a number of interesting labs were performed before and after treatment, and most have never been analyzed. This project proposes to examine the effects of rituximab on different immune cell subsets and cytokines (messenger molecules that can lead to inflammation). By understanding how these parameters change in patients who respond to rituximab compared to those who do not respond, it may provide key insights into how rituximab works and allow us to predict patients who are more likely to respond to rituximab in the future.

Research Proposal Plan

Research Background

Systemic lupus erythematosus (SLE) is one of the most complex, difficult to treat autoimmune diseases faced by rheumatologists. It is a chronic, inflammatory disease that primarily affects women of child-bearing age and can be life threatening [1]. In fact, up to 10% of SLE patients will not survive five years past their initial diagnosis [2]. SLE pathogenesis is complex and multifactorial, involving contributions from a variety of immune cells and mediators. B cells in particular have been actively investigated because of their ability to produce autoantibodies such as anti-nuclear antibodies and anti-double stranded DNA antibodies, which are hallmarks of the disease, and for their role as antigen-presenting cells to autoreactive T cells. For this reason, treating SLE patients with the chimeric monoclonal antibody rituximab, and thereby depleting CD20+ B cells, has strong merit. Numerous small studies with rituximab initially reported a treatment benefit in SLE [3-5]. Two pivotal trials, known as the EXPLORER [6] and LUNAR [7] trials, were conducted to more robustly study the efficacy of rituximab in SLE.

In the EXPLORER trial, patients with active non-renal SLE scoring at least one British Isles Lupus Assessment Group (BILAG) A score or two or more BILAG B scores were enrolled. Subjects continued their background immunosuppressant and were also treated with 0.5 mg/kg/day to 1 mg/kg/day oral prednisone at the beginning of the trial. LUNAR, on the other hand, enrolled SLE patients with biopsy-proven class III or IV nephritis. Subjects were treated with mycophenolate mofetil 3g daily and 0.75 mg/kg/day oral corticosteroids. In both studies, patients were randomized to receive either rituximab 1000mg or matching placebo for two total doses separated by 15 days. Both the EXPLORER and LUNAR trials failed to meet their primary endpoints. This may in part be due to the large amount of background therapy that patients received, potentially masking any added benefit from rituximab.

Despite the negative results, the EXPLORER and LUNAR trials were well run studies that collected large amounts of clinical and laboratory data. Much can be learned from further analysis of these datasets. I propose to analyze changes in specific cell subsets and cytokines that may be involved in SLE pathogenesis, as chosen below, in order to determine if these changes differ by treatment response group. Ultimately, I hope to use baseline cell subset and cytokine values, as well as changes in values from baseline to time of B cell depletion, to construct a prediction model for response to rituximab in SLE using EXPLORER data. This model will then be applied to the LUNAR dataset for validation. This study aims to characterize and identify the effects of rituximab on different cell subsets and cytokines and ultimately provide a model for predicting which patients are more likely to have a treatment response.

Objectives and Findings

Objective 1: Determine whether CD4+ T cells decrease after rituximab treatment and whether the degree of reduction differs by treatment response group.
Background: In patients with rheumatoid arthritis (RA), rituximab treatment has a significant effect on the T cell compartment [8-10]. In a study of 52 RA patients, the CD4+ T cell count decreased by a mean of 37% as compared to baseline at week 12, and CD4+ T cell reduction was associated with a good clinical response [9]. In SLE, small studies have shown that rituximab leads to: a decrease in CD69+CD4+ T cells [11], a decrease in memory T cells relative to naive T cells with decreased expression of CD40L [12] and inducible costimulator (ICOS) [13], and no significant change in CD4+ T cell numbers [14]. Only one study correlated changes in CD4+ T cell numbers with clinical outcome, finding no association, however only 10 patients were included in the analysis [12].
Approach: Using the same definitions as the EXPLORER study of no clinical response, partial clinical response, and major clinical response, I propose to compare the percent CD4+ T cell depletion from baseline to time of B cell depletion across the response groups in rituximab treated patients using Mann–Whitney U tests.
Hypothesis: I hypothesize that the percent decrease in CD4+ T cells will be significantly greater in patients with a clinical response.
Impact: The change in CD4+ T cells in SLE patients after treatment with rituximab has never been evaluated in a study with a sample size large enough to provide meaningful data. If successful, this aim may provide evidence for the differential response to rituximab seen across patients and identify a new parameter to monitor in rituximab treated SLE patients.
Findings: Among patients treated with rituximab, we found no significant difference in the change in CD4+ T cells between patients with a clinical response and those without a clinical response.

