Evidence map›Paper›PMID 41929079›Full record

ArticlebioRxiv : the preprint server for biology2026

Single-cell lung eQTL dataset of Asian never-smokers highlights the roles of alveolar cells in lung cancer etiology.

Thong Luong, Jinhu Yin, Bolun Li, Ju Hye Shin, Elelta Sisay, Sama Mikhail, Fei Qin, Samuel Anyaso-Samuel, Alexander Kane, Alyxandra Golden and 19 more

Abstract readPreprint
PubMed Full text at PMC Publisher
In one paragraph

Article in bioRxiv : the preprint server for biology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

29 authors.

Thong LuongDivision of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA.ORCID 0000-0001-7534-1289
Jinhu YinDivision of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA.
Bolun LiDivision of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA.
Ju Hye ShinDepartment of Internal Medicine, Yonsei University College of Medicine, Seoul, Republic of Korea.
Elelta SisayDivision of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA.
Sama MikhailDivision of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA.
Fei QinDivision of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA.
Samuel Anyaso-SamuelDivision of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA.
Alexander KaneDivision of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA.
Alyxandra GoldenDivision of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA.
Jia LiuCancer Genomics Research Laboratory, Frederick National Laboratory for Cancer Research, Frederick, MD, USA.
Chia Han LeeDivision of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA.
Zixuan Eleanor ZhangDepartment of Biostatistics, Epidemiology and Informatics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA.
Yoon Soo ChangDepartment of Internal Medicine, Yonsei University College of Medicine, Seoul, Republic of Korea.
Jinyoung ByunDepartment of Internal Medicine, University of New Mexico, Albuquerque, NM, USA.
Younghun HanDepartment of Internal Medicine, University of New Mexico, Albuquerque, NM, USA.
Maria Teresa LandiDivision of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA.
Nicholas MancusoCenter for Genetic Epidemiology, Department of Population and Public Health Sciences, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA.
Nicholas E BanovichDivision of Bioinnovation and Genome Sciences, Translational Genomics Research Institute (TGen), Phoenix, AZ, USA.
Nathaniel RothmanDivision of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA.
Christopher AmosDepartment of Internal Medicine, University of New Mexico, Albuquerque, NM, USA.
Qing LanDivision of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA.
Kai YuDivision of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA.
Tongwu ZhangDivision of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA.
Erping LongInstitute of Basic Medical Sciences, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China.
Jianxin ShiDivision of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA.
Jin Gu LeeDepartment of Thoracic and Cardiovascular Surgery, Yonsei University College of Medicine, Seoul, Republic of Korea.
Eun Young KimDepartment of Internal Medicine, Yonsei University College of Medicine, Seoul, Republic of Korea.
Jiyeon ChoiDivision of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA.ORCID 0000-0002-0955-2384

Funding

Translating Molecular and Clinical Data to Population Lung Cancer Risk AssessmentU19CA203654 · NCI · UNIVERSITY OF NEW MEXICO HEALTH SCIS CTR · PI Rayjean J. Hung · 2017 to 2026
$23.7M
NCI NIH HHS U19 CA203654
6 · The paper itself

Abstract

Single-cell expression quantitative trait loci (sc-eQTL) analyses are powerful in identifying context-specific susceptibility genes from genome-wide association studies (GWAS) loci. However, few studies have comprehensively investigated cells of lung cancer origin in non-European populations. Here, we built a lung sc-eQTL dataset from 129 Korean women never-smokers with epithelial cell enrichment. eQTL mapping identified 2,229 genes with an eQTL in 33 cell types, including East Asian-specific findings when compared to predominantly European datasets. Integration with single-cell chromatin accessibility data demonstrated an enrichment of cell-type specific eQTLs in cell-type matched candidate enhancers, while shared eQTLs were more frequently found near promoters. Colocalization and transcriptome-wide association study unveiled 36 susceptibility genes from 22 cell types in 22 lung cancer loci, including 10 loci not achieving genome-wide significance in prior GWAS. Around 47% of these genes were from cells of the alveoli, underscoring their importance, especially in lung adenocarcinoma (LUAD) susceptibility. Focusing on the trajectory of alveolar epithelial cell regeneration, we detected 785 cell-state-interacting QTLs, which overlapped with 28% (10) of the identified susceptibility genes. Finally, we experimentally validated East Asian- and alveolar type 2 cell-specific eQTL of

Identifiers

PMID41929079
PMCPMC13041904

What OpenQuestion holds

Textmetadata
LicenceCC0
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.