ArticleAnnals of the rheumatic diseases2024
Altered serum metabolome as an indicator of paraneoplasia or concomitant cancer in patients with rheumatic disease.
Article in Annals of the rheumatic diseases, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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Who cites it
2 citing papers in PubMed, 2 citations in OpenAlex.
- Autoimmune disease patients with comorbid cancer exhibit prominent immunometabolic crosstalk.Science China. Life sciences · 2026Article
- Lipid metabolism in homeostasis and disease.Signal transduction and targeted therapy · 2026Review
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Authors and funding
13 authors at 3 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
objectivesA timely diagnosis is imperative for curing cancer. However, in patients with rheumatic musculoskeletal diseases (RMDs) or paraneoplastic syndromes, misleading symptoms frequently delay cancer diagnosis. As metabolic remodelling characterises both cancer and RMD, we analysed if a metabolic signature can indicate paraneoplasia (PN) or reveal concomitant cancer in patients with RMD.
methodsMetabolic alterations in the sera of rheumatoid arthritis (RA) patients with (n=56) or without (n=52) a history of invasive cancer were quantified by nuclear magnetic resonance analysis. Metabolites indicative of cancer were determined by multivariable regression analyses. Two independent RA and spondyloarthritis (SpA) cohorts with or without a history of invasive cancer were used for blinded validation. Samples from patients with active cancer or cancer treatment, pulmonary and lymphoid type cancers, paraneoplastic syndromes, non-invasive (NI) precancerous lesions and non-melanoma skin cancer and systemic lupus erythematosus and samples prior to the development of malignancy were used to test the model performance.
resultsBased on the concentrations of acetate, creatine, glycine, formate and the lipid ratio L1/L6, a diagnostic model yielded a high sensitivity and specificity for cancer diagnosis with AUC=0.995 in the model cohort, AUC=0.940 in the blinded RA validation cohort and AUC=0.928 in the mixed RA/SpA cohort. It was equally capable of identifying cancer in patients with PN. The model was insensitive to common demographic or clinical confounders or the presence of NI malignancy like non-melanoma skin cancer.
conclusionsThis new set of metabolic markers reliably predicts the presence of cancer in arthritis or PN patients with high sensitivity and specificity and has the potential to facilitate a rapid and correct diagnosis of malignancy.
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