Novel macrophage-related gene prognostic index for glioblastoma associated with M2 macrophages and T cell dysfunction

Abstract

This study aims to construct a Macrophage-Related Gene Prognostic Index (MRGPI) for glioblastoma (GBM) and explore the underlying molecular, metabolic, and immunological features. Based on the GBM dataset from The Cancer Genome Atlas (n = 156), 13 macrophage-related hub genes were identified by weighted gene co-expression network (WGCNA) analysis. 5 prognostic genes screened by Kaplan-Meire (K-M) analysis and Cox regression model were used to construct the MRGPI, including GPR84, NCF2, HK3, LILRB2, and CCL18. Multivariate Cox regression analysis found that the MRGPI was an independent risk factor (HR = 2.81, CI95: 1.13-6.98, p = 0.026), leading to an unfavorable outcome for the MRGPI-high group, which was further validated by 4 validation GBM cohorts (n = 728). Thereafter, the molecular, metabolic, and immune features and the clinical implications of the MRGPI-based groups were comprehensively characterized. Gene set enrichment analysis (GSEA) found that immune-related pathways, including inflammatory and adaptive immune response, and activated eicosanoid metabolic pathways were enriched in the MRGPI-high group. Besides, genes constituting the MRGPI was primarily expressed by monocytes and macrophages at single-cell scope and was associated with the alternative activation of macrophages. Moreover, correlation analysis and receiver operating characteristic (ROC) curves revealed the relevance between the MRGPI with the expression of immune checkpoints and T cell dysfunction. Thus, the responsiveness of samples in the MRGPI-high group to immune checkpoint inhibitors (ICI) was detected by algorithms, including Tumor Immune Dysfunction and Exclusion (TIDE) and Submap. In contrast, the MRGPI-low group had favorable outcome, was less immune active and insensitive to ICI. Together, we have developed a promising biomarker to classify the prognosis, metabolic and immune features for GBM, and provide references for facilitating the personalized application of ICI in GBM.

Role of NCF2 as a potential prognostic factor and immune infiltration indicator in hepatocellular carcinoma

“…22 In gastrointestinal cancer, high expression level of NCF2 was associated with the poor prognosis of esophageal squamous cell carcinoma, 23 and Zhang et al revealed that upregulation of NCF2 promoted the angiogenesis and metastasis of gastric cancer through NF-κB pathway. 24 Besides, NCF2 was selected to construct a Macrophage-Related Gene Prognostic Index for glioblastoma, 25 and methylation of CpG sites of NCF2 was associated with the risk of breast cancer. 26 However, the effect of NCF2 on the prognosis of HCC has not been explored before.…”

Exploring the prognostic value of HK3 and its association with immune infiltration in glioblastoma multiforme

“…HK3 was also identified as a biomarker of macrophages in clear cell renal cell carcinoma ( Xu et al, 2021 ). Moreover, HK3 showed an association with M2 macrophages and T cell dysfunction in GBM ( Ji et al, 2022 ).…”

Dual roles of HK3 in regulating the network between tumor cells and tumor-associated macrophages in neuroblastoma

“…The potential mechanisms of this phenotype were sought to be elucidated. Since HK3 is a subtype of hexokinase involved in the first step of glucose metabolism, lactate is a direct by-product of glycolysis, which has been widely demonstrated to be directly involved in tumor progression by M2 macrophage polarization in tumor microenvironment [18,26]. Histone lysine lactylation (Kla) was identified as a novel post-modification (PTM) [27].…”