A novel prognostic model based on pyroptosis-related genes for multiple myeloma

Abstract

Abstract Background: Multiple myeloma (MM) is an incurable, relapse-prone disease with apparent prognostic heterogeneity. At present, the risk stratification of myeloma is still incomplete. Pyroptosis, a type of programmed cell death, has been shown to regulate tumor growth, and may have potential prognostic value. However, the role of pyroptosis-related genes (PRGs) in MM remains undetermined. The aim of this study was to to identify potential prognostic biomarkers and construct a predictive model related to PRGs. Methods: Sequencing and clinical data were obtained from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) database. Non-negative matrix factorization (NMF) was performed to identify molecular subtypes screening. LASSO regression was used to screen for prognostic markers. Maxstat package was utilized to calculate the optimal cutoff value for the risk score's ability. Patients were then divided into high/low risk groups depending on the cutoff value, and survival curves were plotted using the Kaplan-Meier (K-M) method. The nomogram and a calibration curve of the multi-factor model was established using the rms package. Results: A total of 33 PRGs were extracted from TCGA database underlying which 4 MM molecular subtypes were defined. Patients in cluster 1 had poorer survival than those in cluster 2 (p = 0.035), and the infiltration degree of many immune cells was the opposite in these two clusters. A total of 9 PRGs were screened out as prognostic markers, and the risk score consisting of which had the best predictive ability of 3-year survival (AUC=0.658). Patients in the high-risk group have worse survival than those in the low-risk group (p ＜ 0.0001), consisting of the results verified by GSE2658 dataset. The nomogram constructed by gender, age, ISS stage and risk score had the better prognostic predictive performance with a c-index of 0.721. Conclusions: Our model could enhance the predictive ability of ISS staging and give a reference for clinical decision-making. The new prognostic pyroptosis-related markers in MM screened out by us may facilitate the development of novel risk stratification for MM. Clinical trial registration: Not applicable.