Construction of a Novel Mitochondria-Associated Gene Model for Assessing ESCC Immune Microenvironment and Predicting Survival

May 8, 2024Journal of microbiology and biotechnology

New Mitochondria-Linked Gene Model for Evaluating Immune Environment and Predicting Survival in Esophageal Cancer

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Abstract

The mitochondria-associated risk (MAR) model identified significant differences in immune infiltration and tumor microenvironment characteristics between high- and low-risk groups in esophageal squamous cell carcinoma (ESCC).

A total of 91 transcriptome expression profiles were analyzed to identify genes correlated with ESCC.
The MAR model constructed through statistical analysis showed a strong association with risk scores and common immunological checkpoints.
In vitro experiments indicated that knockdown of the gene TYMS significantly reduced the proliferation and invasion of ESCC cells.
Specific drugs demonstrated varying effectiveness based on risk classification, with AZD1332 and AZD7762 favored for low-risk patients.
The MAR model may serve as a prognostic biomarker, suggesting potential for personalized treatment strategies for ESCC.

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Esophageal squamous cell carcinoma (ESCC) is among the most common malignant tumors of the digestive tract, with the sixth highest fatality rate worldwide. The ESCC-related dataset, GSE20347, was downloaded from the Gene Expression Omnibus (GEO) database, and weighted gene co-expression network analysis was performed to identify genes that are highly correlated with ESCC. A total of 91 transcriptome expression profiles and their corresponding clinical information were obtained from The Cancer Genome Atlas database. A mitochondria-associated risk (MAR) model was constructed using the least absolute shrinkage and selection operator Cox regression analysis and validated using GSE161533. The tumor microenvironment and drug sensitivity were explored using the MAR model. Finally, in vitro experiments were performed to analyze the effects of hub genes on the proliferation and invasion abilities of ESCC cells. To confirm the predictive ability of the MAR model, we constructed a prognostic model and assessed its predictive accuracy. The MAR model revealed substantial differences in immune infiltration and tumor microenvironment characteristics between high- and low-risk populations and a substantial correlation between the risk scores and some common immunological checkpoints. AZD1332 and AZD7762 were more effective for patients in the low-risk group, whereas Entinostat, Nilotinib, Ruxolutinib, and Wnt.c59 were more effective for patients in the high-risk group. Knockdown of TYMS significantly inhibited the proliferation and invasive ability of ESCC cells in vitro. Overall, our MAR model provides stable and reliable results and may be used as a prognostic biomarker for personalized treatment of patients with ESCC.

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Construction of a Novel Mitochondria-Associated Gene Model for Assessing ESCC Immune Microenvironment and Predicting Survival

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