Joan Wither, MD, PhD, FRCPC
One of the major contributors to morbidity and mortality in Systemic Lupus Erythematosus is lupus nephritis (LN), which affects up to 65% of patients and which is characterized by considerable variability in its response to therapy. The heterogeneous nature of LN, together with the lack of biomarkers to predict treatment response at the time of flare, results in significant delays in escalation of therapy in patients with a poor response to conventional therapy, increasing the risk of kidney damage. Currently, up to 30% of patients with LN will develop renal impairment and 15% will eventually require renal replacement therapy or transplantation, highlighting the urgent need for better biomarkers to identify patients with a high probability of not responding to conventional therapy, allowing escalation of their therapy earlier in their disease course. This is particularly important given the availability of newer therapies that have improved efficacy for LN when added to conventional treatments.
Transcriptional profiling of renal biopsies from patients with LN suggests that high levels of tubular interferon-induced (IFN-I) gene expression are associated with poor therapeutic responses. However, given the labor intensive nature of this technique only a small number of patients were examined. We recently showed that a technique developed by our collaborator, Dr. David Brooks, that measures of IFN-I protein expression as a surrogate marker of IFN-I gene expression, using CyTOF, is an excellent surrogate marker of IFN-I gene expression in lupus. Here we propose to adapt this technique to measurement of these proteins in kidney biopsies, using Imaging Mass Cytometry. This technique can be performed on routine paraffin embedded tissue sections obtained for clinical purposes, and allows the simultaneous evaluation of up to 50 cell surface markers/proteins in a single tissue section. Since the tissue architecture is preserved, expression of IFN-I proteins can be localized to distinct tissue compartments and their proximity to various immune cells examined. Archived renal tissue from a cohort of well characterized LN patients for whom we have already determined their renal outcomes, will be used to assess the feasibility of the approach and generate preliminary data in support of the utility of IFN-I protein quantification as a prognostic biomarker for treatment responses.
Kidney disease, called lupus nephritis (LN), is frequently seen in lupus, occuring in up to 65% of patients. It is highly variable in its severity and response to therapy, with up to 30% of patients failing to respond to treatment resulting in decreased kidney function requiring dialysis or transplantation in 15%. It is well-established that induction of a complete remission after treatment is critical for preserving long-term kidney function, but predicting who will respond to treatment is currently difficult. Therefore, there is an urgent need for new tests to help physicians to identify patients with a lower probability of responding to conventional treatment so that appropriate therapy can be provided.
Recently, high levels of an inflammatory marker, called interferon (IFN)-induced genes, in the kidney biopsies from patients with LN were found to predict poor treatment responses in a small number of patients. Although these new results suggest that measurement of IFN-induced genes in kidney biopsies might be used to predict the response to therapy in LN, the technique used to measure these genes is expensive, time consuming, and requires fresh tissue samples, preventing its use as a clinical test. We have recently developed a technique to measure the levels of IFN in the blood, by examining the levels of IFN-induced proteins, rather than genes. Here we propose to adapt this technique to enable the measurement of IFN-induced proteins in kidney biopsies. The aim of our study is to measure the levels of IFN-induced proteins in the kidneys at the time of a kidney flare in patients with LN and to determine whether the levels of these molecules can be used to predict the response to treatment. The proposed study has the potential to improve kidney outcomes by identifying patients early in the disease course with a high probability of a poor prognosis, allowing initiation of a more aggressive therapy.