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Autophagy functions as a prosurvival mechanism in multiple myeloma (MM).The objective of this research was to establish an autophagy-related gene (ARG) signature for predicting the survival outcomes of MM patients with TP53 mutations.    Material and methods  Information about MM patients with TP53 mutations was downloaded from Gene Expression Omnibus (GEO) database. Cox proportional hazard regression was employed to determine the independent prognostic ARG and construct a risk signature. Time-dependent receiver-operating characteristic (t ROC) curve was used to explore the predictive accuracy of the prognostic model. A nomogram was constructed to give a more precise prediction of the probability of 5-year, 8-year and 10-year overall survival (OS). In addition, we utilized the CIBERSORT algorithm to explore the distribution difference of 22 immune-infiltrating cells.    Results  Three differentially expressed ARGs (CASP8, MAPK8, RB1CC1) were finally incorporated to construct the risk model. Area under the curve (AUC) of corresponding tROC curve for 5-year,8-year and 10-year OS were 0.735, 0.686 and 0.662, respectively. MM patients were categorized into high and low-risk group in accordance with the median threshold value (-1.724549). ARG-based risk score model was an independent prognostic element correlated with OS, giving an hazard ratio (HR) of 3.29 (95%CI 2.35-4.60, P&lt;0.001). 13 immune infiltrating cells were found to have distribution differences between the two groups.    Conclusions  We established a three-ARGs risk signature which manifested an independent prognostic factor. The nomogram was testified to perform well in forecasting the long-term survival of TP53-mutated MM patients.

Prognostic model and immune-infiltrating cell landscape based on differentially expressed autophagy-related genes in TP53-mutated multiple myeloma