Shared Immune and Epigenetic Pathways in Systemic Lupus Erythematosus and Melanoma Immunotherapy: A Cross-Disease Analysis with Prognostic and Therapeutic Implications

  1. Basma Shabana
  2. Nouraldeen Ali Ramadan
  3. Manar Mosad Marey
  4. Mervat Mohamed Shaban

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Abstract

Systemic lupus erythematosus (SLE) and melanoma both involve dysregulated immune pathways, yet their molecular convergence remains poorly understood. We performed a cross-disease transcriptomic analysis of melanoma (GSE168204) and SLE (GSE211700) datasets to identify shared signatures of immune activation and immune checkpoint blockade (ICB) response. Differential expression analysis revealed two distinct signatures: (i) an immune signature’s upregulated in melanoma responders and SLE (n = 147 genes), enriched in interferon signaling and epigenetic regulators such as ASF1B and EZH2 [4, 7, 52]; and (ii) a cell cycle signature’s upregulated in melanoma non-responders and SLE (n = 157 genes), dominated by CDK1 and CCNB1 [39]. Pathway enrichment and protein-protein interaction analyses confirmed that immune activation and epigenetic remodeling drive convergence between SLE and melanoma responders, while cell cycle upregulation is specific to ICB resistance [13, 53]. Validation in independent datasets (GSE91061, GSE261866) supported the immune signature’s relevance (AUC = 0.780, p = 0.0456) and the cell cycle signature’s specificity to melanoma (p = 0.2414 in SLE) [17, 18].In TCGA-SKCM survival analysis, the cell cycle signature demonstrated strong prognostic value, predicting dramatically worse overall survival (OS HR = 15.634, 95% CI: 1.898 - 128.761, p = 0.011) and progression-free survival (PFS HR = 8.484, 95% CI: 1.420 - 50.688, p = 0.019). The immune signature showed protective trends for both OS (HR = 0.259, p = 0.121) and PFS (HR = 0.656, p = 0.585), while a composite score integrating both signatures achieved significant prognostic utility (OS HR = 0.141, p = 0.004; PFS HR = 0.324, p = 0.053) [40]. Connectivity Map analysis identified mTOR inhibitors, proteasome inhibitors, HDAC inhibitors, and statins as candidate therapeutics targeting these pathways [45, 50]. Limitations include reliance on transcriptomic data, moderate biomarker performance (AUC = 0.6567 - 0.780), and lack of functional validation. Future studies should validate these signatures’ in ICB-treated cohorts, integrate multi-omics, and test proposed therapeutics preclinically. Overall, this cross-disease analysis highlights immune-epigenetic convergence linking SLE and melanoma, with implications for biomarker development and therapeutic repurposing [6, 12].

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  1. PREreview

    This Zenodo record is a permanently preserved version of a PREreview. You can view the complete PREreview at https://prereview.org/reviews/17112855.

    Write a short summary of the research's main findings and how this work has moved the field forward.

    This preprint analyzes transcriptomic data from systemic lupus erythematosus (SLE) and melanoma patients to uncover shared immune and epigenetic pathways. Key findings include an "immune signature" (147 genes, enriched in interferon signaling and epigenetic regulators like ASF1B and EZH2) upregulated in SLE and melanoma responders to immune checkpoint blockade (ICB), and a "cell cycle signature" (157 genes, dominated by CDK1 and CCNB1) linked to ICB resistance in melanoma non-responders, with partial overlap in SLE. Validation in independent datasets confirmed the immune signature's relevance (AUC=0.780 in SLE) and the cell cycle signature's specificity to melanoma. In TCGA-SKCM, the cell cycle signature strongly predicted worse survival (OS HR=15.634, p=0.011; PFS HR=8.484, p=0.019), while a composite score improved prognostic utility (OS HR=0.141, p=0.004). Connectivity Map analysis proposed repurposed drugs like mTOR inhibitors, proteasome inhibitors, HDAC inhibitors, and statins. This work advances the field by revealing molecular convergence between autoimmunity and cancer immunotherapy, offering novel biomarkers for ICB response and survival in melanoma, and suggesting therapeutic repurposing opportunities to target shared pathways, potentially bridging SLE and oncology research.

    Major issues

    • List significant concerns about the research, if there are any.

    • The research relied on transcriptomic data without functional or experimental validation, limiting causal inferences about the identified signatures and proposed mechanisms.

    • Also the sample sizes is small in primary datasets (e.g., GSE211700: n=30 for SLE; GSE168204: unclear after filtering), which may reduce statistical power and generalizability.

    • They also used bulk RNA-seq, which lacks cell-type resolution and could confound immune vs. tumor signals in melanoma.

    • Moderate biomarker performance (AUCs 0.6567–0.780), suggesting limited clinical utility without further refinement.

    Minor issues

    • List concerns that would improve the overall flow or clarity but are not critical to the understanding and conclusions of the research.

    • Numerous typos and grammatical errors (e.g., "pipline" for "pipeline", "differential expressied" for "differentially expressed", "pervious" for "previous"), which affect readability.

    • Inconsistent referencing and incomplete supplements (e.g., full DEG lists referenced to a prior preprint but not included here).

    • Limited discussion of confounders (e.g., age, sex, treatments) in survival analyses.

    • The abstract and methods sections were overly dense , which could benefit from clearer subheadings or flow diagrams for better accessibility.

    Competing interests

    The authors declare that they have no competing interests.

  2. Version published to 10.1101/2025.08.19.671053 on bioRxiv