Evidence map›Paper›PMID 42504317›Full record

ArticleDose-response : a publication of International Hormesis Society

Peptidylprolyl Isomerase a Regulates DNA Damage Repair and Serves as a Prognostic Biomarker in Lung Adenocarcinoma.

Li Zou, Bixin Ren, Ying Wan, Xin Wang, Ruichi Shen, Wenlang Zhu, Limin Jin, Qiliang Peng, Ye Tian

Abstract read
In one paragraph

Article in Dose-response : a publication of International Hormesis Society. 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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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

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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

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4 · The record

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5 · Who and what money

Authors and funding

9 authors.

Li ZouDepartment of Radiotherapy & Oncology, The Second Affiliated Hospital of Soochow University, Suzhou, China.ORCID https://orcid.org/0009-0003-3058-3550
Bixin RenDepartment of Respiratory and Critical Care Medicine, The Second Affiliated Hospital of Soochow University, Suzhou, China.
Ying WanDepartment of Pharmacy, Zhongshan Hospital, Fudan University, Shanghai, China.
Xin WangInstitute of Radiation Medicine of Chinese Academy of Medical Science & Peking Union Medical College, Tianjin, China.
Ruichi ShenKangda College of Nanjing Medical University, Nanjing, China.
Wenlang ZhuDepartment of Gastrointestinal Surgery, The First People's Hospital of Taicang City, Taicang Affiliated Hospital of Soochow University, Taicang, Jiangsu, China.
Limin JinDepartment of Radiotherapy & Oncology, The Second Affiliated Hospital of Soochow University, Suzhou, China.
Qiliang PengDepartment of Radiotherapy & Oncology, The Second Affiliated Hospital of Soochow University, Suzhou, China.ORCID https://orcid.org/0000-0002-0248-8826
Ye TianDepartment of Radiotherapy & Oncology, The Second Affiliated Hospital of Soochow University, Suzhou, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: This study investigated the role of peptidylprolyl isomerase A (PPIA) in lung adenocarcinoma (LUAD) using bioinformatics approaches and experimental validation. Methods: This study began by assessing PPIA expression and its prognostic significance in LUAD. We then performed functional enrichment analyses and examined CNVs, DNA methylation, DNMT activity, RNA modification, immune cell infiltration, and drug therapy efficacy. Cellular experiments were performed to confirm the role of PPIA in DNA damage repair. Results: PPIA was overexpressed in LUAD tissues and was associated with poor prognosis, including shorter overall survival and progression-free interval. PPIA expression was correlated with CNVs, DNA methylation, DNMT activity, and RNA modification-related genes. It was also negatively associated with immune cell infiltration and immune-related gene expression, suggesting a potential immunosuppressive role. Drug sensitivity analysis indicated that PPIA may serve as a predictive biomarker for therapeutic efficacy in LUAD. In addition, PPIA expression was associated with DNA damage repair-related genes. Cellular experiments show that PPIA knockdown increases radiosensitivity and γ-H2AX foci formation, whereas PPIA overexpression exerts the opposite effects. Conclusion: This study highlights the potential of PPIA as a prognostic biomarker and target in LUAD, particularly in the regulation of DNA damage repair and tumor immune microenvironment remodeling.

Indexed as

biomarkerDNA damage repairlung adenocarcinomaPPIAprognosis

Identifiers

PMID42504317
PMCPMC13401659

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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.