An original aneuploidy-related gene model for predicting lung adenocarcinoma survival and guiding therapy
Abstract Aneuploidy is a hallmark of cancers, but the role of aneuploidy-related genes in lung adenocarcinoma (LUAD) and their prognostic value remain elusive. Gene expression and copy number variation (CNV) data were enrolled from TCGA and GEO database. Consistency clustering analysis was performed...
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| Format: | Article |
| Language: | English |
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Nature Portfolio
2024-04-01
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| Series: | Scientific Reports |
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| Online Access: | https://doi.org/10.1038/s41598-024-58020-y |
| _version_ | 1797219904828473344 |
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| author | Yalei Zhang Dongmei Li |
| author_facet | Yalei Zhang Dongmei Li |
| author_sort | Yalei Zhang |
| collection | DOAJ |
| description | Abstract Aneuploidy is a hallmark of cancers, but the role of aneuploidy-related genes in lung adenocarcinoma (LUAD) and their prognostic value remain elusive. Gene expression and copy number variation (CNV) data were enrolled from TCGA and GEO database. Consistency clustering analysis was performed for molecular cluster. Tumor microenvironment was assessed by the xCell and ESTIMATE algorithm. Limma package was used for selecting differentially expressed genes (DEGs). LASSO and stepwise multivariate Cox regression analysis were used to establish an aneuploidy-related riskscore (ARS) signature. GDSC database was conducted to predict drug sensitivity. A nomogram was designed by rms R package. TCGA-LUAD patients were stratified into 3 clusters based on CNV data. The C1 cluster displayed the optimal survival advantage and highest inflammatory infiltration. Based on integrated intersecting DEGs, we constructed a 6-gene ARS model, which showed effective prediction for patient’s survival. Drug sensitivity test predicted possible sensitive drugs in two risk groups. Additionally, the nomogram exhibited great predictive clinical treatment benefits. We established a 6-gene aneuploidy-related signature that could effectively predict the survival and therapy for LUAD patients. Additionally, the ARS model and nomogram could offer guidance for the preoperative estimation and postoperative therapy of LUAD. |
| first_indexed | 2024-04-24T12:41:04Z |
| format | Article |
| id | doaj.art-fa7f5792ea7f4b0e835c1f66f6a03823 |
| institution | Directory Open Access Journal |
| issn | 2045-2322 |
| language | English |
| last_indexed | 2024-04-24T12:41:04Z |
| publishDate | 2024-04-01 |
| publisher | Nature Portfolio |
| record_format | Article |
| series | Scientific Reports |
| spelling | doaj.art-fa7f5792ea7f4b0e835c1f66f6a038232024-04-07T11:16:24ZengNature PortfolioScientific Reports2045-23222024-04-0114111410.1038/s41598-024-58020-yAn original aneuploidy-related gene model for predicting lung adenocarcinoma survival and guiding therapyYalei Zhang0Dongmei Li1Department of Thoracic Oncology, The First Affiliated Hospital of Guangzhou Medical UniversityDepartment of Thoracic Oncology, The First Affiliated Hospital of Guangzhou Medical UniversityAbstract Aneuploidy is a hallmark of cancers, but the role of aneuploidy-related genes in lung adenocarcinoma (LUAD) and their prognostic value remain elusive. Gene expression and copy number variation (CNV) data were enrolled from TCGA and GEO database. Consistency clustering analysis was performed for molecular cluster. Tumor microenvironment was assessed by the xCell and ESTIMATE algorithm. Limma package was used for selecting differentially expressed genes (DEGs). LASSO and stepwise multivariate Cox regression analysis were used to establish an aneuploidy-related riskscore (ARS) signature. GDSC database was conducted to predict drug sensitivity. A nomogram was designed by rms R package. TCGA-LUAD patients were stratified into 3 clusters based on CNV data. The C1 cluster displayed the optimal survival advantage and highest inflammatory infiltration. Based on integrated intersecting DEGs, we constructed a 6-gene ARS model, which showed effective prediction for patient’s survival. Drug sensitivity test predicted possible sensitive drugs in two risk groups. Additionally, the nomogram exhibited great predictive clinical treatment benefits. We established a 6-gene aneuploidy-related signature that could effectively predict the survival and therapy for LUAD patients. Additionally, the ARS model and nomogram could offer guidance for the preoperative estimation and postoperative therapy of LUAD.https://doi.org/10.1038/s41598-024-58020-yLung adenocarcinomaAneuploidyRiskscore modelNomogramTherapy |
| spellingShingle | Yalei Zhang Dongmei Li An original aneuploidy-related gene model for predicting lung adenocarcinoma survival and guiding therapy Scientific Reports Lung adenocarcinoma Aneuploidy Riskscore model Nomogram Therapy |
| title | An original aneuploidy-related gene model for predicting lung adenocarcinoma survival and guiding therapy |
| title_full | An original aneuploidy-related gene model for predicting lung adenocarcinoma survival and guiding therapy |
| title_fullStr | An original aneuploidy-related gene model for predicting lung adenocarcinoma survival and guiding therapy |
| title_full_unstemmed | An original aneuploidy-related gene model for predicting lung adenocarcinoma survival and guiding therapy |
| title_short | An original aneuploidy-related gene model for predicting lung adenocarcinoma survival and guiding therapy |
| title_sort | original aneuploidy related gene model for predicting lung adenocarcinoma survival and guiding therapy |
| topic | Lung adenocarcinoma Aneuploidy Riskscore model Nomogram Therapy |
| url | https://doi.org/10.1038/s41598-024-58020-y |
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