Development and validation of a predictive model in diagnosis and prognosis of primary glioblastoma patients based on Homeobox A family

Zong-Qing Zheng; Gui-Qiang Yuan; Guo-Guo Zhang; Qian-Qian Nie; Zhong Wang

doi:10.1007/s12672-023-00726-y

Development and validation of a predictive model in diagnosis and prognosis of primary glioblastoma patients based on Homeobox A family

Discov Oncol. 2023 Jun 23;14(1):108. doi: 10.1007/s12672-023-00726-y.

Authors

Zong-Qing Zheng^#¹, Gui-Qiang Yuan^#², Guo-Guo Zhang¹, Qian-Qian Nie¹, Zhong Wang³

Affiliations

¹ Department of Neurosurgery & Brain and Nerve Research Laboratory, The First Affiliated Hospital of Soochow University, 188 Shizi Street, Suzhou, 215006, Jiangsu Province, China.
² Beijing Neurosurgical Institute & Department of Neurosurgery, Beijing Tiantan Hospital Affiliated to Capital Medical University, Capital Medical University, Beijing, China.
³ Department of Neurosurgery & Brain and Nerve Research Laboratory, The First Affiliated Hospital of Soochow University, 188 Shizi Street, Suzhou, 215006, Jiangsu Province, China. wangzhong_8761@163.com.

^# Contributed equally.

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.

Keywords: Diagnosis; Glioblastoma (GBM); Homeobox-A (HOXA); Nomogram; Prognosis.