Evidence map›Paper›PMID 41121251›Full record

ReviewCancer cell international2025

Ferroptosis and non-coding RNAs in lung cancer: exploring molecular mechanisms and diagnostic/therapeutic implications.

Hedong Xue, Melika Malek, Liangyu Li

Abstract readReview
In one paragraph

Review in Cancer cell international, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Review
  2. 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

3 authors.

Hedong XueDepartment of Respiratory, The First People's Hospital of Pinghu, Pinghu, 314200, Zhejiang, China.
Melika MalekShahid Beheshti University of Medical Sciences, Tehran, Iran. melikamalek862@gmail.com.
Liangyu LiCancer Center, Department of Pulmonary and Critical Care Medicine, Zhejiang Provincial People's Hospital (Affiliated People's Hospital), Hangzhou Medical College, Hangzhou, 310005, Zhejiang, China. lly83618@163.com.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Lung cancer is the second most prevalent type of cancer on a global scale, and is widely known for being the deadliest. Revealing the fundamental molecular mechanisms of this condition has the potential to unlock fresh possibilities and avenues for managing it. Ferroptosis is a newly discovered type of controlled cell death that distinguishes itself from traditional forms of programmed cell death, specifically apoptosis and necrosis, through its distinct biochemical and structural characteristics. Changes made to the mechanism that regulates ferroptosis can have a significant influence on the development of various illnesses, such as, though not limited to, lung cancer. Based on scientific studies, it has been proven that cancer cells possess a significant capability to inhibit ferroptosis, leading to their continuous growth and survival. The presence of non-coding RNAs has a profound influence on controlling a wide range of cellular functions, with a particular focus on cancer. They have been closely associated with all key features of lung cancer. Fresh findings have indicated that these particles also have the task of controlling ferroptosis. Thus, the use of non-coding RNA as a therapeutic strategy offers a potentially effective option for regulating ferroptosis in the management of cancer. The main focus of this overview is on ncRNAs and their function in controlling ferroptosis, specifically within the context of lung cancer.

Indexed as

Cell deathFerroptosisLung cancerMolecular mechanismsNon-coding RNAs

Identifiers

PMID41121251
PMCPMC12542376

What OpenQuestion holds

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LicenceCC BY-NC-ND
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Registered trials

None linked

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.