Enhanced expression of FCER1G predicts positive prognosis in multiple myelomaFu, L., Cheng, Z., Dong, F., Quan, L., Cui, L., Liu, Y., Zeng, T., Huang, W., Chen, J., Pang, Y., Ye, X., Wu, G., Qian, T., Chen, Y. & Si, C., 2020, In : Journal of Breast Cancer. 11, 5, p. 1182-1194 13 p.
Research output: Contribution to journal › Article › Academic › peer-review
Background: Multiple myeloma (MM) is the second most common hematologic malignancy worldwide and does not have sufficient prognostic indicators. FCER1G (Fc fragment Of IgE receptor Ig) is located on chromosome 1q23.3 and is involved in the innate immunity. Early studies have shown that FCER1G participates in many immune-related pathways encompassing multiple cell types. Meanwhile, it is associated with many malignancies. However, the relationship between MM and FCER1G has not been studied.
Methods: In this study, we integrated nine independent gene expression omnibus (GEO) datasets and analyzed the associations of FCER1G expression and myeloma progression, ISS stage, 1q21 amplification and survival in 2296 myeloma patients and 48 healthy donors.
Results: The expression of FCER1G showed a decreasing trend with the advance of myeloma. As ISS stage and 1q21 amplification level increased, the expression of FCER1G decreased (P = 0.0012 and 0.0036, respectively). MM patients with high FCER1G expression consistently had longer EFS and OS across three large sample datasets (EFS: P = 0.0057, 0.0049, OS: P = 0.0014, 0.00065, 0.0019 and 0.0029, respectively). Meanwhile, univariate and multivariate analysis indicated that high FCER1G expression was an independent favorable prognostic factor for EFS and OS in MM patients (EFS: P = 0.006, 0.027, OS: P =0.002,0.025, respectively).
Conclusions: The expression level of FCER1G negatively correlated with myeloma progression, and high FCER1G expression may be applied as a favorable biomarker in MM patients.
|Number of pages||13|
|Journal||Journal of Breast Cancer|
|Publication status||Published - 2020|
- Multiple myeloma, FCER1G, Prognosis, Gene expression profile, Bioinformatics analysis, PLASMA-CELL LEUKEMIA, GAMMA-SUBUNIT, GENES, RECEPTOR, POLYMORPHISMS, FCGR2A, CLASSIFICATION, ASSOCIATION, ACTIVATION, INHIBITOR