Potential prognostic long non-coding RNA identification and their validation in predicting survival of patients with multiple myeloma
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 patien...
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| Format: | Article |
| Language: | English |
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SAGE Publishing
2017-04-01
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| Series: | Tumor Biology |
| Online Access: | https://doi.org/10.1177/1010428317694563 |
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| author | Ai-Xin Hu Zhi-Yong Huang Lin Zhang Jian Shen |
| author_facet | Ai-Xin Hu Zhi-Yong Huang Lin Zhang Jian Shen |
| author_sort | Ai-Xin Hu |
| collection | DOAJ |
| description | 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. |
| format | Article |
| id | doaj-art-9679d69e09424c7aaec3e18961574794 |
| institution | DOAJ |
| issn | 1423-0380 |
| language | English |
| publishDate | 2017-04-01 |
| publisher | SAGE Publishing |
| record_format | Article |
| series | Tumor Biology |
| spelling | doaj-art-9679d69e09424c7aaec3e189615747942025-08-20T02:52:27ZengSAGE PublishingTumor Biology1423-03802017-04-013910.1177/1010428317694563Potential prognostic long non-coding RNA identification and their validation in predicting survival of patients with multiple myelomaAi-Xin Hu0Zhi-Yong Huang1Lin Zhang2Jian Shen3Department of Orthopedic Surgery, People’s Hospital of Three Gorges University, Yichang, ChinaPuAi Institute, Edong Healthcare Group, Huangshi Central Hospital, Huangshi, ChinaDepartment of Spinal Surgery, The Affiliated Huai’an Hospital of Xuzhou Medical University and The Second People’s Hospital of Huai’an, Huai’an, ChinaChangzhou Hygiene Vocational Technology School, Changzhou, ChinaMultiple 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.https://doi.org/10.1177/1010428317694563 |
| spellingShingle | Ai-Xin Hu Zhi-Yong Huang Lin Zhang Jian Shen Potential prognostic long non-coding RNA identification and their validation in predicting survival of patients with multiple myeloma Tumor Biology |
| title | Potential prognostic long non-coding RNA identification and their validation in predicting survival of patients with multiple myeloma |
| title_full | Potential prognostic long non-coding RNA identification and their validation in predicting survival of patients with multiple myeloma |
| title_fullStr | Potential prognostic long non-coding RNA identification and their validation in predicting survival of patients with multiple myeloma |
| title_full_unstemmed | Potential prognostic long non-coding RNA identification and their validation in predicting survival of patients with multiple myeloma |
| title_short | Potential prognostic long non-coding RNA identification and their validation in predicting survival of patients with multiple myeloma |
| title_sort | potential prognostic long non coding rna identification and their validation in predicting survival of patients with multiple myeloma |
| url | https://doi.org/10.1177/1010428317694563 |
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