Objective 2: Determine whether CD8+ T cells increase after rituximab treatment and whether the degree of elevation differs by treatment response group.
Background: In a recent study of sirolimus in SLE, a baseline depletion of CD8+ T cells was noted, and a significant increase in CD8+ T cells after treatment was seen in responders [15]. In fact, the increase in CD8+ effector memory T cells predicted therapeutic response to sirolimus with an AUC value of 0.967. CD8+ T cell numbers were also found to be significantly increased during partial remission, and even further increased at complete remission, in a study of ten proliferative lupus nephritis patients [12].
Approach: Using the EXPLORER response, I propose to compare the percent CD8+ T cell increase from baseline to time of B cell depletion across the response groups in rituximab treated patients using Mann–Whitney U tests.
Hypothesis: I hypothesize that the percent increase in CD8+ T cells will be significantly greater in patients with a clinical response.
Impact: The change in CD8+ T cells in SLE patients after treatment with rituximab has never been evaluated in a study with a sample size large enough to provide meaningful data. If successful, this aim will further define a beneficial effect of rituximab treatment and lend support to the importance of CD8+ T cells in preventing lupus disease activity.
Findings: Among patients treated with rituximab, we found no significant difference in the change in CD8+ T cells between patients with a clinical response and those without a clinical response.

Objective 3: Determine the proportion of patients at time of relapse with a memory CD4+ T cell (CD4+CD45RO+) resurgence versus a memory B cell (CD19+CD27+) resurgence.
Background: Several studies have shown that, after B cell depletion with rituximab, repopulation with transitional B cells is associated with sustained clinical remission, while resurgence of memory B cells portends a poor prognosis [13, 16]. In some patients, however, relapses after rituximab treatment have been associated with a memory T cell resurgence, without repopulation of B cells [13, 17]. This phenomenon has only been evaluated in small numbers of patients, and it is unclear whether repopulation of memory B or memory T cells predominates in relapsing patients.
Approach: I propose to quantify the number of patients at relapse with a memory T cell predominate resurgence compared to the number of patients with a memory B cell predominate resurgence.
Hypothesis: I hypothesize that both will be observed in relatively equal proportions.
Impact: This may lend support to the notion of clinical and biological heterogeneity in SLE patients and may suggest a need for flow cytometric monitoring at relapse in order to provide tailored therapies based on the cell type that predominates.
Findings: Among patients treated with rituximab, we found no significant correlation between relapse and either memory CD4+ T cell (CD4+CD45RO+) resurgence or memory B cell (CD19+CD27+) resurgence.

Objective 4: Describe the change in natural killer (NK) cells (CD16+CD56+) after rituximab treatment and identify any associations with treatment response.
Background: NK cells have been evaluated in SLE patients receiving rituximab, and several studies suggest that the numbers increase after treatment, during remission, and continue to increase at relapse [12, 18-20]. The exact role that NK cells may play in SLE pathogenesis is unclear, and a description of their kinetics in relation to disease activity in a large cohort would be informative.
Approach: I propose to graphically display the trend in NK cell numbers over time for each patient by treatment response group. The mean number/percent NK cells will be assessed using Mann–Whitney U tests at each timepoint.
Hypothesis: I hypothesize that an identifiable trend in NK cells will emerge that may be in part related to treatment response.
Impact: This will add to the sparse body of literature about the change in NK cell numbers in SLE patients after rituximab treatment.
Findings: Among patients treated with rituximab, we found no significant trends related to natural killer cells (CD16+CD56+) after rituximab treatment or any association with treatment response.

Objective 5: Determine whether baseline memory B cell (CD19+CD27+) numbers and/or the ratio of memory to naïve B cells at baseline predicts treatment response.
Background: Memory B cell resurgence has been associated with relapse after rituximab treatment in SLE [13, 16], but baseline abundance of these cells has not been investigated.
Approach: I propose to compare both baseline numbers of memory B cells and the ratio of memory to naïve B cells at baseline across treatment response groups using Mann–Whitney U tests.
Hypothesis: I hypothesize that non-responders will have a higher baseline number of memory B cells and ratio of memory to naïve B cells compared to responders.
Impact: If significant, this finding could help predict which patients are more likely to respond to rituximab.
Findings: Among patients treated with rituximab, we found no significance of baseline memory B cell (CD19+CD27+) numbers or the ratio of memory to naïve B cells at predicting treatment response.

