title: Potential prognostic long non-coding RNA identification and their validation in predicting survival of patients with multiple myeloma.
abstract: Multiple myeloma, a typical hematological malignancy, is characterized by malignant proliferation of plasma cells. This study was to identify differently expressed long non-coding RNAs to predict the survival of patients with multiple myeloma efficiently. Gene expressing profiles of diagnosed patients with multiple myeloma, GSE24080 (559 samples) and GSE57317 (55 samples), were downloaded from Gene Expression Omnibus database. After processing, survival-related long non-coding RNAs were identified by Cox regression analysis. The prognosis of multiple myeloma patients with differently expressed long non-coding RNAs was predicted by Kaplan-Meier analysis. Meanwhile, stratified analysis was performed based on the concentrations of serum beta 2-microglobulin (S-beta 2m), albumin, and lactate dehydrogenase of multiple myeloma patients. Gene set enrichment analysis was performed to further explore the functions of identified long non-coding RNAs. A total of 176 long non-coding RNAs significantly related to the survival of multiple myeloma patients (p < 0.05) were identified. In dataset GSE24080 and GSE57317, there were 558 and 55 patients being clustered into two groups with significant differences, respectively. Stratified analysis indicated that prediction of the prognoses with these long non-coding RNAs was independent from other clinical phenotype of multiple myeloma. Gene set enrichment analysis-identified pathways of cell cycle, focal adhesion, and G2-M checkpoint were associated with these long non-coding RNAs. A total of 176 long non-coding RNAs, especially RP1-286D6.1, AC008875.2, MTMR9L, AC069360.2, and AL512791.1, were potential biomarkers to evaluate the prognosis of multiple myeloma patients. These long non-coding RNAs participated indispensably in many pathways associated to the development of multiple myeloma; however, the molecular mechanisms need to be further studied.
authors.affiliation: 1 Department of Orthopedic Surgery, People's Hospital of Three Gorges University, Yichang, China.
authors.forename: Ai-Xin
authors.initials: AX
authors.lastname: Hu
authors.affiliation: 2 PuAi Institute, Edong Healthcare Group, Huangshi Central Hospital, Huangshi, China.
authors.forename: Zhi-Yong
authors.initials: ZY
authors.lastname: Huang
authors.affiliation: 3 Department of Spinal Surgery, The Affiliated Huai'an Hospital of Xuzhou Medical University and The Second People's Hospital of Huai'an, Huai'an, China.
authors.forename: Lin
authors.initials: L
authors.lastname: Zhang
authors.affiliation: 4 Changzhou Hygiene Vocational Technology School, Changzhou, China.
authors.forename: Jian
authors.initials: J
authors.lastname: Shen
mesh_terms: D020869:Gene Expression Profiling; D006801:Humans; D053208:Kaplan-Meier Estimate; D009101:Multiple Myeloma / Q000235:genetics / Q000378:metabolism / Q000401:mortality*; D011379:Prognosis; D062085:RNA, Long Noncoding / Q000378:metabolism*
chemical_list: D062085:RNA, Long Noncoding
keywords: Long non-coding RNA; gene set enrichment analysis; multiple myeloma; prognosis marker; survival rate