The role of homologous recombination deficiency (HRD) in lower grade glioma (LGG) has not
been elucidated, and accurate prognostic prediction is also important for the treatment and
management of LGG. The aim of this study was to construct an HRD-based risk model and to
explore the immunological and molecular characteristics of this risk model. The HRD score
threshold = 10 was determined from 506 LGG samples in The Cancer Genome Atlas cohort
using the best cut-off value, and patients with highHRDscores had worse overall survival. A total
of 251 HRD-related genes were identified by analyzing differentially expressed genes, 182 of
which were associated with survival. A risk score model based on HRD-related genes was
constructed using univariate Cox regression, least absolute shrinkage and selection operator
regression, and stepwise regression, and patients were divided into high- and low-risk groups
using the median risk score. High-risk patients had significantly worse overall survival than lowrisk
patients. The risk model had excellent predictive performance for overall survival in LGG and
was found to be an independent risk factor. The prognostic value of the riskmodel was validated
using an independent cohort. In addition, the risk score was associated with tumor mutation
burden and immune cell infiltration in LGG. High-risk patients had higher HRD scores and “hot”
tumor immune microenvironment, which could benefit from poly-ADP-ribose polymerase
inhibitors and immune checkpoint inhibitors. Overall, this big data study determined the
threshold of HRD score in LGG, identified HRD-related genes, developed a risk model
based on HRD-related genes, and determined the molecular and immunological
characteristics of the risk model. This provides potential new targets for future targeted
therapies and facilitates the development of individualized immunotherapy to improve prognosis.
| Identifer | oai:union.ndltd.org:DRESDEN/oai:qucosa:de:qucosa:87512 |
| Date | 20 October 2023 |
| Creators | Peng, Hao, Wang, Yibiao, Wang, Pengcheng, Huang, Chuixue, Liu, Zhaohui, Wu, Changwu |
| Publisher | Frontiers Media S.A. |
| Source Sets | Hochschulschriftenserver (HSSS) der SLUB Dresden |
| Language | English |
| Detected Language | English |
| Type | info:eu-repo/semantics/publishedVersion, doc-type:article, info:eu-repo/semantics/article, doc-type:Text |
| Rights | info:eu-repo/semantics/openAccess |
| Relation | 919391, 10.3389/fgene.2022.919391 |
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