Objective To investigate the genetic heterogeneity of multiple myeloma（MM） and the important regulatory role of immune cells in its pathophysiology by using bioinformatics techniques. Methods The datasets of GSE125364 and GSE72213 associated with MM were obtained from the gene expression omnibus database of National Center for Biotechnology Information，and bioinformatics and machine learning methods were used to identify the key genes for the diagnosis of MM. Pathways associated with the differentially expressed genes in MM were analyzed to calculate immune cell infiltration，and molecular biology experiments were used for validation. Results In this study，a total of 410 differentially expressed genes were obtained by the bioinformatics methods based on the gene microarray data of MM from public databases，among which 259 were downregulated and 151 were upregulated in MM patients compared with controls. The gene ontology enrichment analysis showed that the differentially expressed genes were mainly involved in the biological processes such as DNA replication，chromosome segregation，and mitosis； as for cellular localization，they were mainly enriched in chromosomal region and the spindle apparatus； as for molecular function，they were mainly enriched in single-stranded DNA helicase activity，DNA catalysis，and ATP-dependent activity. The KEGG pathway enrichment analysis showed that the main signaling pathways included cell cycle，the p53 signaling pathway，cellular senescence，and DNA replication. The GSEA analysis showed that in the control group，the genes were mainly enriched in cell cycle，DNA replication，purine metabolism，and ribosomes，while in the MM group，the genes were mainly enriched in the adipokine signaling pathway，cell adhesion molecules，ribonucleic acid polymerase，and ascorbate and aldarate metabolism pathways. Two genes，CPXM1 and UROD，were obtained for the diagnosis of MM by support vector machine-recursive feature elimination algorithm，and the immune infiltration analysis via CIBERSORTx showed that CPXM1 and UROD were associated with immune infiltration； qRT-PCR validation was performed in MM.1S cells （P<0.05）. Conclusion Bioinformatics methods can be used to effectively analyze the differentially expressed genes between MM patients and the normal control population，and the key genes CPXM1 and UROD are obtained for the diagnosis of MM and are associated with immune infiltration，which can be used as new targets for subsequent basic and clinical experimental studies on MM.