scholarly journals BIOM-63. DIAGNOSIS AND PROGNOSTIC SIGNIFICANCE OF CIRCULATING miR-2276-5p IN PLASMA OF GLIOMA PATIENTS

2020 ◽  
Vol 22 (Supplement_2) ◽  
pp. ii15-ii15
Author(s):  
Shiguang Zhao
Keyword(s):  
Regression Analysis ◽  
Roc Curve ◽  
Cox Regression ◽  
Low Grade ◽  
High Grade ◽  
Circulating Mirnas ◽  
Cox Regression Analysis ◽  
Relative Expression ◽  
Low Grade Gliomas ◽  
Lower Expression

Abstract Circulating microRNAs (miRNAs) in plasma have the potential to become diagnostic and prognostic biomarkers for various cancers. This study hopes to use plasma circulating miRNAs as biomarkers for diagnosis and prognosis of glioma patients. METHOD: In this study, the plasma circulating miRNAs of 124 patients with glioma and 36 controls was collected to detect the relative expression of miR-2276-5p, and the specificity and sensitivity of the diagnosis were verified by ROC curve. The follow-up survival status was analyzed by cox regression analysis. RESULT: In the GSE 139031 database, it was found that the expression of circulating miR-2276-5p in plasma of glioma patients was significantly lower than that of patients with non-gliomas. Using our plasma samples, and it is indicated that the expression of circulating miR-2276-5p in plasma is lower than that of healthy patients, and compared with low-grade gliomas, patients with high-grade gliomas have a lower expression of circulating miR-2276-5p. ROC curve analysis found that the AUC value was 0.851. The low expression of circulating miR-2276-5p in plasma of glioma patients indicates a poor prognosis of glioma patients, After univariate and multifactorial cox regression analysis, which can be used as an independent prognostic risk factor for glioma patients (P< 0.05). CONCLUSION: The expression of circulating miR-2276-5p in plasma of glioma patients was significantly lower than that of the control group, compared with low-grade gliomas, patients with high-grade gliomas have a lower expression of circulating miR-2276-5p. The lower the relative expression of circulating miR-2276-5p indicated that glioma patients had a worse prognosis.

scholarly journals Antibiotic Allergy and Blood Eosinophils Percent Could Be Prognostic Indicators of Glioma

2021 ◽  
Author(s):  
Liming Cao ◽  
Zhanghua Lv ◽  
Weiliang Wang ◽  
Xue Li ◽  
Jing Shi ◽  
...  
Keyword(s):  
Regression Analysis ◽  
Cox Regression ◽  
Tumor Grade ◽  
Blood Eosinophil ◽  
Low Grade ◽  
High Grade ◽  
Cox Regression Analysis ◽  
Low Grade Gliomas ◽  
Antibiotic Allergy ◽  
High Grade Gliomas

Abstract Background: Antibiotic allergy and blood eosinophil percentage (EOS%) may play an important role in the prognosis of gliomas, but few studies reported the relationship between antibiotic allergy and glioma as well as EOS% and glioma. The aim of our study was to estimate the relationships between antibiotic allergy, blood eosinophil percentage (EOS%) and glioma prognosis and to conduct a nomogram model for glioma patients. Estimating the effect of antibiotic allergy and EOS% on glioma prognosis may conduce to finding low-cost and safe prognostic indicators of glioma.Methods: We conducted a retrospective cohort study with 656 glioma patients to estimate the associations between antibiotic allergy, EOS% and glioma prognosis by Kaplan-Meier and Cox regression analysis. Stratified analyses were performed according to tumor grade. We constructed a nomogram with age at diagnosis, gender, tumor grade, antibiotic allergy, EOS% to predict the survival probabilities of glioma. Results: During 12 months follow-up, a total of 227 patients were alive and 318 patients died. Antibiotic allergy and EOS% >1.65 conferred a survival advantage on glioma patients. In the stratified analysis by tumor grade, antibiotic allergy was significantly associated with the prognosis of the prognosis of low-grade gliomas (HR = 0.36, 95%CI: 0.13-0.97) and high-grade gliomas (HR = 0.58, 95%CI: 0.36-0.93) in the univariate Cox regression analysis. However, after adjusting for confounding factors in the multivariate Cox regression analysis, antibiotic allergy was only significantly associated with high-grade gliomas (HRadj = 0.50, 95%CI: 0.30-0.82); the relationship between EOS% and glioma prognosis was restricted to low-grade gliomas (HRadj = 0.50, 95%CI: 0.30-0.82). The C-index of nomogram was 0.74.Conclusions: Antibiotic allergy was a protective prognosis factor of high-grade gliomas, EOS% >1.65 was a protective prognosis factor of low-grade gliomas. The nomogram with antibiotic allergy and EOS% could effectively predict the survival probability of glioma.

