Signature identification based on immunogenic cell death-related lncRNAs to predict the prognosis and immune activity of patients with endometrial carcinoma
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View abstract on PubMed
Summary
This summary is machine-generated.This study identifies six long non-coding RNAs (lncRNAs) linked to immunogenic cell death (ICD) that can predict endometrial carcinoma (EC) patient prognosis. The developed risk model aids in classifying EC patients and guiding treatment strategies.
Area Of Science
- Oncology
- Molecular Biology
- Bioinformatics
Background
- Endometrial carcinoma (EC) is a common gynecologic malignancy requiring better classification for treatment and prognosis.
- Long non-coding RNAs (lncRNAs) and immunogenic cell death (ICD) are crucial in tumor progression, but their interplay in EC is not fully understood.
Purpose Of The Study
- To explore the role of ICD-related lncRNAs in EC.
- To establish a prognostic risk model based on ICD-related lncRNAs for EC patients.
- To investigate immune infiltration and function across prognostic groups.
Main Methods
- Utilized The Cancer Genome Atlas (TCGA) database for EC samples and clinical data.
- Developed a prognostic risk model using the least absolute shrinkage and selection operator (LASSO) method.
- Assessed immune cell infiltration using ssGSEA and TIMER algorithms; validated lncRNA expression via qPCR and in vitro/in vivo experiments.
Main Results
- Identified 16 prognostic ICD-related lncRNAs.
- Established a risk model using six lncRNAs (SCARNA9, FAM198B-AS1, FKBP14-AS1, FBXO30-DT, LINC01943, AL161431.1) that independently predicted EC prognosis.
- High-risk group showed lower overall survival and reduced immune cell infiltration compared to the low-risk group.
Conclusions
- A prognostic signature of six ICD-related lncRNAs was established for EC.
- The developed risk model effectively predicts patient prognosis and can inform treatment decisions.
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