Tumor Biology

, Volume 37, Issue 12, pp 15967–15975 | Cite as

A new ten-gene risk fraction model serving as prognostic indicator for clinical outcome of multiple myeloma

Original Article


Multiple myeloma (MM) is a kind of aggressive tumor prevalent with high heterogeneity. Abnormal expression of certain genes may lead to the occurrence and development of MM. Nowadays, it is not commonly seen in clinical research to predict the prognostic circumstances of patients with MM by multiple gene expression profiling method. Identification of potential genes in prognostic process could be beneficial for clinical management of MM. Therefore, we aimed to build a risk fraction model to screen out the prognostic indicator for clinical outcome of MM. Microarray data were downloaded from the Genome Expression Omnibus (GEO) datasets with accession numbers GSE24080 and GSE57317. A total of 279 samples were selected out randomly. Besides, a risk formula was constructed and verified in the dataset. Time-dependent receiver operating characteristic (ROC) curve was applied in evaluating the accurate prognostic conditions of patients. Finally, a ten genes model in the training dataset was found to be closely related to the survival condition of MM patients. Patients with MM were divided into two groups, high-risk and low-risk, by the expression of these ten genes, and significant statistical difference was found between the two groups. Furthermore, the result of multivariate cox regression and stratified analysis indicated that this model was independent of other clinical phenotypes. ROC curves also showed its feasibility to predict the survival status of MM patients. Our results demonstrated that the fraction risk model constructed by the selected ten genes could be used to predict survival status of multiple myeloma patients, which could also help in improvement of prognostic and therapeutic tool of MM.


Microarray expression profiling Genes Multiple myeloma Survival rates Prognostic indicator 

Supplementary material

13277_2016_5449_MOESM1_ESM.doc (35 kb)
Supplement Table 1 (DOC 35 kb)


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Copyright information

© International Society of Oncology and BioMarkers (ISOBM) 2016

Authors and Affiliations

  1. 1.The Department of Orthopedic SurgeryPeople’s Hospital of Three Gorges UniversityYiChangChina
  2. 2.PuAi Institute, E Dong Healthcare GroupThe Central Hospital of HuangshiHuangshiChina
  3. 3.Department of Pathology, Shiyan Taihe HospitalHubei University of MedicineShiyan CityChina
  4. 4.Department of Clinical Laboratory Center, Central Hospital of Enshi Autonomous PrefectureEnshi Clinical College of Wuhan UniversityEnshiChina
  5. 5.Department of EmergencyThe Affiliated Huai’an Hospital of Xuzhou Medical College and The Second People’s Hospital of Huai’anHuai’anChina
  6. 6.Department of Hematology, Huai’an First People’s HospitalNanjing Medical UniversityHuai’anChina

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