ReviewInternational journal of molecular sciences2026
Redefining Difficult-to-Treat Systemic Lupus Erythematosus: Biomarkers of Molecular Refractoriness Beyond Clinical Failure.
Review in International journal of molecular sciences, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
2 citing papers in PubMed.
- Chimeric Antigen Receptor T-cell (CAR-T) Therapy in Autoimmune Diseases: A Narrative Review.Cureus · 2026Review
- Mapping organ-associated autoantigenic landscapes in systemic lupus erythematosus.Frontiers in immunology · 2026Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Difficult-to-treat systemic lupus erythematosus (D2T-SLE) remains a major unmet challenge in contemporary lupus care, yet it continues to be defined predominantly by clinical non-response rather than underlying biology. Current biomarkers largely quantify inflammatory burden, immune complex activity, or organ damage and do not reliably capture persistent activation of pathogenic pathways under therapy. Emerging multi-omics, single-cell, and longitudinal studies suggest that, in a subset of patients, apparent treatment failure may reflect incomplete attenuation of dominant immune circuits rather than uniformly elevated inflammation. We propose molecular refractoriness in systemic lupus erythematosus (SLE) as sustained, pathway-level immune activity despite apparently adequate, mechanism-directed therapy. We outline the major immune programs implicated in this process-including interferon-enriched, B-cell/plasmablast-associated, neutrophil extracellular trap (NET)-related, cytotoxic T-cell, and cytokine-associated states-and discuss their relevance for biomarker development and precision trial design. Importantly, we emphasize that interferon gene signatures (IGS) should be interpreted as context-dependent and non-specific markers of interferon responsiveness, reflecting combined activity of type I, II, and III interferons, and functioning primarily as predictive rather than mechanistic biomarkers. We further highlight critical limitations of a purely endotype-based model, including the need to distinguish true molecular refractoriness from damage-dominant and pseudo-refractory states, as well as the emerging role of immune-reset strategies such as cluster of differentiation 19 (CD19)-directed chimeric antigen receptor T-cell (CAR-T) therapy, which may overcome refractoriness independently of specific pathway dominance. These observations suggest that difficult-to-treat SLE encompasses biologically heterogeneous states that may not be fully captured by pathway-resolved stratification alone. Reframing D2T-SLE as a biologically heterogeneous state of incomplete immune attenuation may help bridge the gap between clinical treatment failure and mechanism-informed precision medicine in systemic lupus erythematosus.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.