Evidence map›Paper›PMID 40205015›Full record

ArticleOncogene2025

Transcriptome-wide association study of alternative polyadenylation identifies susceptibility genes in non-small cell lung cancer.

Xiaohang Xu, Sicong Wang, Hanyi Zhou, Qilong Tan, Zeyong Lang, Yun Zhu, Huadi Yuan, Zixiang Wu, Ling Zhu, Kejia Hu and 4 more

Abstract read
In one paragraph

Article in Oncogene, 2025. 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. Article
  2. Article
  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

14 authors.

Xiaohang XuCenter of Clinical Big Data and Analytics of the Second Affiliated Hospital and School of Public Health, Zhejiang University School of Medicine, Hangzhou, China.
Sicong WangCenter of Clinical Big Data and Analytics of the Second Affiliated Hospital and School of Public Health, Zhejiang University School of Medicine, Hangzhou, China.
Hanyi ZhouCenter of Clinical Big Data and Analytics of the Second Affiliated Hospital and School of Public Health, Zhejiang University School of Medicine, Hangzhou, China.
Qilong TanCenter of Clinical Big Data and Analytics of the Second Affiliated Hospital and School of Public Health, Zhejiang University School of Medicine, Hangzhou, China.
Zeyong LangCenter of Clinical Big Data and Analytics of the Second Affiliated Hospital and School of Public Health, Zhejiang University School of Medicine, Hangzhou, China.
Yun ZhuCenter of Clinical Big Data and Analytics of the Second Affiliated Hospital and School of Public Health, Zhejiang University School of Medicine, Hangzhou, China.
Huadi YuanDepartment of Thoracic Surgery, Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China.
Zixiang WuDepartment of Thoracic Surgery, Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China.
Ling ZhuDepartment of Thoracic Surgery, Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China.
Kejia HuCenter of Clinical Big Data and Analytics of the Second Affiliated Hospital and School of Public Health, Zhejiang University School of Medicine, Hangzhou, China.
Wenyuan LiCenter of Clinical Big Data and Analytics of the Second Affiliated Hospital and School of Public Health, Zhejiang University School of Medicine, Hangzhou, China.
Dan ZhouCenter of Clinical Big Data and Analytics of the Second Affiliated Hospital and School of Public Health, Zhejiang University School of Medicine, Hangzhou, China.ORCID http://orcid.org/0000-0002-5313-8164
Ming WuDepartment of Thoracic Surgery, Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China.
Xifeng WuCenter of Clinical Big Data and Analytics of the Second Affiliated Hospital and School of Public Health, Zhejiang University School of Medicine, Hangzhou, China. xifengw@zju.edu.cn.ORCID http://orcid.org/0000-0003-2980-8129

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Alternative polyadenylation (APA) plays a crucial role in cancer development and prognosis. However, the molecular characteristics of APA related to non-small cell lung cancer (NSCLC) susceptibility remain understudied, especially in East Asian populations. In this study, we constructed an atlas of APA-regulated 3' untranslated region (3'UTR) and profiled its genetic regulation in 747 lung tissue samples (including tumors and paired normal tissues) from 417 NSCLC Chinese patients. We verified a significant global shortening of 3'UTRs in tumor samples compared to normal samples and underscored the value of APA-regulation as a prognostic marker. The 3'UTR APA quantitative trait loci (3'aQTL) was identified by regressing the percentage of distal poly(A) site usage index (PDUI) value on genetic variants. We found that a significant proportion 3'aQTLs are independent of genetic regulation of expression and are specific in Chinese. We also conducted a 3'UTR APA transcriptome-wide association study (3'aTWAS) by integrating the APA regulation atlas with a genome-wide association study (GWAS) for NSCLC involving 7035 cases and 185,413 cancer-free controls. We identified NSCLC-associated genes, highlighting TUBB, TEAD3, and PPP1R10. Combining the consistent results from colocalization analysis, differential APA analysis, and survival analysis, we provide novel evidence for the role TUBB APA regulation in NSCLC and identified potential upstream regulators. Overall, our study profiled the APA regulation and highlighted the substantial role of APA in NSCLC carcinogenesis and prognosis in East Asian populations.

Indexed as

Carcinoma, Non-Small-Cell LungGenetic Predisposition to DiseaseLung NeoplasmsPolyadenylationTranscriptome3' Untranslated RegionsFemaleGene Expression Regulation, NeoplasticGenome-Wide Association StudyHumansMaleMiddle AgedPolymorphism, Single NucleotidePrognosisQuantitative Trait Loci3' Untranslated Regions

Identifiers

PMID40205015
PMCPMC12183086

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.