Super-Enhancer Associated Five-Gene Risk Score Model Predicts Overall Survival in Multiple Myeloma Patients
Multiple myeloma (MM) is a malignant plasma cell tumor with high heterogeneity, characterized by anemia, hypercalcemia, renal failure, and lytic bone lesions. Although various powerful prognostic factors and models have been exploited, the development of more accurate prognosis and treatment for MM...
| Main Authors: | , , , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Frontiers Media S.A.
2020-12-01
|
| Series: | Frontiers in Cell and Developmental Biology |
| Subjects: | |
| Online Access: | https://www.frontiersin.org/articles/10.3389/fcell.2020.596777/full |
| _version_ | 1818646911622578176 |
|---|---|
| author | Tingting Qi Tingting Qi Tingting Qi Jian Qu Jian Qu Chao Tu Qiong Lu Qiong Lu Guohua Li Guohua Li Jiaojiao Wang Jiaojiao Wang Qiang Qu Qiang Qu |
| author_facet | Tingting Qi Tingting Qi Tingting Qi Jian Qu Jian Qu Chao Tu Qiong Lu Qiong Lu Guohua Li Guohua Li Jiaojiao Wang Jiaojiao Wang Qiang Qu Qiang Qu |
| author_sort | Tingting Qi |
| collection | DOAJ |
| description | Multiple myeloma (MM) is a malignant plasma cell tumor with high heterogeneity, characterized by anemia, hypercalcemia, renal failure, and lytic bone lesions. Although various powerful prognostic factors and models have been exploited, the development of more accurate prognosis and treatment for MM patients is still facing many challenges. Given the essential roles of super-enhancer (SE) associated genes in the tumorigenesis of MM, we tried to initially screen and identify the significant prognostic factors from SE associated genes in MM by the least absolute shrinkage and selection operator (Lasso) penalized Cox regression, univariate and multivariate Cox regression analysis using GSE24080 and GSE9782 datasets. Risk score model of five genes including CSGALNACT1, FAM53B, TAPBPL, REPIN1, and DDX11, was further constructed and the Kaplan-Meier (K-M) curves showed that the low-risk group seems to have better clinical outcome of survival compared to the high-risk group. Time-dependent receiver operating characteristic (ROC) curves presented the favorable performance of the model. An interactive nomogram consisting of the five-gene risk group and eleven clinical traits was established and identified by calibration curves. Therefore, the risk score model of SE associated five genes developed here could be used to predict the prognosis of MM patients, which may assist the clinical treatment of MM patients in the future. |
| first_indexed | 2024-12-17T00:54:10Z |
| format | Article |
| id | doaj.art-00b3ba545be14f589da39ae4d5308ed1 |
| institution | Directory Open Access Journal |
| issn | 2296-634X |
| language | English |
| last_indexed | 2024-12-17T00:54:10Z |
| publishDate | 2020-12-01 |
| publisher | Frontiers Media S.A. |
| record_format | Article |
| series | Frontiers in Cell and Developmental Biology |
| spelling | doaj.art-00b3ba545be14f589da39ae4d5308ed12022-12-21T22:09:38ZengFrontiers Media S.A.Frontiers in Cell and Developmental Biology2296-634X2020-12-01810.3389/fcell.2020.596777596777Super-Enhancer Associated Five-Gene Risk Score Model Predicts Overall Survival in Multiple Myeloma PatientsTingting Qi0Tingting Qi1Tingting Qi2Jian Qu3Jian Qu4Chao Tu5Qiong Lu6Qiong Lu7Guohua Li8Guohua Li9Jiaojiao Wang10Jiaojiao Wang11Qiang Qu12Qiang Qu13Department of Pharmacy, Xiangya Hospital, Central South University, Changsha, ChinaDepartment of Pharmacy, The Second Xiangya Hospital, Central South University, Changsha, ChinaInstitute of Clinical Pharmacy, Central South University, Changsha, ChinaDepartment of Pharmacy, The Second Xiangya Hospital, Central South University, Changsha, ChinaInstitute of Clinical Pharmacy, Central South University, Changsha, ChinaDepartment of Orthopaedics, The Second Xiangya Hospital, Central South University, Changsha, ChinaDepartment of Pharmacy, The Second Xiangya Hospital, Central South University, Changsha, ChinaInstitute of Clinical Pharmacy, Central South University, Changsha, ChinaDepartment of Pharmacy, The Second Xiangya Hospital, Central South University, Changsha, ChinaInstitute of Clinical Pharmacy, Central South University, Changsha, ChinaDepartment of Pharmacy, The Second Xiangya Hospital, Central South University, Changsha, ChinaInstitute of Clinical Pharmacy, Central South University, Changsha, ChinaDepartment of Pharmacy, Xiangya Hospital, Central South University, Changsha, ChinaInstitute for Rational and Safe