Objective 6: Determine whether the number of residual memory B cells (CD19+CD27+) after depletion differs by treatment response group.
Background: In the EXPLORER study, an ad hoc analysis that excluded patients without complete B cell depletion did not change the primary outcome [6]. However, residual memory B cells were not explicitly investigated. It is conceivable that failure to adequately deplete memory B cells impacts the clinical response to rituximab.
Approach: I propose to compare the number of residual memory B cells after rituximab depletion across treatment response groups using Mann–Whitney U tests.
Hypothesis: I hypothesize that non-responders will have significantly higher numbers of residual memory B cells after rituximab treatment.
Impact: If significant, this finding could help predict which patients are more likely to respond to rituximab.
Findings: Among patients treated with rituximab, we found no significant difference in the number of residual memory B cells (CD19+CD27+) after depletion by treatment response group.

Objective 7: Compare the mean change in serum IL-6 after rituximab treatment across treatment response groups.
Background: IL-6 is a cytokine with diverse effects on the immune system, and its levels are increased in patients with a number of inflammatory diseases [21]. IL-6 promotes the differentiation of naïve CD4+ T cells into Th17 T cells, it induces CD8+ T cells to become cytotoxic, and it aids B-cell differentiation into antibody producing cells. In SLE, serum IL-6 is elevated compared to healthy controls [22, 23], and urinary IL-6 correlates with anti-dsDNA titers and disease activity in patients with lupus nephritis [23]. IL-6 levels have been shown to predict SLE disease activity, either in combination with circulating immune complexes or serum free light chains [24, 25]. It is unknown how serum IL-6 levels change in response to rituximab treatment and whether reductions have any bearing on treatment response.
Approach: I propose to compare the change in serum IL-6 levels from baseline to the time of B cell depletion across treatment response groups using Mann–Whitney U tests.
Hypothesis: I hypothesize that IL-6 levels will decrease in all subjects, but that responders will see a significantly larger reduction.
Impact: This will be the first characterization of how rituximab treatment affects serum IL-6 levels in SLE patients.
Findings: Among patients treated with rituximab, we found no significant difference in the mean change in serum IL-6 after rituximab treatment across treatment response groups.

Objective 8: Compare the mean change in serum IL-10 after rituximab treatment across treatment response groups.
Background: IL-10 is a cytokine with primarily anti-inflammatory and immunosuppressive functions, however in SLE it is elevated and is thought to be disease-promoting. This may be due to its effects on B cells, as it promotes their survival, proliferation, activation, and differentiation into antibody-secreting cells [26, 27]. Numerous studies have shown that serum IL-10 levels are several-fold higher in SLE patients compared to healthy controls, and that serum IL-10 levels correlate with disease activity in SLE [28-32]. It is unknown how serum IL-10 levels change in response to rituximab treatment and whether reductions have any bearing on treatment response.
Approach: I propose to compare the change in serum IL-10 levels from baseline to the time of B cell depletion across treatment response groups using Mann–Whitney U tests.
Hypothesis: I hypothesize that IL-10 levels will decrease in all subjects, but that responders will see a significantly larger reduction.
Impact: This will be the first characterization of how rituximab treatment affects serum IL-10 levels in SLE patients.
Findings: Among patients treated with rituximab, we found no significant difference in the mean change in serum IL-10 after rituximab treatment across treatment response groups.

Objective 9: Compare the mean change in serum interferon-alpha after rituximab treatment across treatment response groups.
Background: Interferon-alpha is one of the major cytokines implicated in SLE pathogenesis [33]. It induces neutrophils to undergo NETosis, increases cytotoxicity of CD8+ T cells and NK cells, promotes monocytes differentiation into dendritic cells, skews the T helper cell response to Th1, enhances BAFF-induced B cell differentiation and survival, and suppresses regulatory T cell activity. In SLE, serum interferon-alpha is elevated compared to healthy controls [34], and interferon-alpha levels correlate with disease activity [34, 35]. It is unknown how serum interferon-alpha levels change in response to rituximab treatment and whether reductions have any bearing on treatment response.
Approach: I propose to compare the change in serum interferon-alpha levels from baseline to the time of B cell depletion across treatment response groups using Mann–Whitney U tests.
Hypothesis: I hypothesize that interferon-alpha levels will decrease in all subjects, but that responders will see a significantly larger reduction.
Impact: This will be the first characterization of how rituximab treatment affects serum interferon-alpha levels in SLE patients.
Findings: Among patients treated with rituximab, we found no significant difference in the mean change in serum interferon-alpha after rituximab treatment across treatment response groups.

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