Prognostic model and immune-infiltrating cell landscape based on differentially expressed autophagy-related genes in TP53-mutated multiple myeloma
Introduction Autophagy functions as a prosurvival mechanism in multiple myeloma (MM). The objective of this research was to establish an autophagy-related gene (ARG) signature for predicting the survival outcomes of MM patients with TP53 mutations. Material and methods Information about MM patients...
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| Language: | English |
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Termedia Publishing House
2021-07-01
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| Series: | Archives of Medical Science |
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| Online Access: | https://www.archivesofmedicalscience.com/Prognostic-model-and-immune-infiltrating-cell-landscape-based-on-differentially-expressed,140293,0,2.html |
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| author | Yan-Hua Zheng Hong-Yuan Shen Xiang Chen Juan Feng Guang-Xun Gao |
| author_facet | Yan-Hua Zheng Hong-Yuan Shen Xiang Chen Juan Feng Guang-Xun Gao |
| author_sort | Yan-Hua Zheng |
| collection | DOAJ |
| description | Introduction
Autophagy functions as a prosurvival mechanism in multiple myeloma (MM). The objective of this research was to establish an autophagy-related gene (ARG) signature for predicting the survival outcomes of MM patients with TP53 mutations.
Material and methods
Information about MM patients with TP53 mutations was downloaded from the Gene Expression Omnibus (GEO) database. Cox proportional hazard regression was employed to determine the independent prognostic ARG and construct a risk signature. Time-dependent receiver-operating characteristic (tROC) curve analysis was used to explore the predictive accuracy of the prognostic model. A nomogram was constructed to give a more precise prediction of the probability of 5-year, 8-year and 10-year overall survival (OS). In addition, we used the CIBERSORT algorithm to explore the distribution difference of 22 immune-infiltrating cells.
Results
Three differentially expressed ARGs (CASP8, MAPK8, RB1CC1) were finally incorporated to construct the risk model. Area under the curve (AUC) values of the corresponding tROC curve for 5-year, 8-year and 10-year OS were 0.735, 0.686 and 0.662, respectively. Multiple myeloma patients were categorized into high and low-risk groups in accordance with the median threshold value (–1.724549). An ARG-based risk score model was an independent prognostic element correlated with OS, giving an hazard ratio (HR) of 3.29 (95% CI 2.35–4.60, p < 0.001). Thirteen immune infiltrating cells were found to have distribution differences between the two groups.
Conclusions
We established a three-ARG risk signature which manifested an independent prognostic factor. The nomogram was testified to perform well in forecasting the long-term survival of TP53-mutated MM patients. |
| format | Article |
| id | doaj-art-6ad9657f24564fd5aefcd319d50ae1fa |
| institution | Kabale University |
| issn | 1734-1922 1896-9151 |
| language | English |
| publishDate | 2021-07-01 |
| publisher | Termedia Publishing House |
| record_format | Article |
| series | Archives of Medical Science |
| spelling | doaj-art-6ad9657f24564fd5aefcd319d50ae1fa2025-01-27T10:44:31ZengTermedia Publishing HouseArchives of Medical Science1734-19221896-91512021-07-012051619163010.5114/aoms/140293140293Prognostic model and immune-infiltrating cell landscape based on differentially expressed autophagy-related genes in TP53-mutated multiple myelomaYan-Hua Zheng0https://orcid.org/0000-0002-7527-8248Hong-Yuan Shen1Xiang Chen2Juan Feng3Guang-Xun Gao4Department of Hematology, Xijing Hospital, Fourth Military Medical University (Air Force Medical University), Xi’an, Shaanxi, ChinaDepartment of Hematology, Xijing Hospital, Fourth Military Medical University (Air Force Medical University), Xi’an, Shaanxi, ChinaDepartment of Pharmacy, Daping Hospital, Third Military Medical University, Chongqing, ChinaDepartment of Hematology, Xijing Hospital, Fourth Military Medical University (Air Force Medical University), Xi’an, Shaanxi, ChinaDepartment of Hematology, Xijing Hospital, Fourth Military Medical University (Air Force Medical University), Xi’an, Shaanxi, ChinaIntroduction Autophagy functions as a prosurvival mechanism in multiple myeloma (MM). The objective of this research was to establish an autophagy-related gene (ARG) signature for predicting the survival outcomes of MM patients with TP53 mutations. Material and methods Information about MM patients with TP53 mutations was downloaded from the Gene Expression Omnibus (GEO) database. Cox proportional hazard regression was employed to determine the independent prognostic ARG and construct a risk signature. Time-dependent receiver-operating characteristic (tROC) curve analysis was used to explore the predictive accuracy of the prognostic model. A nomogram was constructed to give a more precise prediction of the probability of 5-year, 8-year and 10-year overall survival (OS). In addition, we used the CIBERSORT algorithm to explore the distribution difference of 22 immune-infiltrating cells. Results Three differentially expressed ARGs (CASP8, MAPK8, RB1CC1) were finally incorporated to construct the risk model. Area under the curve (AUC) values of the corresponding tROC curve for 5-year, 8-year and 10-year OS were 0.735, 0.686 and 0.662, respectively. Multiple myeloma patients were categorized into high and low-risk groups in accordance with the median threshold value (–1.724549). An ARG-based risk score model was an independent prognostic element correlated with OS, giving an hazard ratio (HR) of 3.29 (95% CI 2.35–4.60, p < 0.001). Thirteen immune infiltrating cells were found to have distribution differences between the two groups. Conclusions We established a three-ARG risk signature which manifested an independent prognostic factor. The nomogram was testified to perform well in forecasting the long-term survival of TP53-mutated MM patients.https://www.archivesofmedicalscience.com/Prognostic-model-and-immune-infiltrating-cell-landscape-based-on-differentially-expressed,140293,0,2.htmlmultiple myelomaautophagyprognosisrisk signaturetp53 mutationimmune-infiltrating cell |
| spellingShingle | Yan-Hua Zheng Hong-Yuan Shen Xiang Chen Juan Feng Guang-Xun Gao Prognostic model and immune-infiltrating cell landscape based on differentially expressed autophagy-related genes in TP53-mutated multiple myeloma Archives of Medical Science multiple myeloma autophagy prognosis risk signature tp53 mutation immune-infiltrating cell |
| title | Prognostic model and immune-infiltrating cell landscape based on differentially expressed autophagy-related genes in TP53-mutated multiple myeloma |
| title_full | Prognostic model and immune-infiltrating cell landscape based on differentially expressed autophagy-related genes in TP53-mutated multiple myeloma |
| title_fullStr | Prognostic model and immune-infiltrating cell landscape based on differentially expressed autophagy-related genes in TP53-mutated multiple myeloma |
| title_full_unstemmed | Prognostic model and immune-infiltrating cell landscape based on differentially expressed autophagy-related genes in TP53-mutated multiple myeloma |
| title_short | Prognostic model and immune-infiltrating cell landscape based on differentially expressed autophagy-related genes in TP53-mutated multiple myeloma |
| title_sort | prognostic model and immune infiltrating cell landscape based on differentially expressed autophagy related genes in tp53 mutated multiple myeloma |
| topic | multiple myeloma autophagy prognosis risk signature tp53 mutation immune-infiltrating cell |
| url | https://www.archivesofmedicalscience.com/Prognostic-model-and-immune-infiltrating-cell-landscape-based-on-differentially-expressed,140293,0,2.html |
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