Autoimmune disease patients with comorbid cancer exhibit prominent immunometabolic crosstalk

Patients with autoimmune diseases (AIDs) are at an increased risk of developing cancer; however, the immunometabolic programs that shape this comorbidity remain incompletely defined. We integrated targeted serum metabolomics with multiplex profiling of cytokines, chemokines, and immune checkpoint proteins in patients with five major AIDs-idiopathic inflammatory myopathies, rheumatoid arthritis, systemic lupus erythematosus, Sjögren's syndrome, and systemic sclerosis-with or without cancer. A total of 49 patients with AID and comorbid cancer (AID-CA), 47 patients with AID alone, and 15 healthy controls were enrolled. Compared with AID alone, AID-CA was associated with coordinated remodeling of amino acid and nucleotide metabolism, dominated by the alanine, aspartate, and glutamate pathways. Decreased L-glutamine and increased L-glutamic acid levels were consistently observed and remained significant after the false discovery rate correction. Immune profiling revealed modest but consistent differences, including higher levels of CXCL9 and Galectin-9 and lower levels of selected checkpoint molecules in AID-CA. The effects of major metabolites and immune mediators were directionally stable after adjusting for age, sex, treatment exposure, and autoimmune disease subtype. Integrative analyses revealed stronger associations between metabolites and immune mediators in AID-CA, centered on CXCL9 and Galectin-9, and linked to amino acid and pyrimidine metabolism. In ex vivo assays, perturbation of glutamine or arginine availability preferentially modulated the release of CXCL9 and Galectin-9 from peripheral blood mononuclear cells of patients with AID-CA. Together, these findings define an internally consistent immunometabolic pattern associated with cancer comorbidities in patients with AIDs. They nominated amino acid metabolism and CXCL9/Galectin-9-centered immune signaling as candidates for mechanistic investigation and biomarker development, while underscoring the need for validation in larger, longitudinal, and disease-specific cohorts.