Evidence map›Paper›PMID 41766901›Full record

ArticleFrontiers in immunology2026

Decoding the role of RPL38 in lung adenocarcinoma: a multi-omics approach.

Lu Zhang, Fei Teng, Yuan Wang, Yang Chen, Qiuxia Liu, Fengsheng Dai, Liang Yu, Chenguo Yao, Zhiqiang Wang

Abstract read
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Article in Frontiers in immunology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

What it found

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2 · The registry

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3 · Its place in the literature

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4 · The record

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5 · Who and what money

Authors and funding

9 authors.

Lu ZhangCenter of Thoracic Cancer, Chongqing University Caner Hospital, Chongqing, China.
Fei TengCenter of Thoracic Cancer, Chongqing University Caner Hospital, Chongqing, China.
Yuan WangCenter of Thoracic Cancer, Chongqing University Caner Hospital, Chongqing, China.
Yang ChenCenter of Thoracic Cancer, Chongqing University Caner Hospital, Chongqing, China.
Qiuxia LiuCenter of Thoracic Cancer, Chongqing University Caner Hospital, Chongqing, China.
Fengsheng DaiChongqing Key Laboratory for the Mechanism and Intervention of Cancer Metastasis, Chongqing, China.
Liang YuThe State Key Laboratory of Power Transmission Equipment and System Security and New Technology, School of Electrical Engineering, Chongqing University, Chongqing, China.
Chenguo YaoThe State Key Laboratory of Power Transmission Equipment and System Security and New Technology, School of Electrical Engineering, Chongqing University, Chongqing, China.
Zhiqiang WangCenter of Thoracic Cancer, Chongqing University Caner Hospital, Chongqing, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Introduction: Members of the Ribosomal Protein L (RPL) family are involved in diverse biological processes and cancer biology, yet their precise functions and clinical implications in lung adenocarcinoma (LUAD) remain incompletely understood. Methods: Machine learning was applied to The Cancer Genome Atlas (TCGA) data to identify pivotal RPL genes and construct a predictive risk model. Multi-omics analyses-including pan-cancer cohorts and spatial transcriptomics-were integrated to evaluate the expression and prognostic significance of Ribosomal Protein L38 (RPL38). Functional impacts were examined using CCK‑8, colony formation, wound healing, Transwell assays, and subcutaneous xenograft models. Results: A three‑gene RPL‑based prognostic signature was established from the TCGA‑LUAD cohort. High‑risk patients exhibited shorter survival and increased immunosuppressive characteristics. RPL38 was upregulated in multiple cancers and associated with unfavorable outcomes. Immunohistochemical and spatial transcriptomic analyses confirmed its aberrant expression in LUAD and linked it to an immunosuppressive tumor microenvironment. Genetic ablation of RPL38 significantly inhibited LUAD cell proliferation and migration in vitro, and impaired xenograft tumor growth in vivo. Conclusions: RPL38 plays a tumor‑promoting role in LUAD. This study clarifies the contribution of RPL38 to LUAD development, provides new insights into its pathogenesis, and suggests a rationale for therapeutic targeting of RPL38 in LUAD treatment.

Indexed as

Adenocarcinoma of LungBiomarkers, TumorLung NeoplasmsRibosomal ProteinsAnimalsCell Line, TumorCell MovementCell ProliferationFemaleGene Expression ProfilingGene Expression Regulation, NeoplasticHumansMaleMiceMultiomicsPrognosisBiomarkers, TumorRibosomal Proteinslung adenocarcinomamulti-omics dataprogressionRPL38tumor immunetumor microenvironment

Identifiers

PMID41766901
PMCPMC12935985

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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.