Evidence map›Paper›PMID 41605901›Full record

ArticleCell discovery2026

Integrative clinico-molecular analysis reveals actionable subtypes and biomarkers in lung adenocarcinoma.

Jun Shang, He Jiang, Yueren Yan, Yue Zhao, Jingcheng Yang, Han Han, Hui Yuan, Leming Shi, Yuanting Zheng, Haiquan Chen

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Cell discovery, 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

10 authors.

Jun Shang *Departments of Thoracic Surgery and State Key Laboratory of Genetic Engineering, Fudan University Shanghai Cancer Center, Shanghai, China. shangjunv@163.com.ORCID http://orcid.org/0000-0002-5767-1492
He Jiang *Center for Precision Cancer Medicine & Translational Research, Key Laboratory of Cancer Prevention and Therapy, National Clinical Research Center for Cancer, Tianjin's Clinical Research Center for Cancer, Tianjin Medical University Cancer Institute & Hospital, Tianjin, China.ORCID http://orcid.org/0000-0003-0673-0605
Yueren Yan *Departments of Thoracic Surgery and State Key Laboratory of Genetic Engineering, Fudan University Shanghai Cancer Center, Shanghai, China.
Yue Zhao *Departments of Thoracic Surgery and State Key Laboratory of Genetic Engineering, Fudan University Shanghai Cancer Center, Shanghai, China.ORCID http://orcid.org/0000-0003-3645-2634
Jingcheng Yang *State Key Laboratory of Genetic Engineering, School of Life Sciences, Human Phenome Institute and Shanghai Cancer Center, Fudan University, Shanghai, China.
Han HanDepartments of Thoracic Surgery and State Key Laboratory of Genetic Engineering, Fudan University Shanghai Cancer Center, Shanghai, China.
Hui YuanDepartments of Thoracic Surgery and State Key Laboratory of Genetic Engineering, Fudan University Shanghai Cancer Center, Shanghai, China.
Leming ShiState Key Laboratory of Genetic Engineering, School of Life Sciences, Human Phenome Institute and Shanghai Cancer Center, Fudan University, Shanghai, China.ORCID http://orcid.org/0000-0002-2981-4150
Yuanting ZhengState Key Laboratory of Genetic Engineering, School of Life Sciences, Human Phenome Institute and Shanghai Cancer Center, Fudan University, Shanghai, China. zhengyuanting@fudan.edu.cn.ORCID http://orcid.org/0000-0003-4480-8303
Haiquan ChenDepartments of Thoracic Surgery and State Key Laboratory of Genetic Engineering, Fudan University Shanghai Cancer Center, Shanghai, China. hqchen1@yahoo.com.ORCID http://orcid.org/0000-0001-7846-257X

Funding

National Natural Science Foundation of China (National Science Foundation of China) 82203037National Natural Science Foundation of China (National Science Foundation of China) 82430099
6 · The paper itself

Abstract

Deeper insights into omics in the clinical and tumor microenvironments of lung adenocarcinoma (LUAD) could reveal therapy-sensitive subtypes and novel treatments. From a cohort of 1008 samples from Chinese patients with LUAD with whole-genome and transcriptome sequencing data along with comprehensive longitudinal clinical and therapeutic information, we identified four prognostically distinct subtypes, namely, low proliferation and invasion (LPI), immune-desert (IMD), immune-enriched (IME), and high proliferation and invasion (HPI), based on the transcriptomic features linked to the radiological, pathological, and microenvironmental dimensions. Compared with chemotherapy, tyrosine kinase inhibitor (TKI) therapy demonstrated significantly superior efficacy for LPI and IMD, whereas no such difference was observed for HPI. VOPP1 and RRM2B amplification were closely associated with TKI resistance and sensitivity, respectively. VOPP1 knockdown restored sensitivity to TKI treatment, while RRM2B knockdown induced TKI resistance, and its overexpression restored sensitivity. Patients with RRM2B amplification had a 5-year survival rate of nearly 100%. Additionally, the IME subtype exhibited higher immune checkpoint activity and a higher frequency of DYNC2H1 mutation, with patients benefiting from immunotherapy. These findings provide critical insights into LUAD treatment optimization.

Identifiers

PMID41605901
PMCPMC12852120

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.