Evidence map›Paper›PMID 35102130›Full record

ArticleMedical science monitor : international medical journal of experimental and clinical research2022

A Novel Predictive Model Incorporating Ferroptosis-Related Gene Signatures for Overall Survival in Patients with Lung Adenocarcinoma.

Yuli Wang, Yanbin Pan, Jianchun Wu, Yingbin Luo, Zhihong Fang, Rongzhong Xu, Wenjing Teng, Min Chen, Yan Li

Abstract read
In one paragraph

Article in Medical science monitor : international medical journal of experimental and clinical research, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Genetic profile of ferroptosis in non-small cell lung carcinoma and pharmaceutical options for ferroptosis induction.Clinical & translational oncology : official publication of the Federation of Spanish Oncology Societies and of the National Cancer Institute of Mexico · 2025
    Review
  2. Regulation of Ferroptosis in Lung Adenocarcinoma.International journal of molecular sciences · 2023
    Review
  3. 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

9 authors.

Yuli WangDepartment of Oncology, Shanghai Municipal Hospital of Traditional Chinese Medicine, Shanghai University of Traditional Chinese Medicine, Shanghai, China (mainland).ORCID 0000-0003-1462-460X
Yanbin PanDepartment of Oncology, Shanghai Municipal Hospital of Traditional Chinese Medicine, Shanghai University of Traditional Chinese Medicine, Shanghai, China (mainland).
Jianchun WuDepartment of Oncology, Shanghai Municipal Hospital of Traditional Chinese Medicine, Shanghai University of Traditional Chinese Medicine, Shanghai, China (mainland).
Yingbin LuoDepartment of Oncology, Shanghai Municipal Hospital of Traditional Chinese Medicine, Shanghai University of Traditional Chinese Medicine, Shanghai, China (mainland).
Zhihong FangDepartment of Oncology, Shanghai Municipal Hospital of Traditional Chinese Medicine, Shanghai University of Traditional Chinese Medicine, Shanghai, China (mainland).
Rongzhong XuDepartment of Oncology, Shanghai Municipal Hospital of Traditional Chinese Medicine, Shanghai University of Traditional Chinese Medicine, Shanghai, China (mainland).
Wenjing TengDepartment of Oncology, Shanghai Municipal Hospital of Traditional Chinese Medicine, Shanghai University of Traditional Chinese Medicine, Shanghai, China (mainland).
Min ChenDepartment of Oncology, Shanghai Municipal Hospital of Traditional Chinese Medicine, Shanghai University of Traditional Chinese Medicine, Shanghai, China (mainland).
Yan LiDepartment of Oncology, Shanghai Municipal Hospital of Traditional Chinese Medicine, Shanghai University of Traditional Chinese Medicine, Shanghai, China (mainland).

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

BACKGROUND Lung adenocarcinoma (LUAD) is the predominant histological type of lung cancer with high morbidity and mortality. Ferroptosis is regarded as a new pattern of programmed cell death concerned with the progression of lung cancer characterized by lipid peroxidation. Nevertheless, the prognostic role of ferroptosis-related genes for LUAD warrant to be explored. MATERIAL AND METHODS RNA sequencing and relevant clinical patient data were obtained from public-access databanks. A prognostic model was constructed through the LASSO Cox regression in the cancer genome atlas cohort. The diagnostic value of the prognostic model was further evaluated in the gene expression omnibus cohort. RESULTS Most of the ferroptosis-related genes (69.9%) were differentially expressed between tumor and adjacent non-cancerous tissues. 43 differentially expressed genes showed a close association with the prognosis of LUAD patients (adjusted p-value <0.05). An 18-gene signature was built and applied to assign patients into high vs low-risk groups. Compared with the high-risk group, patients defined as the low-risk group suffered significantly prolonged OS. Both uni- and multivariate analyses demonstrated that the signature-based score served as a crucial role in influencing the OS of LUAD patients (hazard ratio >1, p<0.001). The immunity-related signaling pathway was enriched in the functional analysis and the infiltration of the immune cells showed a great difference between groups. CONCLUSIONS The predictive model could be applied for prognostic prediction for LUAD. Targeting ferroptosis could be a possible curative strategy against LUAD, and immunomodulation may be one of the potential mechanisms.

Indexed as

Adenocarcinoma of LungBiomarkers, TumorCohort StudiesFerroptosisHumansLung NeoplasmsSequence Analysis, RNASurvival AnalysisBiomarkers, Tumor

Identifiers

PMID35102130
PMCPMC8817619

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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.