Table_2_Development and Validation of a 9-Gene Prognostic Signature in Patients With Multiple Myeloma.docx (14.7 kB)

Table_2_Development and Validation of a 9-Gene Prognostic Signature in Patients With Multiple Myeloma.docx

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posted on 08.01.2019, 04:36 by Xiao-Ping Liu, Xiao-Hong Yin, Xiang-Yu Meng, Xin-Hui Yan, Fan Wang, Li He

Background: Multiple myeloma (MM) is one of the most common types of hematological malignance, and the prognosis of MM patients remains poor.

Objective: To identify and validate a genetic prognostic signature in patients with MM.

Methods: Co-expression network was constructed to identify hub genes related with International Staging System (ISS) stage of MM. Functional analysis of hub genes was conducted. Univariate Cox proportional hazard regression analysis was conducted to identify genes correlated with the overall survival (OS) of MM patients. Least absolute shrinkage and selection operator (LASSO) penalized Cox proportional hazards regression model was used to minimize overfitting and construct a prognostic signature. The prognostic value of the signature was validated in the test set and an independent validation cohort.

Results: A total of 758 hub genes correlated with ISS stage of MM patients were identified, and these hub genes were mainly enriched in several GO terms and KEGG pathways involved in cell proliferation and immune response. Nine hub genes (HLA-DPB1, TOP2A, FABP5, CYP1B1, IGHM, FANCI, LYZ, HMGN5, and BEND6) with non-zero coefficients in the LASSO Cox regression model were used to build a 9-gene prognostic signature. Relapsed MM and ISS stage III MM was associated with high risk score calculated based on the signature. Patients in the 9-gene signature low risk group was significantly associated with better clinical outcome than those in the 9-gene signature high risk group in the training set, test, and validation set.

Conclusions: We developed a 9-gene prognostic signature that might be an independent prognostic factor in patients with MM.

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