ArticleOncology letters2025
BDNF is a prognostic biomarker involved in the immune infiltration of lung adenocarcinoma and associated with programmed cell death.
Article in Oncology letters, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
1 citing paper in PubMed.
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Authors and funding
11 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
It is well established that genes associated with cell death can serve as prognostic markers for patients with cancer. Programmed cell death (PCD) is known to play a role in cancer cell apoptosis and antitumor immunity. With the continuous discovery of new forms of PCD, the roles of PCD in lung adenocarcinoma (LUAD) require ongoing evaluation. In the present study, mRNA expression data and clinical information associated with 15 forms of PCD were extracted from publicly available databases and systematically analyzed. Utilizing these data, a robust risk prediction model was established that incorporates six PCD-related genes (PRGs). Datasets from the Gene Expression Omnibus database were employed to validate the six genes exhibiting risk-associated characteristics. The PRG-based model reliably predicted the prognosis of patients with LUAD, with the high-risk group showing a poor prognosis, reduced levels of immune infiltration molecules and diminished expression of human leukocyte antigens. Additionally, the relationships among PRGs, somatic mutations, tumor stemness index and immune infiltration were assessed. Based on these risk characteristics, a nomogram was constructed, patient stratification was performed, small-molecule drug candidates were predicted, and somatic mutations and chemotherapy responses were analyzed. Furthermore, reverse transcription-quantitative PCR was used to assess the expression of PDGs
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