scholarly journals The Role of Extent of Resection in IDH1 Wild-Type or Mutant Low-Grade Gliomas

Neurosurgery ◽  
2017 ◽  
Vol 82 (6) ◽  
pp. 808-814 ◽  
Author(s):  
Toral Patel ◽  
Evan D Bander ◽  
Rachael A Venn ◽  
Tiffany Powell ◽  
Gustav Young-Min Cederquist ◽  
...  
Keyword(s):  
Cox Regression ◽  
Extent Of Resection ◽  
World Health ◽  
Low Grade ◽  
Wild Type ◽  
Who Grade ◽  
Cox Regression Analysis ◽  
Low Grade Gliomas ◽  
Grade Ii ◽  
The Impact

Abstract BACKGROUND Maximizing extent of resection (EOR) improves outcomes in adults with World Health Organization (WHO) grade II low-grade gliomas (LGG). However, recent studies demonstrate that LGGs bearing a mutation in the isocitrate dehydrogenase 1 (IDH1) gene are a distinct molecular and clinical entity. It remains unclear whether maximizing EOR confers an equivalent clinical benefit in IDH mutated (mtIDH) and IDH wild-type (wtIDH) LGGs. OBJECTIVE To assess the impact of EOR on malignant progression-free survival (MPFS) and overall survival (OS) in mtIDH and wtIDH LGGs. METHODS We performed a retrospective review of 74 patients with WHO grade II gliomas and known IDH mutational status undergoing resection at a single institution. EOR was assessed with quantitative 3-dimensional volumetric analysis. The effect of predictor variables on MPFS and OS was analyzed with Cox regression models and the Kaplan–Meier method. RESULTS Fifty-two (70%) mtIDH patients and 22 (30%) wtIDH patients were included. Median preoperative tumor volume was 37.4 cm3; median EOR of 57.6% was achieved. Univariate Cox regression analysis confirmed EOR as a prognostic factor for the entire cohort. However, stratifying by IDH status demonstrates that greater EOR independently prolonged MPFS and OS for wtIDH patients (hazard ratio [HR] = 0.002 [95% confidence interval {CI} 0.000-0.074] and HR = 0.001 [95% CI 0.00-0.108], respectively), but not for mtIDH patients (HR = 0.84 [95% CI 0.17-4.13] and HR = 2.99 [95% CI 0.15-61.66], respectively). CONCLUSION Increasing EOR confers oncologic and survival benefits in IDH1 wtLGGs, but the impact on IDH1 mtLGGs requires further study.

scholarly journals Combination of CHARGE AF score and index of 24-hour electrocardiogram to predict incident atrial fibrillation and cardiovascular events

2021 ◽  
Vol 42 (Supplement_1) ◽  
Author(s):  
T Nishimura ◽  
K Senoo ◽  
I Hibiki ◽  
T Okura ◽  
T Miki ◽  
...  
Keyword(s):  
Heart Failure ◽  
Atrial Fibrillation ◽  
Regression Analysis ◽  
Roc Curve ◽  
Cardiovascular Events ◽  
Cox Regression ◽  
Cox Regression Analysis ◽  
Holter Ecg ◽  
New Onset

