Altered serum metabolome as an indicator of paraneoplasia or concomitant cancer in patients with rheumatic disease - Gente, Karolina; Feißt, Manuel; Marx, Dorothea; Klika, Karel D.; Christopoulos, Petros; Graf, Jürgen; Will, Julia; Luft, Thomas; Hassel, Jessica C.; Müller-Tidow, Carsten; Carvalho, Rui A.; Lorenz, Hanns-Martin; et al. (Annals of the rheumatic diseases, 2024)
Objectives A 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. - Methods Metabolic 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. - Results Based 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. - Conclusions This 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.