Evidence map›Paper›PMID 40041412›Full record

ArticleOncology letters2025

BDNF is a prognostic biomarker involved in the immune infiltration of lung adenocarcinoma and associated with programmed cell death.

Jiangnan Xia, Wei Zhuo, Lilan Deng, Sheng Yin, Shuangqin Tang, Lijuan Yi, Chuanping Feng, Xiangyun Zhong, Zhijun He, Biqiang Sun and 1 more

Abstract read
In one paragraph

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.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

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.

2 · The registry

The trial behind it

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.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

11 authors.

Jiangnan XiaCollege of Pharmacy, Hunan Traditional Chinese Medical College, Zhuzhou, Hunan 412012, P.R. China.
Wei ZhuoCollege of Pharmacy, Hunan Traditional Chinese Medical College, Zhuzhou, Hunan 412012, P.R. China.
Lilan DengCollege of Pharmacy, Hunan Traditional Chinese Medical College, Zhuzhou, Hunan 412012, P.R. China.
Sheng YinCollege of Pharmacy, Hunan Traditional Chinese Medical College, Zhuzhou, Hunan 412012, P.R. China.
Shuangqin TangCollege of Pharmacy, Hunan Traditional Chinese Medical College, Zhuzhou, Hunan 412012, P.R. China.
Lijuan YiCollege of Pharmacy, Hunan Traditional Chinese Medical College, Zhuzhou, Hunan 412012, P.R. China.
Chuanping FengCollege of Pharmacy, Hunan Traditional Chinese Medical College, Zhuzhou, Hunan 412012, P.R. China.
Xiangyun ZhongCollege of Pharmacy, Hunan Traditional Chinese Medical College, Zhuzhou, Hunan 412012, P.R. China.
Zhijun HeCollege of Pharmacy, Hunan Traditional Chinese Medical College, Zhuzhou, Hunan 412012, P.R. China.
Biqiang SunCollege of Pharmacy, Hunan Traditional Chinese Medical College, Zhuzhou, Hunan 412012, P.R. China.
Chi ZhangDepartment of Oncology, Dongfang Hospital, Beijing University of Chinese Medicine, Beijing 100078, P.R. China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

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

Indexed as

bioinformaticsimmune infiltrationlung cancerprognostic modelprogrammed cell death

Identifiers

PMID40041412
PMCPMC11877015

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.