A prognostic survival model based on metabolism-related gene expression in plasma cell myeloma

• Published in: Leukemia Vol. 35; no. 11; pp. 3212 - 3222
• Main Authors: Huang, Han-ying, Wang, Yun, Wang, Wei-da, Wei, Xiao-li, Gale, Robert Peter, Li, Jin-yuan, Zhang, Qian-yi, Shu, Ling-ling, Li, Liang, Li, Juan, Lin, Huan-xin, Liang, Yang
• Format: Journal Article
• Language: English
• Published: London Nature Publishing Group UK 01.11.2021; Nature Publishing Group
• Subjects: 13/2; 13/31; 38/39; 45/41; 631/67/2327; 692/699/1541/1990/804; Aged; Antineoplastic Agents - therapeutic use; Biomarkers, Tumor - genetics; Biomarkers, Tumor - metabolism; Cancer Research; Cell metabolism; Cell survival; Cohort Studies; Confidence intervals; Critical Care Medicine; Datasets; Female; Follow-Up Studies; Gene expression; Gene Expression Regulation, Neoplastic; Genetic aspects; Health aspects; Hematology; Humans; In vitro methods and tests; Intensive; Internal Medicine; Male; Medical prognosis; Medicine; Medicine & Public Health; Metabolism; Metabolome; Multiple myeloma; Multiple Myeloma - genetics; Multiple Myeloma - metabolism; Multiple Myeloma - mortality; Multiple Myeloma - pathology; Myeloma; Nomograms; Nomography (Mathematics); Oncology; Performance prediction; Plasma cells; Predictions; Prognosis; Risk; Robustness (mathematics); Statistical analysis; Statistics; Survival; Survival Rate; Training; China
• ISSN: 0887-6924; 1476-5551; 1476-5551
• DOI: 10.1038/s41375-021-01206-4

Accurate survival prediction of persons with plasma cell myeloma (PCM) is challenging. We interrogated clinical and laboratory co-variates and RNA matrices of 1040 subjects with PCM from public datasets in the Gene Expression Omnibus database in training ( N  = 1) and validation ( N  = 2) datasets. Genes regulating plasma cell metabolism correlated with survival were identified and seven used to build a metabolic risk score using Lasso Cox regression analyses. The score had robust predictive performance with 5-year survival area under the curve (AUCs): 0.71 (95% confidence interval, 0.65, 0.76), 0.88 (0.67, 1.00) and 0.64 (0.57, 0.70). Subjects in the high‐risk training cohort (score > median) had worse 5-year survival compared with those in the low‐risk cohort (62% [55, 68%] vs. 85% [80, 90%]; p  < 0.001). This was also so for the validation cohorts. A nomogram combining metabolic risk score with Revised International Staging System (R-ISS) score increased survival prediction from an AUC = 0.63 [0.58, 0.69] to an AUC = 0.73 [0.66, 0.78]; p  = 0.015. Modelling predictions were confirmed in in vitro tests with PCM cell lines. Our metabolic risk score increases survival prediction accuracy in PCM.