Golgi-apparatus genes related signature for predicting the progression-free interval of patients with papillary thyroid carcinoma
Abstract Background We aimed to build a novel model with golgi apparatus related genes (GaGs) signature and relevant clinical parameters for predicting progression-free interval (PFI) after surgery for papillary thyroid carcinoma (PTC). Methods We performed a bioinformatic analysis of integrated PTC...
| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
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BMC
2023-03-01
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| Series: | BMC Medical Genomics |
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| Online Access: | https://doi.org/10.1186/s12920-023-01485-z |
| _version_ | 1797853501477355520 |
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| author | Rui Liu Zhen Cao Mengwei Wu Xiaobin Li Peizhi Fan Ziwen Liu |
| author_facet | Rui Liu Zhen Cao Mengwei Wu Xiaobin Li Peizhi Fan Ziwen Liu |
| author_sort | Rui Liu |
| collection | DOAJ |
| description | Abstract Background We aimed to build a novel model with golgi apparatus related genes (GaGs) signature and relevant clinical parameters for predicting progression-free interval (PFI) after surgery for papillary thyroid carcinoma (PTC). Methods We performed a bioinformatic analysis of integrated PTC datasets with the GaGs to identify differentially expressed GaGs (DE-GaGs). Then we generated PFI-related DE-GaGs and established a novel GaGs based signature. After that, we validated the signature on multiple external datasets and PTC cell lines. Further, we conducted uni- and multivariate analyses to identify independent prognostic characters. Finally, we established a signature and clinical parameters-based nomogram for predicting the PFI of PTC. Results We identified 260 DE-GaGs related to PFI in PTC. The functional enrichment analysis showed that the DE-MTGs were associated with an essential oncogenic glycoprotein biosynthetic process. Consequently, we established and optimized a novel 11 gene signature that could distinguish patients with poorer prognoses and predicted PFI accurately. The novel signature had a C-index of 0.78, and the relevant nomogram had a C-index of 0.79. Also, it was closely related to the pivotal clinical characters of and anaplastic potential in datasets and PTC cell lines. And the signature was confirmed a significant independent prognostic factor in PTC. Finally, we built a nomogram by including the signature and relevant clinical factors. Validation analysis showed that the nomogram’s efficacy was satisfying in predicting PTC’s PFI. Conclusion The GaGs signature and nomogram were closely associated with PTC prognosis and may help clinicians improve the individualized prediction of PFI, especially for high-risk patients after surgery. |
| first_indexed | 2024-04-09T19:51:38Z |
| format | Article |
| id | doaj.art-27e521039db549b49f394ae66a50270a |
| institution | Directory Open Access Journal |
| issn | 1755-8794 |
| language | English |
| last_indexed | 2024-04-09T19:51:38Z |
| publishDate | 2023-03-01 |
| publisher | BMC |
| record_format | Article |
| series | BMC Medical Genomics |
| spelling | doaj.art-27e521039db549b49f394ae66a50270a2023-04-03T05:43:51ZengBMCBMC Medical Genomics1755-87942023-03-0116111410.1186/s12920-023-01485-zGolgi-apparatus genes related signature for predicting the progression-free interval of patients with papillary thyroid carcinomaRui Liu0Zhen Cao1Mengwei Wu2Xiaobin Li3Peizhi Fan4Ziwen Liu5Department of Breast and Thyroid Surgery, Hunan Provincial People’s Hospital/The First Affiliated Hospital of Hunan Normal UniversityDepartment of General Surgery, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical CollegeDepartment of General Surgery, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical CollegeDepartment of General Surgery, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical CollegeDepartment of Breast and Thyroid Surgery, Hunan Provincial People’s Hospital/The First Affiliated Hospital of Hunan Normal UniversityDepartment of General Surgery, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical CollegeAbstract Background We aimed to build a novel model with golgi apparatus related genes (GaGs) signature and relevant clinical parameters for predicting progression-free interval (PFI) after surgery for papillary thyroid carcinoma (PTC). Methods We performed a bioinformatic analysis of integrated PTC datasets with the GaGs to identify differentially expressed GaGs (DE-GaGs). Then we generated PFI-related DE-GaGs and established a novel GaGs based signature. After that, we validated the signature on multiple external datasets and PTC cell lines. Further, we conducted uni- and multivariate analyses to identify independent prognostic characters. Finally, we established a signature and clinical parameters-based nomogram for predicting the PFI of PTC. Results We identified 260 DE-GaGs related to PFI in PTC. The functional enrichment analysis showed that the DE-MTGs were associated with an essential oncogenic glycoprotein biosynthetic process. Consequently, we established and optimized a novel 11 gene signature that could distinguish patients with poorer prognoses and predicted PFI accurately. The novel signature had a C-index of 0.78, and the relevant nomogram had a C-index of 0.79. Also, it was closely related to the pivotal clinical characters of and anaplastic potential in datasets and PTC cell lines. And the signature was confirmed a significant independent prognostic factor in PTC. Finally, we built a nomogram by including the signature and relevant clinical factors. Validation analysis showed that the nomogram’s efficacy was satisfying in predicting PTC’s PFI. Conclusion The GaGs signature and nomogram were closely associated with PTC prognosis and may help clinicians improve the individualized prediction of PFI, especially for high-risk patients after surgery.https://doi.org/10.1186/s12920-023-01485-zPapillary thyroid carcinomaPredictive modelThe Cancer Genome Atlas ProgramGolgi apparatus related genesNomogram |
| spellingShingle | Rui Liu Zhen Cao Mengwei Wu Xiaobin Li Peizhi Fan Ziwen Liu Golgi-apparatus genes related signature for predicting the progression-free interval of patients with papillary thyroid carcinoma BMC Medical Genomics Papillary thyroid carcinoma Predictive model The Cancer Genome Atlas Program Golgi apparatus related genes Nomogram |
| title | Golgi-apparatus genes related signature for predicting the progression-free interval of patients with papillary thyroid carcinoma |
| title_full | Golgi-apparatus genes related signature for predicting the progression-free interval of patients with papillary thyroid carcinoma |
| title_fullStr | Golgi-apparatus genes related signature for predicting the progression-free interval of patients with papillary thyroid carcinoma |
| title_full_unstemmed | Golgi-apparatus genes related signature for predicting the progression-free interval of patients with papillary thyroid carcinoma |
| title_short | Golgi-apparatus genes related signature for predicting the progression-free interval of patients with papillary thyroid carcinoma |
| title_sort | golgi apparatus genes related signature for predicting the progression free interval of patients with papillary thyroid carcinoma |
| topic | Papillary thyroid carcinoma Predictive model The Cancer Genome Atlas Program Golgi apparatus related genes Nomogram |
| url | https://doi.org/10.1186/s12920-023-01485-z |
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