Abstract Background Atrial fibrillation (AF) is associated with increased risks of stroke and heart failure. AF risk prediction can facilitate the efficient deployment of diagnosis or interventions to prevent AF. Purpose We sought to assess the combination prediction value of Holter electrocardiogram (Holter ECG) and the CHARGE-AF score (Cohorts for Aging and Research in Genomic Epidemiology-AF) for the new-onset of AF in a single center study. We also investigated the association between clinical findings and the new-onset of cerebral cardiovascular events. Methods From January 2008 and May 2014, 1246 patients with aged≥20 undergoing Holter ECG for palpitations, dizziness, or syncope were recruited. Among them, 350 patients were enrolled in this study after exclusion of 1) AF history at the time of inspection or before, 2) post cardiac device implantation, 3) follow-up duration <1 year, and 4) no 12-lead ECG records within 6 months around Holter ECG. Results During the 5.9-year follow-up, 40 patients (11.4%) developed AF incidence. Multivariate cox regression analysis revealed that CHARGE-AF score (hazard ratio [HR]: 1.59, 95% confidence interval (95% CI): 1.13–2.26, P<0.01), BMI (HR: 0.91, 95% CI: 0.83–0.99, P=0.03), frequent supraventricular extrasystoles (SVEs) ≥1000 beats/day (HR: 4.87, 95% CI: 2.59–9.13, P<0.001) and first-degree AV block (HR: 3.52, 95% CI: 1.63–7.61, P<0.01) were significant independent predictors for newly AF. The area under the ROC curve (AUC) of the combination of the CHARGE-AF score and frequent SVEs (≥1000) was greater than the CHARGE-AF score alone (0.73, 95% CI: 0.64–0.82 vs 0.66, 95% CI: 0.56–0.75, respectively). On the ROC curve, the CHARGE-AF score of 12.9 was optimum cut-off value for newly AF. Patients with both the CHARGE-AF score≥12.9 and SVEs≥1000 developed AF at 129.0/1000 person-years, compared with those with the CHARGE-AF score<12.9 and SVEs≥1000 (48.9), the CHARGE-AF score≥12.9 and SVEs<1000 (40.0) and the CHARGE-AF score<12.9 and SVEs<1000 (7.4), respectively. In multivariate cox regression analysis, age, past history of congestive heart failure and myocardial infarction, and antihypertensive medication were significant predictors of cerebral cardiovascular events (n=43), all of which signifying the components of the CHARGE-AF score. The AUC of the combination of the CHARGE-AF score and frequent SVEs (≥1000) was not different from the CHARGE-AF score alone (0.73, 95% CI: 0.64–0.81 vs 0.73, 95% CI: 0.64–0.82, respectively). Conclusion CHARGE-AF score has higher predictive power of both the new incident AF and cerebral cardiovascular events. The combination of CHARGE-AF score and SVEs≥1000 beats/day in Holter ECG can demonstrate the additional effect of prediction ability for the new incident AF, but not for cerebral cardiovascular events. FUNDunding Acknowledgement Type of funding sources: None.

scholarly journals Clinical Prognostic Model of Autophagy-Related LncRNA Genes in The Esophageal Adenocarcinoma (EAC) to Predicting Overall Survival (OS) of The Patients：The Evidence From Bioinformatic Analysis

2021 ◽  
Author(s):  
Liusheng Wu ◽  
Xiaoqiang Li ◽  
Jixian Liu ◽  
Da Wu ◽  
Dingwang Wu ◽  
...  
Keyword(s):  
Overall Survival ◽  
Regression Analysis ◽  
Esophageal Adenocarcinoma ◽  
Clinical Data ◽  
Roc Curve ◽  
Prognostic Model ◽  
Cox Regression ◽  
Enrichment Analysis ◽  
Prognostic Models ◽  
Cox Regression Analysis

