Evidence map›Paper›PMID 37324090›Full record

ArticleJournal of thoracic disease2023

Identification of the potential ferroptosis key genes in lung cancer with bone metastasis.

Qin Zhou, Ting Xu, Jiajing Li, Jing Tan, Qixing Mao, Tengfei Liu, Lijun Wang, Minhao Zhang

Open access · diamondAbstract read
In one paragraph

Article in Journal of thoracic disease, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed, 1 pooled it
1.6field-weighted citation impact, top 16% of its field
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

4 citing papers in PubMed, 1 synthesis or guideline pooled it, 6 citations in OpenAlex.

  1. Pooled it
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  4. 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

8 authors at 4 institutions in 1 country.

Qin Zhou *Department of Anesthesiology, Jiangsu Cancer Hospital and Jiangsu Institute of Cancer Research and The Affiliated Cancer Hospital of Nanjing Medical University, Nanjing, China.
Ting Xu *Department of Respiratory Medicine, Nanjing Chest Hospital, Affiliated Nanjing Brain Hospital, Nanjing Medical University, Nanjing, China.
Jiajing Li *Department of Anesthesiology, Jiangsu Province Hospital of Chinese Medicine and Affiliated Hospital of Nanjing University of Chinese Medicine, Nanjing, China.
Jing TanDepartment of Anesthesiology, Jiangsu Cancer Hospital and Jiangsu Institute of Cancer Research and The Affiliated Cancer Hospital of Nanjing Medical University, Nanjing, China.
Qixing MaoDepartment of Anesthesiology, Jiangsu Cancer Hospital and Jiangsu Institute of Cancer Research and The Affiliated Cancer Hospital of Nanjing Medical University, Nanjing, China.
Tengfei LiuDepartment of Anesthesiology, Jiangsu Cancer Hospital and Jiangsu Institute of Cancer Research and The Affiliated Cancer Hospital of Nanjing Medical University, Nanjing, China.
Lijun WangDepartment of Anesthesiology, Jiangsu Cancer Hospital and Jiangsu Institute of Cancer Research and The Affiliated Cancer Hospital of Nanjing Medical University, Nanjing, China.
Minhao ZhangDepartment of Anesthesiology, Jiangsu Cancer Hospital and Jiangsu Institute of Cancer Research and The Affiliated Cancer Hospital of Nanjing Medical University, Nanjing, China.
Nanjing Medical University · CNJiangsu Cancer Hospital · CNJiangsu Province Hospital · CNNanjing Brain Hospital · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: To identify the potential key genes of ferroptosis in the pathogenesis of lung cancer with bone metastasis (LCBM) by bioinformatics analysis to provide new targets for treating LCBM and an indicator for early monitoring. Methods: We first obtained differentially expressed genes (DEGs) associated with ferroptosis from the Gene Expression Omnibus (GEO) database. MiRWalk 2.0 was used to predict the key microRNAs (miRNAs) and construct related gene-miRNA interaction networks. The functional enrichment analysis of key miRNAs was performed using the miEAA database. Finally, the clinical data of 105 lung cancer patients were retrospectively analyzed, and logistic regression analysis was conducted to assess the relationship between serum alkaline phosphatase (ALP), neuron-specific enolase (NSE), and bone metastasis in lung cancer patients, and a receiver operating characteristic (ROC) curve was drawn. Results: We identified 15 ferroptosis-related genes that were differentially expressed in lung cancer bone metastasis. GO and KEGG enrichment analyses suggested that these genes may affect the oxidative stress response, hypoxia response, rough endoplasmic reticulum, mitochondrial outer membrane, iron-sulfur cluster binding, virus receptor activity, central carbon metabolism in cancer, the interleukin-17 (IL-17) signaling pathway, and other aspects to participate in the occurrence and development of lung cancer bone metastasis. Among the 105 lung cancer patients included in the study, 39 cases had bone metastasis, and the incidence rate was 37.14%. A high Eastern Cooperative Oncology Group (ECOG) score and serum ALP and NSE overexpression were associated with bone metastasis in patients with lung cancer. By assessing the risk of bone metastasis in patients with lung cancer, we found that the Area Under Curves (AUCs) of serum ALP and NSE alone and combined were >0.70. Conclusions: The differentially expressed ferroptosis-related genes and predicted miRNA regulatory network in lung cancer bone metastasis and the related functional enrichment analysis provide new targets for the treatment of lung cancer bone metastasis. At the same time, from a serological perspective, it was found that early monitoring of serum ALP and NSE expression in patients with lung cancer could be considered to assess the risk of bone metastasis in the future.

Indexed as

a target pointbioinformatics analysisbone metastasisiron deathLung cancer

Identifiers

PMID37324090
PMCPMC10267905
OpenAlexW4380075652

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LicenceCC BY-NC-ND
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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.