ArticleFrontiers in genetics2022
Comprehensive Analysis of Programmed Cell Death Signature in the Prognosis, Tumor Microenvironment and Drug Sensitivity in Lung Adenocarcinoma.
Article in Frontiers in genetics, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.
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Who cites it
13 citing papers in PubMed.
- LRP11 as a potential predictor of poor prognosis and immune suppression in lung adenocarcinoma.Discover oncology · 2025Article
- Exploratory Analysis of Regulated Cell Death-Related Genes as Potential Prognostic Biomarkers in Endometrial Carcinoma.Biomedicines · 2025Article
- Development of a machine learning-derived programmed cell death index for prognostic prediction and immune insights in colorectal cancer.Discover oncology · 2025Article
- BDNF is a prognostic biomarker involved in the immune infiltration of lung adenocarcinoma and associated with programmed cell death.Oncology letters · 2025Article
- Multi‑omics identification of a novel signature for serous ovarian carcinoma in the context of 3P medicine and based on twelve programmed cell death patterns: a multi-cohort machine learning study.Molecular medicine (Cambridge, Mass.) · 2025Article
- Integrated multi-optosis model for pan-cancer candidate biomarker and therapy target discovery.Frontiers in bioinformatics · 2025Article
- Identification and analysis of prognostic immune cell homeostasis characteristics in lung adenocarcinoma.The clinical respiratory journal · 2024Article
- A programmed cell death-related gene signature to predict prognosis and therapeutic responses in liver hepatocellular carcinoma.Discover oncology · 2024Article
- Omada: robust clustering of transcriptomes through multiple testing.GigaScience · 2024Article
- Leveraging diverse cell-death patterns to predict the clinical outcome of immune checkpoint therapy in lung adenocarcinoma: Based on muti-omics analysis and vitro assay.Oncology research · 2023Article
- Construction of IL-1 signalling pathway correlation model in lung adenocarcinoma and association with immune microenvironment prognosis and immunotherapy: Multi-data validation.Frontiers in immunology · 2023Article
- Identification of cuproptosis-related subtypes in lung adenocarcinoma and its potential significance.Frontiers in pharmacology · 2022Article
- The characterization of tumor microenvironment infiltration and the construction of predictive index based on cuproptosis-related gene in primary lung adenocarcinoma.Frontiers in oncology · 2022Article
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8 authors.
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Abstract
Programmed cell death (PCD) is a process that regulates the homeostasis of cells in the body, and it plays an important role in tumor immunity. However, the expression profile and clinical characteristics of PCD-related genes remain unclear. In this study, we comprehensively analysed the PCD genes with the tumor microenvironment (TME), drug sensitivity, immunothearapy response, and evaluated their prognostic value through systematic bioinformatics methods.We identified 125 PCD-related regulatory factors, which were expressed differently in lung adenocarcinoma (LUAD) and normal lung tissues. 32 PCD related prognostic genes associated with LUAD were identified by univariate Cox analysis. 23 PCD-related gene signature was constructed, and all LUAD patients in the Cancer Genome Atlas (TCGA) dataset were stratified as low-risk or high-risk groups according to the risk score. This signature had a powerful prognostic value, which was validated in three independent data sets and clinical subtypes. Additionally, it has unique properties in TME. Further analysis showed that different risk groups have different immune cell infiltration, immune inflammation profile, immune pathways, and immune subtypes. In addition, the low-risk group had a better immunotherapy response with higher levels of multiple immune checkpoints and lower Tumor immune dysfunction and exclusion (TIDE) score, while the high-risk group was sensitive to multiple chemotherapeutic drugs because of its lower IC50. In short, this is the first model to predict the prognosis and immunological status of LUAD patients based on PCD-related genes. It may be used as a predictor of immunotherapy response to achieve customized treatment of LUAD.
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