Fol. Biol. 2024, 70, 85-94
Integrating Lysosomal Genes and Immune Infiltration for Multiple Myeloma Subtyping and Prognostic Stratification
Lysosomes are crucial in the tumour immune microenvironment, which is essential for the survival and homeostasis in multiple myeloma (MM). Here, we aimed to identify lysosome-related genes for the prognosis of MM and predicted their regulatory mechanisms. Gene expression profiles of MM from the GSE2658 and GSE57317 datasets were analysed. Lysosome-related differentially expressed genes (DEGs) were identified and used for molecular subtyping of MM patients. A prognostic model was constructed using univariate Cox regression and LASSO regression analyses. The relationship between prognostic genes, immune cell types, and autophagy pathways was assessed through correlation analysis. RT-qPCR was performed to validate the expression of prognostic genes in MM cells. A total of 9,954 DEGs were identified between high and low immune score groups, with 213 intersecting with lysosomal genes. Molecular subtyping revealed two distinct MM subtypes with significant differences in immune cell types and autophagy pathway activities. Five lysosome-related DEGs (CORO1A, ELANE, PSAP, RNASE2, and SNAPIN) were identified as significant prognostic markers. The prognostic model showed moderate predictive accuracy with AUC values up to 0.723. Prognostic genes demonstrated significant correlations with various immune cell types and autophagy pathways. Additionally, CORO1A, PSAP and RNASE2 expression was up-regulated in MM cells, while ELANE and SNAPIN were down-regulated. Five lysosomal genes in MM were identified, and a new risk model for prognosis was developed using these genes. This research could lead to discovering important gene markers for the treatment and prognosis of MM.
Supplementary materials: Figure S1 and Table S1 (docx file)
Keywords
multiple myeloma, immune score, lysosome, prognostic model, autophagy.
Funding
This study was supported by a Chinese Medicine Research Fund Project of Zhejiang Province (number 2021ZB092) and the Zhejiang Province Natural Science Foundation (number LQ18H080003).
References
Copyright
This is an open-access article distributed under the terms of the Creative Commons Attribution License.