Abstract Objective: Autophagy-related LncRNA genes play a vital role in the development of esophageal adenocarcinoma.Our study try to construct a prognostic model of autophagy-related LncRNA esophageal adenocarcinoma, and use this model to calculate patients with esophageal adenocarcinoma. The survival risk value of esophageal adenocarcinoma can be used to evaluate its survival prognosis. At the same time, to explore the sites of potential targeted therapy genes to provide valuable guidance for the clinical diagnosis and treatment of esophageal adenocarcinoma.Methods: Our study have downloaded 261 samples of LncRNA-related transcription and clinical data of 87 patients with esophageal adenocarcinoma from the TCGA database, and 307 autophagy-related gene data from www.autuphagy.com. We applied R software (Version 4.0.2) for data analysis, merged the transcriptome LncRNA genes, autophagy-related genes and clinical data, and screened autophagy LncRNA genes related to the prognosis of esophageal adenocarcinoma. We also performed KEGG and GO enrichment analysis and GSEA enrichment analysis in these LncRNA genes to analysis the risk characteristics and bioinformatics functions of signal transduction pathways. Univariate and multivariate Cox regression analysis were used to determine the correlation between autophagy-related LncRNA and independent risk factors. The establishment of ROC curve facilitates the evaluation of the feasibility of predicting prognostic models, and further studies the correlation between autophagy-related LncRNA and the clinical characteristics of patients with esophageal adenocarcinoma. Finally, we also used survival analysis, risk analysis and independent prognostic analysis to verify the prognosis model of esophageal adenocarcinoma.Results: We screened and identified 22 autophagic LncRNA genes that are highly correlated with the overall survival (OS) of patients with esophageal adenocarcinoma. The area under the ROC curve（AUC=0.941）and the calibration curve have a good lineup, which has statistical analysis value. In addition, univariate and multivariate Cox regression analysis showed that the autophagy LncRNA feature of this esophageal adenocarcinoma is an independent predictor of esophageal adenocarcinoma.Conclusion: These LncRNA screened and identified may participate in the regulation of cellular autophagy pathways, and at the same time affect the tumor development and prognosis of patients with esophageal adenocarcinoma. These results indicate that risk signature and nomogram are important indicators related to the prognosis of patients with esophageal adenocarcinoma.

scholarly journals Expression Status and Prognostic Value of m6A RNA Methylation Regulators in Lung Adenocarcinoma

2020 ◽  
Author(s):  
Rui Wang ◽  
Zian Feng ◽  
Jie Hu ◽  
Xiaodong He ◽  
Zuojun Shen
Keyword(s):  
Regression Analysis ◽  
Survival Analysis ◽  
Roc Curve ◽  
Cox Regression ◽  
Risk Group ◽  
Cox Regression Analysis ◽  
Rna Methylation ◽  
Kaplan Meier ◽  
Prediction Efficiency

Abstract Background: N6-methyladenosine (m6A) RNA modification is the most abundant modification method in mRNA, and it plays an important role in the occurrence and development of many cancers. However, data on the role of m6A RNA methylation regulators in lung adenocarcinoma (LUAD) are still lacking. This paper mainly discusses the role of m6A RNA methylation regulators in LUAD, to identify novel prognostic biomarkers.Methods: The gene expression data of 19 m6A methylation regulator in LUAD patients and its relevant clinical parameters were extracted from The Cancer Genome Atlas (TCGA) database. The least absolute shrinkage and selection operator (LASSO) Cox regression algorithm were performed to construct a risk signature and evaluated its prognostic prediction efficiency by using the receiver operating characteristic (ROC) curve. The risk score of each patient was calculated according to the risk signature, and LUAD patients were divided into high-risk group and low-risk group. Kaplan-Meier survival analysis and Cox regression analysis were used to identify the independent prognostic significance of risk signature. Finally, Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), and Gene Set Enrichment Analysis (GSEA) were used to explore the differential signaling pathways and cellular processes between the two groups.Results: The expression of 15 m6A RNA methylation regulators in LUAD tissues was significantly different than that in normal tissues. YTHDF3, YTHDF2, KIAA1429, HNRNPA2B1, RBM15, METTL3, HNRNPC, YTHDF1, IGF2BP2, IGF2BP3, IGF2BP1 were significantly up-regulated in LUAD, and the expressions of FTO, ZC3H13, WTAP, and METL14 were significantly down-regulated. We selected IGF2BP1, HNRNPC, and HNRNPA2B1 to construct the risk signature. ROC curve indicated the area under the curve (AUC) was 0.659, which means the risk signature had a good prediction efficiency. The results of Kaplan-Meier survival analysis and Cox regression analysis showed that the risk score can be used as an independent prognostic factor for LUAD.Conclusions: The m6A RNA methylation regulators IGF2BP1, HNRNPC, and HNRNPA2B1 have a significant correlation with the clinicopathological characteristics of LUAD, which may be a promising prognostic feature and clinical treatment target.

