Zinc Finger Protein-Based Prognostic Signature Predicts Survival in Lung Adenocarcinoma
- Lihui Yu 1, Yahui Zhou 2, Jingyu Chen 3
- Lihui Yu 1, Yahui Zhou 2, Jingyu Chen 3
- 1Wuxi School of Medicine, Jiangnan University, Wuxi 214122, China.
- 2Department of Neonatology, Affiliated Children's Hospital of Jiangnan University, Wuxi Children's Hospital, Wuxi 214023, China.
- 3Wuxi Lung Transplant Center, Wuxi People's Hospital Affiliated to Nanjing Medical University, Wuxi 214023, China.
- 0Wuxi School of Medicine, Jiangnan University, Wuxi 214122, China.
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View abstract on PubMed
Summary
This summary is machine-generated.This study identifies 21 zinc finger proteins (ZNFs) as key predictors of survival in lung adenocarcinoma (LUAD). A developed risk score model using these ZNFs can distinguish between high-risk and low-risk patients, aiding in treatment strategies.
Area Of Science
- Oncology
- Genetics
- Bioinformatics
Background
- Zinc finger proteins (ZNFs) are critical regulators of gene expression implicated in cancer development.
- Their specific roles in lung adenocarcinoma (LUAD) pathogenesis are not fully understood.
- Understanding ZNF functions is crucial for identifying new therapeutic targets.
Purpose Of The Study
- To investigate the prognostic significance of zinc finger proteins in lung adenocarcinoma.
- To develop a predictive model for patient survival based on ZNF expression.
- To identify potential molecular targets for LUAD treatment.
Main Methods
- Utilized TCGA and GEO datasets for transcriptional data analysis.
- Applied univariate Cox regression and LASSO algorithm for marker selection and risk score model development.
- Validated findings through multivariable Cox regression and cell-based expression analysis (qRT-PCR).
Main Results
- A risk score model incorporating 21 ZNFs was developed to predict clinical outcomes in LUAD.
- Patients in the low-risk group exhibited significantly better survival rates than those in the high-risk group.
- Transcriptional profiles of key ZNFs showed concordance between bioinformatics data and experimental cell models.
Conclusions
- The developed prognostic framework utilizing ZNFs demonstrates significant biomarker potential for LUAD survival prediction.
- This research offers novel insights into the molecular mechanisms of LUAD.
- Identified ZNFs represent potential targets for developing innovative therapeutic strategies against lung adenocarcinoma.
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