Complement and coagulation cascades are associated with prognosis and the immune microenvironment of lower-grade glioma

Abstract

Background Abnormal coagulation is a common feature of glioma. There is a strong correlation between coagulation and the complement system, named complement and coagulation cascades (CCC). However, the role of CCC genes in lower-grade glioma (LGG) remains unclear. This study aimed to investigate the role of CCC genes in LGG. Methods In total, 5,628 differential expressed genes were identified between 498 LGG tissues from The Cancer Genome Atlas (TCGA) and 207 normal brain tissues from Genotype-Tissue Expression Project (GTEx). Among them, 20 overlapped CCC genes were identified as differentially expressed CCC genes. Then, comprehensive bioinformatics analysis was used to investigate the role of CCC genes in LGG; 271 LGG tissues from the Chinese Glioma Genome Atlas (CGGA) were used as the validation dataset. Cell Counting Kit-8 (CCK8) proliferation assay, colony formation assay, and wound healing assay were conducted to explore the anti-glioma effect of the sensitive drugs we predicted. Results We constructed a risk signature consisting of six CCC genes, including F2R , SERPINA1 , TFPI , C1QC , C2 , and C3AR1 . The CCC gene-based risk signature could accurately predict the prognosis of patients with LGG. In addition, we found that the JAK-STAT, NOD-like receptor, Notch, PI3K-Akt, and Rap1 signaling pathways might be activated and had crosstalk with CCC in the high-risk group. Our findings analyses demonstrated that samples in high- and low-risk groups had different immune landscapes. Moreover, patients in the high-risk group might have greater resistance to immunotherapy. We validated the accuracy of the risk signature in predicting immunotherapy response in two public immunotherapy cohorts, GSE135222 and GSE78220. By means of oncoPredict, MG-132, BMS-536924, PLX-4720, and AZD6482 were identified as potential sensitive drugs for high-risk patients, of which MG-132 was particularly recommended for high-risk patients. We performed in vitro experiments to explore the anti-glioma effect of MG-132, and the results demonstrated MG-132 could inhibit the proliferation and migration of glioma cells. Conclusions Our findings show that CCC genes are associated with the prognosis and immune infiltration of LGG and provide possible immunotherapeutic and novel chemotherapeutic strategies for patients with LGG based on the risk signature.

Integrated pan-cancer and scRNA-seq analyses identify a prognostic coagulation-related gene signature associated with tumor microenvironment in lower-grade glioma

“…This rigorous approach aimed to identify the most robust and predictive features and enhanced the model's prognostic performance. Notably, our model outperformed a previously reported predictive model in the literature [ 25 ]. While their model achieved survival AUC values of 0.57, 0.61, and 0.65 at 1, 3, and 5 years, respectively, in the test CGGA dataset, our model exhibited superior predictive accuracy with survival AUC values of 0.79, 0.82, and 0.81 at the corresponding time points.…”