A novel signature based on m6A related genes as the potential prognostic factor in hepatocellular carcinoma.

2020 ◽  
Author(s):  
Zhuomao Mo ◽  
Shaoju Luo ◽  
Hao Hu ◽  
Ling Yu ◽  
Zhirui Cao ◽  
...  
Keyword(s):  
Hepatocellular Carcinoma ◽  
Regression Analysis ◽  
Roc Curve ◽  
Cox Regression ◽  
Risk Group ◽  
Immune Therapy ◽  
The Cancer Genome Atlas ◽  
Cox Regression Analysis ◽  
Potential Biomarker ◽  
Significant Difference

Abstract Background Many different signatures and models have been established for patients with hepatocellular carcinoma (HCC), but no signature based on m6A related genes was developed. The objective of this research was to establish the signature with m6A related genes in HCC. Methods Data from 377 HCC patients from The Cancer Genome Atlas (TCGA) database was downloaded. The included m6A related genes were selected by Cox regression analysis and the signature was verified by survival analysis and multiple receiver operating characteristic (ROC) curve. Furthermore, the nomogram was constructed and evaluated by C-index, calibration plot and ROC curve. Results The signature was established with the four m6A related genes (YTHDF2, YTHDF1, METTL3 and KIAA1429). Under the grouping from signature, patients in high risk group of showed the poor prognosis than those in low risk group. And significant difference was found in two kinds of immune cells (T cell gamma delta and NK cells activated) between two groups. The univariate and multivariate Cox regression analysis indicated that m6A related signature can be the potential independent prognosis factor in HCC. Finally, we developed a clinical risk model predicting the HCC prognosis and successfully verified it in C-index, calibration and ROC curve. Conclusion Our study identified the m6A related signature for predicting prognosis of HCC and provided the potential biomarker between m6A and immune therapy.

scholarly journals Identification of an independent immune-genes prognostic index for renal cell carcinoma

BMC Cancer ◽  
2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Guangyao Li ◽  
Xiyi Wei ◽  
Shifeng Su ◽  
Shangqian Wang ◽  
Wei Wang ◽  
...  
Keyword(s):  
Regression Analysis ◽  
Risk Score ◽  
Roc Curve ◽  
Cox Regression ◽  
Cox Regression Analysis ◽  
Immune Genes ◽  
Score Model ◽  
Set Up ◽  
Immune Related Genes ◽  
Survival Risk

