Development and validation of a predictive model in diagnosis and prognosis of primary glioblastoma patients based on Homeobox A family
Abstract Background Homeobox A (HOXA) family is involved in the development of malignancies as either tumor suppressors or oncogenes. However, their roles in glioblastoma (GBM) and clinical significance have not been fully elucidated. Methods HOXA mutation and expressions in pan-cancers were investi...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
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Springer
2023-06-01
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| Series: | Discover Oncology |
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| Online Access: | https://doi.org/10.1007/s12672-023-00726-y |
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| author | Zong-Qing Zheng Gui-Qiang Yuan Guo-Guo Zhang Qian-Qian Nie Zhong Wang |
| author_facet | Zong-Qing Zheng Gui-Qiang Yuan Guo-Guo Zhang Qian-Qian Nie Zhong Wang |
| author_sort | Zong-Qing Zheng |
| collection | DOAJ |
| description | Abstract Background Homeobox A (HOXA) family is involved in the development of malignancies as either tumor suppressors or oncogenes. However, their roles in glioblastoma (GBM) and clinical significance have not been fully elucidated. Methods HOXA mutation and expressions in pan-cancers were investigated using GSCA and Oncomine, which in GBM were validated by cBioPortal, Chinese Glioma Genome Atlas (CGGA), and The Cancer Genome Atlas (TCGA) datasets. Kaplan–Meier analyses were conducted to determine prognostic values of HOXAs at genetic and mRNA levels. Diagnostic roles of HOXAs in tumor classification were explored by GlioVis and R software. Independent prognostic HOXAs were identified using Cox survival analyses, the least absolute shrinkage and selection operator (LASSO) regression, quantitative real-time PCR, and immunohistochemical staining. A HOXAs-based nomogram survival prediction model was developed and evaluated using Kaplan–Meier analysis, time-dependent Area Under Curve, calibration plots, and Decision Curve Analysis in training and validation cohorts. Results HOXAs were highly mutated and overexpressed in pan-cancers, especially in CGGA and TCGA GBM datasets. Genetic alteration and mRNA expression of HOXAs were both found to be prognostic. Specific HOXAs could distinguish IDH mutation (HOXA1-7, HOXA9, HOXA13) and molecular GBM subtypes (HOXA1-2, HOXA9-11, HOXA13). HOXA1/2/3/10 were confirmed to be independent prognostic members, with high expressions validated in clinical GBM tissues. The HOXAs-based nomogram model exhibited good prediction performance and net benefits for patients in training and validation cohorts. Conclusion HOXA family has diagnostic values, and the HOXAs-based nomogram model is effective in survival prediction, providing a novel approach to support the treatment of GBM patients. |
| first_indexed | 2024-03-13T03:21:43Z |
| format | Article |
| id | doaj.art-ecc0dcac54db4061b7e7fccbabb2a7a7 |
| institution | Directory Open Access Journal |
| issn | 2730-6011 |
| language | English |
| last_indexed | 2024-03-13T03:21:43Z |
| publishDate | 2023-06-01 |
| publisher | Springer |
| record_format | Article |
| series | Discover Oncology |
| spelling | doaj.art-ecc0dcac54db4061b7e7fccbabb2a7a72023-06-25T11:20:48ZengSpringerDiscover Oncology2730-60112023-06-0114111810.1007/s12672-023-00726-yDevelopment and validation of a predictive model in diagnosis and prognosis of primary glioblastoma patients based on Homeobox A familyZong-Qing Zheng0Gui-Qiang Yuan1Guo-Guo Zhang2Qian-Qian Nie3Zhong Wang4Department of Neurosurgery & Brain and Nerve Research Laboratory, The First Affiliated Hospital of Soochow UniversityBeijing Neurosurgical Institute & Department of Neurosurgery, Beijing Tiantan Hospital Affiliated to Capital Medical University, Capital Medical UniversityDepartment of Neurosurgery & Brain and Nerve Research Laboratory, The First Affiliated Hospital of Soochow UniversityDepartment of Neurosurgery & Brain and Nerve Research Laboratory, The First Affiliated Hospital of Soochow UniversityDepartment of Neurosurgery & Brain and Nerve Research Laboratory, The First Affiliated Hospital of Soochow UniversityAbstract Background Homeobox A (HOXA) family is involved in the development of malignancies as either tumor suppressors or oncogenes. However, their roles in glioblastoma (GBM) and clinical significance have not been fully elucidated. Methods HOXA mutation and expressions in pan-cancers were investigated using GSCA and Oncomine, which in GBM were validated by cBioPortal, Chinese Glioma Genome Atlas (CGGA), and The Cancer Genome Atlas (TCGA) datasets. Kaplan–Meier analyses were conducted to determine prognostic values of HOXAs at genetic and mRNA levels. Diagnostic roles of HOXAs in tumor classification were explored by GlioVis and R software. Independent prognostic HOXAs were identified using Cox survival analyses, the least absolute shrinkage and selection operator (LASSO) regression, quantitative real-time PCR, and immunohistochemical staining. A HOXAs-based nomogram survival prediction model was developed and evaluated using Kaplan–Meier analysis, time-dependent Area Under Curve, calibration plots, and Decision Curve Analysis in training and validation cohorts. Results HOXAs were highly mutated and overexpressed in pan-cancers, especially in CGGA and TCGA GBM datasets. Genetic alteration and mRNA expression of HOXAs were both found to be prognostic. Specific HOXAs could distinguish IDH mutation (HOXA1-7, HOXA9, HOXA13) and molecular GBM subtypes (HOXA1-2, HOXA9-11, HOXA13). HOXA1/2/3/10 were confirmed to be independent prognostic members, with high expressions validated in clinical GBM tissues. The HOXAs-based nomogram model exhibited good prediction performance and net benefits for patients in training and validation cohorts. Conclusion HOXA family has diagnostic values, and the HOXAs-based nomogram model is effective in survival prediction, providing a novel approach to support the treatment of GBM patients.https://doi.org/10.1007/s12672-023-00726-yGlioblastoma (GBM)Homeobox-A (HOXA)NomogramPrognosisDiagnosis |
| spellingShingle | Zong-Qing Zheng Gui-Qiang Yuan Guo-Guo Zhang Qian-Qian Nie Zhong Wang Development and validation of a predictive model in diagnosis and prognosis of primary glioblastoma patients based on Homeobox A family Discover Oncology Glioblastoma (GBM) Homeobox-A (HOXA) Nomogram Prognosis Diagnosis |
| title | Development and validation of a predictive model in diagnosis and prognosis of primary glioblastoma patients based on Homeobox A family |
| title_full | Development and validation of a predictive model in diagnosis and prognosis of primary glioblastoma patients based on Homeobox A family |
| title_fullStr | Development and validation of a predictive model in diagnosis and prognosis of primary glioblastoma patients based on Homeobox A family |
| title_full_unstemmed | Development and validation of a predictive model in diagnosis and prognosis of primary glioblastoma patients based on Homeobox A family |
| title_short | Development and validation of a predictive model in diagnosis and prognosis of primary glioblastoma patients based on Homeobox A family |
| title_sort | development and validation of a predictive model in diagnosis and prognosis of primary glioblastoma patients based on homeobox a family |
| topic | Glioblastoma (GBM) Homeobox-A (HOXA) Nomogram Prognosis Diagnosis |
| url | https://doi.org/10.1007/s12672-023-00726-y |
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