Immunologic Changes over Time in Repeat Kidney Biopsies from the AURORA Studies of Voclosporin in Lupus Nephritis
Bibliographic record
Abstract
Background: The AURORA 1 and 2 studies investigated the use of voclosporin (VCS) plus standard-of-care (SOC) for the treatment of lupus nephritis (LN). All patients underwent a kidney biopsy for enrollment (Bx1), and a subset of patients elected to undergo a second biopsy (Bx2) to assess how histology of the kidney changes in response to treatment. Here we have used multiplex immunofluorescence (mIF) to investigate changes in the immunologic landscape of the kidney in response to immunosuppression using these paired biopsies. Methods: Formalin-fixed paraffin-embedded tissue sections were stained with MILAN technology with a 10-marker panel. Sequential acquisitions for each biopsy were registered, and autofluorescence subtracted. Dedicated ImageJ-based pipelines were used to measure total biopsy areas and immunopositive markers and/or to count cells and related positivity for markers of interest. Results: A total of 27 paired samples were available for mIF (17 and 10 from VCS- and SOC-treated patients, respectively). CD34 and Ki67 were significantly overexpressed in Bx2 compared to Bx1 (Table 1). Within each treatment group, there was a trend toward upregulation of CD34; the differences were not statistically significant (adjusted p-values of 0.07 [VCS] and 0.12 [SOC], respectively). Conclusion: CD34 and Ki67, which have been implicated in tissue regeneration and healing in glomerulonephritides, showed significantly higher expression in repeat biopsies of patients with LN treated with immunosuppression during the AURORA trials. The lack of difference within each treatment group may indicate a lack of concordance between clinical response and immunological landscape but may also be reflective of the small sample size. The potential utility of CD34 and Ki67 as biomarkers of response requires further investigation. Funding: Commercial Support - Aurinia Pharmaceuticals Inc.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".