Abstract Background Considerable evidence has indicated an association between the immune microenvironment and clinical outcome in ccRCC. The purpose of this study is to extensively figure out the influence of immune-related genes of tumors on the prognosis of patients with ccRCC. Methods Files containing 2498 immune-related genes were obtained from the Immunology Database and Analysis Portal (ImmPort), and the transcriptome data and clinical information relevant to patients with ccRCC were identified and downloaded from the TCGA data-base. Univariate and multivariate Cox regression analyses were used to screen out prognostic immune genes. The immune risk score model was established in light of the regression coefficient between survival and hub immune-related genes. We eventually set up a nomogram for the prediction of the overall survival for ccRCC. Kaplan-Meier (K-M) and ROC curve was used in evaluating the value of the predictive risk model. A P value of < 0.05 indicated statistically significant differences throughout data analysis. Results Via differential analysis, we found that 556 immune-related genes were expressed differentially between tumor and normal tissues (p < 0. 05). The analysis of univariate Cox regression exhibited that there was a statistical correlation between 43 immune genes and survival risk in patients with ccRCC (p < 0.05). Through Lasso-Cox regression analysis, we established an immune genetic risk scoring model based on 18 immune-related genes. The high-risk group showed a bad prognosis in K-M analysis. (p < 0.001). ROC curve showed that it was reliable of the immune risk score model to predict survival risk (5 year over survival, AUC = 0.802). The model indicated satisfactory AUC and survival correlation in the validation data set (5 year OS, Area Under Curve = 0.705, p < 0.05). From Multivariate regression analysis, the immune-risk score model plays an isolated role in the prediction of the prognosis of ccRCC. Under multivariate-Cox regression analysis, we set up a nomogram for comprehensive prediction of ccRCC patients’ survival rate. At last, it was identified that 18 immune-related genes and risk scores were not only tremendously related to clinical prognosis but also contained in a variety of carcinogenic pathways. Conclusion In general, tumor immune-related genes play essential roles in ccRCC development and progression. Our research established an unequal 18-immune gene risk index to predict the prognosis of ccRCC visually. This index was found to be an independent predictive factor for ccRCC.

scholarly journals Clinical Significance of B-Type Natriuretic Peptide Levels at 3 Months after Atrial Fibrillation Ablation

Diseases ◽  
2021 ◽  
Vol 9 (3) ◽  
pp. 49
Author(s):  
Sen Matsumoto ◽  
Yasuharu Matsunaga-Lee ◽  
Masashi Ishimi ◽  
Mamoru Ohnishi ◽  
Nobutaka Masunaga ◽  
...  
Keyword(s):  
Atrial Fibrillation ◽  
Regression Analysis ◽  
Natriuretic Peptide ◽  
Roc Curve ◽  
Cox Regression ◽  
Significant Prognostic Factor ◽  
Cox Regression Analysis ◽  
Af Ablation ◽  
Increased Risk ◽  
The Impact

The role of B-type natriuretic peptide (BNP) levels as a predictor of arrhythmia recurrence (AR) after atrial fibrillation (AF) ablation remains unclear. In this study, we investigated the association of BNP levels before and 3 months after ablation with the risk of AR. A total of 234 patients undergoing their first session of AF ablation were included (68% male, mean age of 69 years). The cut-off value for discriminating AR was determined based on the maximum value of the area under the receiver operating characteristic (ROC) curve. The impact of BNP levels on AR was evaluated using Cox regression analysis. ROC curve analysis showed that the area under the curve for BNP at 3 months after the procedure was larger (0.714) compared to BNP levels before ablation (0.593). Elevated levels of BNP 3 months after the procedure (>40.5 pg/mL, n = 96) was associated with a higher risk of AR compared to those without elevated levels (34.4% vs. 10.9%, p < 0.01). Multivariate Cox regression analysis revealed that elevated BNP levels were associated with an increased risk of AR (hazard ratio 2.43; p = 0.014). Elevated BNP levels 3 months after AF ablation were a significant prognostic factor in AR, while baseline BNP levels were not.

scholarly journals Expression Status and Prognostic Value of m6A RNA Methylation Regulators in Lung Adenocarcinoma

Life ◽  
2021 ◽  
Vol 11 (7) ◽  
pp. 619
Author(s):  
Xiuhong Li ◽  
Zian Feng ◽  
Rui Wang ◽  
Jie Hu ◽  
Xiaodong He ◽  
...  
Keyword(s):  
Regression Analysis ◽  
Survival Analysis ◽  
Lung Adenocarcinoma ◽  
Roc Curve ◽  
Cox Regression ◽  
Cox Regression Analysis ◽  
Rna Methylation ◽  
Kaplan Meier ◽  
M6a Rna Methylation ◽  
Prediction Efficiency

