Abstract
Multiple myeloma is a heterogeneous plasma cell malignancy that remains incurable because of the tendency of relapse for most patients. Survival outcomes may vary widely due to patient and disease variables; therefore, it is necessary to establish a more accurate prognostic model to improve prognostic precision and guide clinical therapy. Here, we developed a risk score model based on myeloma gene expression profiles from three independent datasets: GSE6477, GSE13591, and GSE24080. In this model, highly survival-associated five genes, including EPAS1, ERC2, PRC1, CSGALNACT1, and CCND1, are selected by using the least absolute shrinkage and selection operator (Lasso) regression and univariate and multivariate Cox regression analyses. At last, we analyzed three validation datasets (including GSE2658, GSE136337, and MMRF datasets) to examine the prognostic efficacy of this model by dividing patients into high-risk and low-risk groups based on the median risk score. The results indicated that the survival of patients in low-risk group was greatly prolonged compared with their counterparts in the high-risk group. Therefore, the five-gene risk score model could increase the accuracy of risk stratification and provide effective prediction for the prognosis of patients and instruction for individualized clinical treatment.
Highlights
Multiple myeloma (MM) is a heterogeneous plasma cell malignancy, which is the second most common hematological malignancy in the world (Kazandjian, 2016)
A total of 304 differentially expressed genes (DEGs) were identified with the cutoffs of |log fold change| > 1 and Benjamini–Hochberg–adjusted p < 0.05, among which, 90 genes were upregulated and 214 genes were downregulated, as shown in the volcano plot (Supplementary Figure S1)
The final risk score can be acquired by multiplying the expression of each gene with its corresponding coefficient and adding them together; we used the median of the risk score as the cut-off value to divide the high-risk and lowrisk groups
Summary
Multiple myeloma (MM) is a heterogeneous plasma cell malignancy, which is the second most common hematological malignancy in the world (Kazandjian, 2016). There were 16,500 new cases and 10,300 deaths of MM in China in 2016; the morbidity and mortality rates increased with age, and older people were at higher risk of MM (Gerecke et al, 2016; Liu et al, 2019). The International Staging System (ISS) is a widely used system for the stratification of MM patients based on easy-to-apply variables (serum beta2-microglobulin and serum albumin) (Greipp et al, 2005). In 2015, the International Myeloma Working Group (IMWG) developed the revised international staging system (R-ISS); it classifies patients into three risk groups by combining the ISS with high-risk cytogenetic abnormalities (CA) [del (17p), t (4; 14) (p16; q32), or t (14; 16) (q32; q23)] and serum lactate dehydrogenase (LDH) (Palumbo et al, 2015).
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call
