Evidence map›Paper›PMID 41816490›Full record

ArticleJournal of thoracic disease2026

SCARNA20 influences the occurrence and development of lung cancer by inhibiting tumor cell proliferation, migration, and invasion.

Yuanhao Li, Jin Zhang, Qi Chen, Haoshuai Yang, Peihang Xu, Yue Zhao, Di Li, Qianli Ma, Deruo Liu, Chaoyang Liang

Abstract read
In one paragraph

Article in Journal of thoracic disease, 2026. 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

10 authors.

Yuanhao LiDepartment of Thoracic Surgery, Capital Medical University China-Japan Friendship Hospital, Beijing, China.
Jin ZhangDepartment of Thoracic Surgery, China-Japan Friendship Hospital, Beijing, China.
Qi ChenDepartment of Thoracic Surgery, Capital Medical University China-Japan Friendship Hospital, Beijing, China.
Haoshuai YangDepartment of Thoracic Surgery, China-Japan Friendship Hospital, Beijing, China.
Peihang XuDepartment of Thoracic Surgery, China-Japan Friendship Hospital, Beijing, China.
Yue ZhaoDepartment of Thoracic Surgery, China-Japan Friendship Hospital, Beijing, China.
Di LiDepartment of Thoracic Surgery, China-Japan Friendship Hospital, Beijing, China.
Qianli MaDepartment of Thoracic Surgery, China-Japan Friendship Hospital, Beijing, China.
Deruo LiuDepartment of Thoracic Surgery, China-Japan Friendship Hospital, Beijing, China.
Chaoyang LiangDepartment of Thoracic Surgery, China-Japan Friendship Hospital, Beijing, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Non-small cell lung cancer (NSCLC) remains a leading cause of cancer-related mortality with limited treatment efficacy. Small nucleolar RNAs (snoRNAs) have emerged as potential key players in tumorigenesis, but their roles in NSCLC are largely unexplored. Our previous study identified SCARNA20 as significantly downregulated in NSCLC tissues, suggesting a potential tumor-suppressive function. Thus, in order to further explore the role of SCARNA20 in NSCLC, we conducted this study to verify its function. Methods: The biological functions of SCARNA20 were investigated Results: Overexpression of SCARNA20 significantly inhibited NSCLC cell proliferation, colony formation, migration, and invasion Conclusions: SCARNA20 acts as a tumor suppressor in NSCLC, inhibiting malignant phenotypes including cell proliferation, migration, and invasion, both

Indexed as

lung cancernon-coding RNASCARNA20small nucleolar RNAs (snoRNAs)

Identifiers

PMID41816490
PMCPMC12972830

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
Read underepoch 390

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.