N6-methyladenosine (m6A) RNA modification is the most abundant modification method in mRNA, and it plays an important role in the occurrence and development of many cancers. This paper mainly discusses the role of m6A RNA methylation regulators in lung adenocarcinoma (LUAD) to identify novel prognostic biomarkers. The gene expression data of 19 m6A methylation regulators in LUAD patients and its relevant clinical parameters were extracted from The Cancer Genome Atlas (TCGA) database. We selected three significantly differentially expressed m6A regulators in LUAD to construct the risk signature, and evaluated its prognostic prediction efficiency using the receiver operating characteristic (ROC) curve. Kaplan–Meier survival analysis and Cox regression analysis were used to identify the independent prognostic significance of the risk signature. The ROC curve indicated that the area under the curve (AUC) was 0.659, which means that the risk signature had a good prediction efficiency. The results of the Kaplan–Meier survival analysis and Cox regression analysis showed that the risk score can be used as an independent prognostic factor for LUAD. In addition, we explored the differential signaling pathways and cellular processes related to m6A methylation regulators in LUAD.

scholarly journals Comprehensive Analysis of Inflammatory Response–Related Genes, and Prognosis and Immune Infiltration in Patients With Low-Grade Glioma

2021 ◽  
Vol 12 ◽  
Author(s):  
Tao Han ◽  
Zhifan Zuo ◽  
Meilin Qu ◽  
Yinghui Zhou ◽  
Qing Li ◽  
...  
Keyword(s):  
Regression Analysis ◽  
High Risk ◽  
Immune Cell ◽  
Risk Model ◽  
Cox Regression ◽  
Risk Group ◽  
High Risk Group ◽  
Low Grade ◽  
Immune Microenvironment ◽  
Cox Regression Analysis

Background: Although low-grade glioma (LGG) has a good prognosis, it is prone to malignant transformation into high-grade glioma. It has been confirmed that the characteristics of inflammatory factors and immune microenvironment are closely related to the occurrence and development of tumors. It is necessary to clarify the role of inflammatory genes and immune infiltration in LGG.Methods: We downloaded the transcriptome gene expression data and corresponding clinical data of LGG patients from the TCGA and GTEX databases to screen prognosis-related differentially expressed inflammatory genes with the difference analysis and single-factor Cox regression analysis. The prognostic risk model was constructed by LASSO Cox regression analysis, which enables us to compare the overall survival rate of high- and low-risk groups in the model by Kaplan–Meier analysis and subsequently draw the risk curve and survival status diagram. We analyzed the accuracy of the prediction model via ROC curves and performed GSEA enrichment analysis. The ssGSEA algorithm was used to calculate the score of immune cell infiltration and the activity of immune-related pathways. The CellMiner database was used to study drug sensitivity.Results: In this study, 3 genes (CALCRL, MMP14, and SELL) were selected from 9 prognosis-related differential inflammation genes through LASSO Cox regression analysis to construct a prognostic risk model. Further analysis showed that the risk score was negatively correlated with the prognosis, and the ROC curve showed that the accuracy of the model was better. The age, grade, and risk score can be used as independent prognostic factors (p &lt; 0.001). GSEA analysis confirmed that 6 immune-related pathways were enriched in the high-risk group. We found that the degree of infiltration of 12 immune cell subpopulations and the scores of 13 immune functions and pathways in the high-risk group were significantly increased by applying the ssGSEA method (p &lt; 0.05). Finally, we explored the relationship between the genes in the model and the susceptibility of drugs.Conclusion: This study analyzed the correlation between the inflammation-related risk model and the immune microenvironment. It is expected to provide a reference for the screening of LGG prognostic markers and the evaluation of immune response.

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