Medication Practices, National Clinical Research Center for Geriatric Disorders, Xiangya Hospital, Central South University, Changsha, ChinaMultiple myeloma (MM) is a malignant plasma cell tumor with high heterogeneity, characterized by anemia, hypercalcemia, renal failure, and lytic bone lesions. Although various powerful prognostic factors and models have been exploited, the development of more accurate prognosis and treatment for MM patients is still facing many challenges. Given the essential roles of super-enhancer (SE) associated genes in the tumorigenesis of MM, we tried to initially screen and identify the significant prognostic factors from SE associated genes in MM by the least absolute shrinkage and selection operator (Lasso) penalized Cox regression, univariate and multivariate Cox regression analysis using GSE24080 and GSE9782 datasets. Risk score model of five genes including CSGALNACT1, FAM53B, TAPBPL, REPIN1, and DDX11, was further constructed and the Kaplan-Meier (K-M) curves showed that the low-risk group seems to have better clinical outcome of survival compared to the high-risk group. Time-dependent receiver operating characteristic (ROC) curves presented the favorable performance of the model. An interactive nomogram consisting of the five-gene risk group and eleven clinical traits was established and identified by calibration curves. Therefore, the risk score model of SE associated five genes developed here could be used to predict the prognosis of MM patients, which may assist the clinical treatment of MM patients in the future.https://www.frontiersin.org/articles/10.3389/fcell.2020.596777/fullmultiple myelomasuper-enhancerLASSOoverall survivalrisk score model |
| spellingShingle | Tingting Qi Tingting Qi Tingting Qi Jian Qu Jian Qu Chao Tu Qiong Lu Qiong Lu Guohua Li Guohua Li Jiaojiao Wang Jiaojiao Wang Qiang Qu Qiang Qu Super-Enhancer Associated Five-Gene Risk Score Model Predicts Overall Survival in Multiple Myeloma Patients Frontiers in Cell and Developmental Biology multiple myeloma super-enhancer LASSO overall survival risk score model |
| title | Super-Enhancer Associated Five-Gene Risk Score Model Predicts Overall Survival in Multiple Myeloma Patients |
| title_full | Super-Enhancer Associated Five-Gene Risk Score Model Predicts Overall Survival in Multiple Myeloma Patients |
| title_fullStr | Super-Enhancer Associated Five-Gene Risk Score Model Predicts Overall Survival in Multiple Myeloma Patients |
| title_full_unstemmed | Super-Enhancer Associated Five-Gene Risk Score Model Predicts Overall Survival in Multiple Myeloma Patients |
| title_short | Super-Enhancer Associated Five-Gene Risk Score Model Predicts Overall Survival in Multiple Myeloma Patients |
| title_sort | super enhancer associated five gene risk score model predicts overall survival in multiple myeloma patients |
| topic | multiple myeloma super-enhancer LASSO overall survival risk score model |
| url | https://www.frontiersin.org/articles/10.3389/fcell.2020.596777/full |
| work_keys_str_mv | AT tingtingqi superenhancerassociatedfivegeneriskscoremodelpredictsoverallsurvivalinmultiplemyelomapatients AT tingtingqi superenhancerassociatedfivegeneriskscoremodelpredictsoverallsurvivalinmultiplemyelomapatients AT tingtingqi superenhancerassociatedfivegeneriskscoremodelpredictsoverallsurvivalinmultiplemyelomapatients AT jianqu superenhancerassociatedfivegeneriskscoremodelpredictsoverallsurvivalinmultiplemyelomapatients AT jianqu superenhancerassociatedfivegeneriskscoremodelpredictsoverallsurvivalinmultiplemyelomapatients AT chaotu superenhancerassociatedfivegeneriskscoremodelpredictsoverallsurvivalinmultiplemyelomapatients AT qionglu superenhancerassociatedfivegeneriskscoremodelpredictsoverallsurvivalinmultiplemyelomapatients AT qionglu superenhancerassociatedfivegeneriskscoremodelpredictsoverallsurvivalinmultiplemyelomapatients AT guohuali superenhancerassociatedfivegeneriskscoremodelpredictsoverallsurvivalinmultiplemyelomapatients AT guohuali superenhancerassociatedfivegeneriskscoremodelpredictsoverallsurvivalinmultiplemyelomapatients AT jiaojiaowang superenhancerassociatedfivegeneriskscoremodelpredictsoverallsurvivalinmultiplemyelomapatients AT jiaojiaowang superenhancerassociatedfivegeneriskscoremodelpredictsoverallsurvivalinmultiplemyelomapatients AT qiangqu superenhancerassociatedfivegeneriskscoremodelpredictsoverallsurvivalinmultiplemyelomapatients AT qiangqu superenhancerassociatedfivegeneriskscoremodelpredictsoverallsurvivalinmultiplemyelomapatients |