Hypoxia–Immune-Related Gene SLC19A1 Serves as a Potential Biomarker for Prognosis in Multiple Myeloma

• Published in: Frontiers in immunology Vol. 13; p. 843369
• Main Authors: Li, Wenjin, Yuan, Peng, Liu, Weiqin, Xiao, Lichan, Xu, Chun, Mo, Qiuyu, Xu, Shujuan, He, Yuchan, Jiang, Duanfeng, Wang, Xiaotao
• Format: Journal Article
• Language: English
• Published: Frontiers Media S.A 25.07.2022
• Subjects: hypoxia; immune; Immunology; multiple myeloma; prognosis; SLC19A1
• ISSN: 1664-3224; 1664-3224
• DOI: 10.3389/fimmu.2022.843369

Multiple myeloma (MM) remains an incurable malignant tumor of plasma cells. Increasing evidence has reported that hypoxia and immune status contribute to the progression of MM. In this research, the prognostic value of the hypoxia-immune-related gene SLC19A1 in MM was evaluated by bioinformatics analysis.BackgroundMultiple myeloma (MM) remains an incurable malignant tumor of plasma cells. Increasing evidence has reported that hypoxia and immune status contribute to the progression of MM. In this research, the prognostic value of the hypoxia-immune-related gene SLC19A1 in MM was evaluated by bioinformatics analysis.RNA-sequencing (RNA-seq) data along with clinical information on MM were downloaded from the Gene Expression Omnibus (GEO) database. Consistent clustering analysis and ESTIMATE algorithms were performed to establish the MM sample subgroups related to hypoxia and immune status, respectively, based on the GSE24080 dataset. The differentially expressed analysis was performed to identify the hypoxia-immune-related genes. Subsequently, a hypoxia-immune-gene risk signature for MM patients was constructed by univariate and multivariate Cox regression analyses, which was also verified in the GSE4581 dataset. Furthermore, the mRNA expression of SLC19A1 was determined using qRT-PCR in 19 MM patients, and the correlations between the genetic expression of SLC19A1 and clinical features were further analyzed.MethodRNA-sequencing (RNA-seq) data along with clinical information on MM were downloaded from the Gene Expression Omnibus (GEO) database. Consistent clustering analysis and ESTIMATE algorithms were performed to establish the MM sample subgroups related to hypoxia and immune status, respectively, based on the GSE24080 dataset. The differentially expressed analysis was performed to identify the hypoxia-immune-related genes. Subsequently, a hypoxia-immune-gene risk signature for MM patients was constructed by univariate and multivariate Cox regression analyses, which was also verified in the GSE4581 dataset. Furthermore, the mRNA expression of SLC19A1 was determined using qRT-PCR in 19 MM patients, and the correlations between the genetic expression of SLC19A1 and clinical features were further analyzed.A total of 47 genes were identified as hypoxia-immune-related genes for MM. Among these genes, SLC19A1 was screened to construct a risk score model that had better predictive power for MM. The constructed prognostic signature based on SLC19A1 was verified in the GSE4581 dataset. All independent prognostic factors (age, β2-microglobulin, LDH, albumin, MRI, and gene risk score) were used to develop a nomogram that showed a better performance for predicting the survival probability of MM patients for 1-5 years. Furthermore, SLC19A1 was highly expressed in newly diagnosed and relapsed MM patients, and high expression of SLC19A1 is correlated with higher bone marrow aspiration plasma cells and β2-microglobulin levels in MM patients.ResultA total of 47 genes were identified as hypoxia-immune-related genes for MM. Among these genes, SLC19A1 was screened to construct a risk score model that had better predictive power for MM. The constructed prognostic signature based on SLC19A1 was verified in the GSE4581 dataset. All independent prognostic factors (age, β2-microglobulin, LDH, albumin, MRI, and gene risk score) were used to develop a nomogram that showed a better performance for predicting the survival probability of MM patients for 1-5 years. Furthermore, SLC19A1 was highly expressed in newly diagnosed and relapsed MM patients, and high expression of SLC19A1 is correlated with higher bone marrow aspiration plasma cells and β2-microglobulin levels in MM patients.In conclusion, our results suggest that SLC19A1 is aberrantly expressed in MM and highly expressed SLC19A1 might be a biomarker correlated with inferior prognosis. More importantly, we identified SLC19A1 as a hypoxia-immune-related gene in MM. Future functional and mechanistic studies will further clarify the roles of SLC19A1 in MM.ConclusionIn conclusion, our results suggest that SLC19A1 is aberrantly expressed in MM and highly expressed SLC19A1 might be a biomarker correlated with inferior prognosis. More importantly, we identified SLC19A1 as a hypoxia-immune-related gene in MM. Future functional and mechanistic studies will further clarify the roles of SLC19A1 in MM.