Dataset Information

Construction of novel hypoxia-related gene model for prognosis and tumor microenvironment in endometrial carcinoma.

ABSTRACT:

Introduction

Endometrial cancer is currently one of the three most common female reproductive cancers, which seriously threatens women's lives and health. Hypoxia disrupts the tumor microenvironment, thereby affecting tumor progression and drug resistance.

Methods

We established hypoxia-related gene model to predict patient prognosis and 1-, 3-, and 5-year overall survival rates. Then, the expression level of hypoxia-related genes and survival data were extracted for comprehensive analysis by Cox regression analysis, and the model was established.

Results

We analyzed the survival and prognosis of patients in the high and low-risk groups. The Kaplan-Meier curve showed that the low-risk group is associated with a better survival rate. The 1-, 3-, and 5-year AUC values of the model were 0.680, 0.698, and 0.687, respectively. Finally, we found that LAG3 may be a potential immune checkpoint for endometrial cancer.

Conclusion

We found four hypoxia-related genes (ANXA2, AKAP12, NR3C1, and GPI) associated with prognosis. The hypoxia-related gene model can also predict prognosis and tumor microenvironment in endometrial cancer.

SUBMITTER: Chen J

PROVIDER: S-EPMC9797861 | biostudies-literature | 2022

REPOSITORIES: biostudies-literature

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Publications

Construction of novel hypoxia-related gene model for prognosis and tumor microenvironment in endometrial carcinoma.

Chen Junfeng J Wang Guocheng G Zhang Donghai D Luo Xiaomei X Zhang Da D Zhang Yongli Y

Frontiers in endocrinology 20221215

<h4>Introduction</h4>Endometrial cancer is currently one of the three most common female reproductive cancers, which seriously threatens women's lives and health. Hypoxia disrupts the tumor microenvironment, thereby affecting tumor progression and drug resistance.<h4>Methods</h4>We established hypoxia-related gene model to predict patient prognosis and 1-, 3-, and 5-year overall survival rates. Then, the expression level of hypoxia-related genes and survival data were extracted for comprehensive ...[more]

PMID: 36589842

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Project description:Background Hepatocellular carcinoma (HCC) is one of the most common malignant tumors in the world with high morbidity and mortality. Identifying an effective marker for predicting the prognosis and therapeutic response is extremely meaningful. Angiogenesis-related genes (ARGs) play important roles in the tumor progression and immune-suppressive microenvironment formation. Methods The differential expressed ARGs associated with the prognosis of HCC were identified in the TCGA dataset. Univariate Cox and least absolute shrinkage selection operator (LASSO) regression were applied to construct a ARGs Scoring model. The prognostic value of the ARGs Scoring model was assessed by Cox regression, Kaplan-Meier (KM) and ROC curve analyses. Then the model was further validated in an external dataset, ICGC dataset. The patients were split into two groups based on the ARGs Score and the clinical features were compared. TIMER, CIBERSORT and xCell algorithms were utilized to analyze the correlation between the ARGs Score and tumor immune microenvironment (TIME). Furthermore, we analyzed the efficacy of the model in predicting the therapeutic response for immunotherapy, targeted therapy and TACE treatment in different cohorts. Results A total of 97 differential expressed ARGs were identified relating to the prognosis of HCC patients from the TCGA dataset. Then the ARGs Scoring model based on a 9-gene signature was constructed using the Cox and LASSO regression analyses. Higher ARGs Score had a poor clinical outcome and was considered to be an independent prognostic predictor for HCC in the multivariate Cox analysis. The ARGs Score was related to the enrichment of various immune cells, such as CD4+ T cells, Treg, macrophage, neutrophil and dendritic cells, exhibiting a more immunosuppressive phenotype. Higher ARGs Score was correlated with higher expression of immune checkpoint genes and poor response to immunotherapy. Furthermore, higher ARGs Score indicated poor therapeutic response in the sorafenib and TACE treatment cohorts, individually. Conclusions The ARGs Scoring model exhibited robust predictive value for the prognosis and TIME for HCC patients. Higher ARGs Score indicated poor therapeutic response of the immunotherapy, sorafenib and TACE treatment. The ARGs Scoring model could be used as a biomarker to help physicians to develop more individualized treatment for HCC patients.

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Dataset Information

Construction of novel hypoxia-related gene model for prognosis and tumor microenvironment in endometrial carcinoma.

Introduction

Methods

Results

Conclusion

Publications

Construction of novel hypoxia-related gene model for prognosis and tumor microenvironment in endometrial carcinoma.

Similar Datasets

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