Evidence map›Paper›PMID 40719993›Full record

ArticleDiscover oncology2025

Systematic pan-cancer analysis identified NCOA4 as an immunological and prognostic biomarker and validated in lung adenocarcinoma.

An Wang, Yun-Ye Mao, Tao Li, Xin Zhou, Yi-Bing Bai, Jia-Pei Qin, Yi Dong, Ting Wang, Tong Zhang, Zhi-Qiang Ma and 1 more

Abstract read
In one paragraph

Article in Discover oncology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed, 1 pooled it
–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

1 citing paper in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
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

11 authors.

An Wang *Senior Department of Oncology, The First Medical Center; Chinese PLA General Hospital; (Chinese PLA Key Laboratory of Oncology, Key Laboratory for Tumor Targeting Therapy and Antibody Drugs (Ministry of Education, China), Beijing, China.ORCID https://orcid.org/0009-0001-6032-1573
Yun-Ye Mao *Senior Department of Oncology, The First Medical Center; Chinese PLA General Hospital; (Chinese PLA Key Laboratory of Oncology, Key Laboratory for Tumor Targeting Therapy and Antibody Drugs (Ministry of Education, China), Beijing, China.ORCID https://orcid.org/0009-0004-9457-6664
Tao Li *Senior Department of Oncology, The First Medical Center; Chinese PLA General Hospital; (Chinese PLA Key Laboratory of Oncology, Key Laboratory for Tumor Targeting Therapy and Antibody Drugs (Ministry of Education, China), Beijing, China.ORCID https://orcid.org/0000-0002-9038-4794
Xin ZhouSenior Department of Oncology, The First Medical Center; Chinese PLA General Hospital; (Chinese PLA Key Laboratory of Oncology, Key Laboratory for Tumor Targeting Therapy and Antibody Drugs (Ministry of Education, China), Beijing, China.
Yi-Bing BaiSenior Department of Oncology, The First Medical Center; Chinese PLA General Hospital; (Chinese PLA Key Laboratory of Oncology, Key Laboratory for Tumor Targeting Therapy and Antibody Drugs (Ministry of Education, China), Beijing, China.
Jia-Pei QinSenior Department of Oncology, The First Medical Center; Chinese PLA General Hospital; (Chinese PLA Key Laboratory of Oncology, Key Laboratory for Tumor Targeting Therapy and Antibody Drugs (Ministry of Education, China), Beijing, China.
Yi DongSenior Department of Oncology, The First Medical Center; Chinese PLA General Hospital; (Chinese PLA Key Laboratory of Oncology, Key Laboratory for Tumor Targeting Therapy and Antibody Drugs (Ministry of Education, China), Beijing, China.
Ting WangSenior Department of Oncology, The First Medical Center; Chinese PLA General Hospital; (Chinese PLA Key Laboratory of Oncology, Key Laboratory for Tumor Targeting Therapy and Antibody Drugs (Ministry of Education, China), Beijing, China.
Tong ZhangGraduate School, Chinese PLA General Hospital/Medical School of Chinese PLA, Beijing, 100853, PR China. kqzhengji301@163.com.
Zhi-Qiang MaSenior Department of Oncology, The First Medical Center; Chinese PLA General Hospital; (Chinese PLA Key Laboratory of Oncology, Key Laboratory for Tumor Targeting Therapy and Antibody Drugs (Ministry of Education, China), Beijing, China. mazhiqiang@301hospital.com.cn.
Yi HuSenior Department of Oncology, The First Medical Center; Chinese PLA General Hospital; (Chinese PLA Key Laboratory of Oncology, Key Laboratory for Tumor Targeting Therapy and Antibody Drugs (Ministry of Education, China), Beijing, China. huyi301zlxb@sina.com.ORCID https://orcid.org/0000-0001-9319-5692

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundCancer immunotherapy has revolutionized treatment, yet predicting patient responses remains challenging. The potential of nuclear receptor coactivator 4 (NCOA4) as a biomarker has been identified in different types of cancer. However, its role as an immunological and prognostic factor across cancers, particularly lung adenocarcinoma (LUAD), still needs to be fully understood. This study aims to address this gap by systematically analyzing NCOA4's expression and its correlation with clinical outcomes and immune responses in pan-cancer.

objectiveTo evaluate NCOA4 as a prognostic biomarker and explore its association with immune microenvironments across different cancer types, specifically focusing on LUAD.

methodsWe comprehensively analyzed data from the CCLE, GTEx, and TCGA databases. NCOA4 expression was analyzed in both normal and tumor tissues, and its correlation with overall survival was assessed using univariate Cox regression and Kaplan-Meier analysis. Immune infiltration was evaluated using the ESTIMATE, TIMER, and xCELL algorithms. We comprehensively analyzed its correlation with six genomic instability markers and the DNA methylation- and mRNA-based stemness index in certain tumors to investigate the potential role of NCOA4 in mediating cancer genomic heterogeneity and stemness. PPI network analysis and KEGG/GO enrichment analysis were conducted to identify associated proteins and pathways. LUAD samples were stained using immunohistochemistry (IHC). TIDE algorithm was used to predict immune checkpoint blockade (ICB) response within the TCGA-LUAD cohort.

resultsNCOA4 expression was significantly higher in tumor tissues than normal tissues in 18 cancer types, including LUAD, while it was lower in 5. Survival outcomes in specific cancers were found to be inversely associated with NCOA4 expression, as indicated by the results of univariate Cox regression and Kaplan-Meier analysis. Analysis of immune infiltration demonstrated a significant association between NCOA4 and the presence of immune cells, including CD8 + T cells, neutrophils, and dendritic cells. Genomic instability markers, including TMB and MSI, showed significant correlations with NCOA4 expression, indicating a potential role in immunotherapy response. Stemness index analyses suggested NCOA4's involvement in regulating tumor stemness. PPI network and KEGG/GO enrichment analyses implicated NCOA4 in immune-related biological processes and pathways. IHC staining of LUAD tissues confirmed higher NCOA4 expression in tumors versus non-cancerous tissues. The TIDE algorithm predicted that higher NCOA4 expression levels, as indicated by elevated TIDE scores, were associated with poorer ICB response rates in the TCGA-LUAD cohort.

conclusionNCOA4 exhibits context-dependent associations with prognosis, immune infiltration, and genomic instability across cancers. While experimental validation in LUAD supports its candidacy as a biomarker, mechanistic studies are required to establish causal relationships. These findings highlight NCOA4's potential utility in stratifying patients for immunotherapy and ferroptosis-targeted therapies.

Indexed as

Immunological biomarkerImmunotherapyLung adenocarcinomaNCOA4Prognostic biomarkerTumor microenvironment

Identifiers

PMID40719993
PMCPMC12304365

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Registered trials

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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.