Linares-Blanco, J. | Search bioRxiv

bioRxiv2026

A transcriptional patient map of systemic lupus erythematosus reveals disease-related multicellular immune programs conserved between blood and kidney

Systemic lupus erythematosus (SLE) shows marked clinical and molecular heterogeneity, yet patient stratification often relies on gene expression signatures lacking multicellular context. Here we construct a transcriptional patient map of SLE by analyzing 1,167 total samples (783 SLE, 384 healthy controls) across different resolutions, including single-cell and bulk blood as well as spatially resolved kidney tissue transcriptomes. Using an unsupervised approach we inferred patient-level transcriptomic immune programs from two independent single-cell RNA sequencing cohorts of peripheral blood mononuclear cells (PBMCs), capturing both differences between SLE and health as well as within-SLE heterogeneity. Specifically, we identified four conserved programs comprising two multicellular inflammatory programs driven by interferon and TNF/NFkB activity across immune cells, and two cell type-specific programs reflecting CD8 T cell cytotoxicity and a CD4 T cell naive-to-effector state. Functional analysis of these programs revealed a rewiring of both cell-to-cell interactions and task allocation across cell types during disease activation. In addition, mapping these programs onto an external longitudinal blood transcriptomic cohort predicted flare risk and identified candidate blood protein biomarkers detectable by proteomics. Finally, we showed that these blood programs were enriched in immune-infiltrated glomerular regions from kidney biopsies of individuals with lupus nephritis using spatially resolved transcriptomic data, thereby linking systemic immune programs to local tissue pathology. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=115 SRC="FIGDIR/small/721379v1_ufig1.gif" ALT="Figure 1"> View larger version (27K): org.highwire.dtl.DTLVardef@1e75f00org.highwire.dtl.DTLVardef@10e0a63org.highwire.dtl.DTLVardef@cc194forg.highwire.dtl.DTLVardef@191b4d2_HPS_FORMAT_FIGEXP M_FIG C_FIG

systems biology↗

bioRxiv2025

Transcriptomic signature reveals sensitivity to tubulin inhibitors in colon cancer

Colon cancer is the second most common cause of cancer death worldwide. Despite advances in the development of new molecular strategies for stratifying patients with colon cancer, many of these patients do not respond adequately to the standard of care. While previous studies have focused on the development of prognostic gene expression signatures, the exploration of predictive signatures to inform treatment decisions remains incomplete. In this study, we leveraged public gene expression datasets to design and experimentally validate a 37-gene expression signature for prognosis in colon cancer patients. We obtained a C-index of 0.732 (0.610-0.853) in four independent studies. Specifically, we discovered that the signature is associated with the mitotic phase of the cell cycle. Furthermore, the signature identified a population of colon cancer patients sensitive to tubulin inhibitor drugs. In particular, we validated in vitro and in vivo the efficacy of paclitaxel, a commonly used tubulin inhibitor in breast cancer treatment, in patient-derived preclinical models. These results highlight the importance of incorporating gene expression signatures to identify new therapeutic options for colon cancer treatment. Furthermore, the identification of alternative treatment options with potentially improved efficacy holds promise for the development of new clinical trials, and reshapes the biomarker-based treatment strategy for second line and refractory colon cancer patients.

cancer biology↗