Abstract
Lower-grade gliomas (LrGG), characterized by invasiveness and heterogeneity, remain incurable with current therapies. Clinicopathological features provide insufficient information to guide optimal individual treatment and cannot predict prognosis completely. Recently, an increasing amount of studies indicate that the tumor microenvironment plays a pivotal role in tumor malignancy and treatment responses. However, studies focusing on the tumor microenvironment (TME) of LrGG are still limited. In this study, taking advantage of the currently popular computational methods for estimating the infiltration of tumor-associated normal cells in tumor samples and using weighted gene co-expression network analysis, we screened the co-expressed gene modules associated with the TME and further identified the prognostic hub genes in these modules. Furthermore, eight prognostic hub genes (ARHGDIB, CLIC1, OAS3, PDIA4, PARP9, STAT1, TAP2, and TAGLN2) were selected to construct a prognostic risk score model using the least absolute shrinkage and selection operator method. Univariate and multivariate Cox regression analysis demonstrated that the risk score was an independent prognostic factor for LrGG. Moreover, time-dependent ROC curves indicated that our model had favorable efficiency in predicting both short- and long-term prognosis in LrGG patients, and the stratified survival analysis demonstrated that our model had prognostic value for different subgroups of LrGG patients. Additionally, our model had potential value for predicting the sensitivity of LrGG patients to radio- and chemotherapy. Besides, differential expression analysis showed that the eight genes were aberrantly expressed in LrGG compared to normal brain tissue. Correlation analysis revealed that the expression of the eight genes was significantly associated with the infiltration levels of six types of immune cells in LrGG. In summary, the TME-related eight-gene signature was significantly associated with the prognosis of LrGG patients. They might act as potential prognostic biomarkers for LrGG patients, offer better stratification for future clinical trials, and be candidate targets for immunotherapy, thus deserving further investigation.
Highlights
Lower-grade gliomas (LrGG) are infiltrative and heterogeneous brain neoplasms that include World Health Organization (WHO) grade II and III diffuse gliomas (Patel et al, 2017)
The results showed that both immune scores and stromal scores in IDH Mutant (IDH-Mut) subtype samples were significantly lower than those in IDH wildtype (IDH-Wt) subtype samples (Figures 1C, D)
The stromal scores of transcriptome subtypes were similar to the results of immune scores, except there was no significant difference between the stromal scores of neural and proneural subtype samples (Figure 1F)
Summary
Lower-grade gliomas (LrGG) are infiltrative and heterogeneous brain neoplasms that include World Health Organization (WHO) grade II and III diffuse gliomas (Patel et al, 2017) Because of their highly invasive characteristics, complete neurosurgical resection is unachievable for most patients. Due to considerable heterogeneity between LrGG, an optimal treatment strategy against this disease at the individual level still remains a challenge (Duffau, 2018). From this perspective, it is necessary to develop reliable approaches for identifying subsets of patients at high risk of deterioration and to find novel molecular targets for the development of effective therapeutic strategies
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