Evidence map›Paper›PMID 40940134›Full record

ArticleJournal for immunotherapy of cancer2025

Novel circulating microRNA signature for early detection and prognostication of checkpoint inhibitor-related pneumonitis.

Haiyi Deng, Yi Yang, Yilin Yang, Ying Liang, Fei Wang, Lanmengxi Yang, Kangjing Ma, Junyi Mo, Zekun Chenli, Junwei Wu and 14 more

Abstract read
In one paragraph

Article in Journal for immunotherapy of cancer, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing 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

5 citing papers in PubMed.

  1. Article
  2. [Advances in Radiomics for Immune Checkpoint Inhibitor-related Pneumonitis 
of Lung Cancer].Zhongguo fei ai za zhi = Chinese journal of lung cancer · 2026
    Review
  3. Article
  4. Review
  5. Review
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

24 authors.

Haiyi Deng *KingMed School of Laboratory Medicine, The First Affiliated Hospital of Guangzhou Medical University, Guangzhou Medical University, Guangzhou, Guangdong, China.
Yi Yang *KingMed School of Laboratory Medicine, The First Affiliated Hospital of Guangzhou Medical University, Guangzhou Medical University, Guangzhou, Guangdong, China.
Yilin Yang *KingMed School of Laboratory Medicine, The First Affiliated Hospital of Guangzhou Medical University, Guangzhou Medical University, Guangzhou, Guangdong, China.ORCID http://orcid.org/0009-0005-8883-4361
Ying Liang *Department of Laboratory Medicine, The First Affiliated Hospital of Guangzhou Medical University, Guangzhou, Guangdong, China.
Fei WangKingMed School of Laboratory Medicine, The First Affiliated Hospital of Guangzhou Medical University, Guangzhou Medical University, Guangzhou, Guangdong, China.
Lanmengxi YangKingMed School of Laboratory Medicine, The First Affiliated Hospital of Guangzhou Medical University, Guangzhou Medical University, Guangzhou, Guangdong, China.
Kangjing MaKingMed School of Laboratory Medicine, The First Affiliated Hospital of Guangzhou Medical University, Guangzhou Medical University, Guangzhou, Guangdong, China.
Junyi MoKingMed School of Laboratory Medicine, The First Affiliated Hospital of Guangzhou Medical University, Guangzhou Medical University, Guangzhou, Guangdong, China.
Zekun ChenliKingMed School of Laboratory Medicine, The First Affiliated Hospital of Guangzhou Medical University, Guangzhou Medical University, Guangzhou, Guangdong, China.
Junwei WuKingMed School of Laboratory Medicine, The First Affiliated Hospital of Guangzhou Medical University, Guangzhou Medical University, Guangzhou, Guangdong, China.
Yuheng LiuKingMed School of Laboratory Medicine, The First Affiliated Hospital of Guangzhou Medical University, Guangzhou Medical University, Guangzhou, Guangdong, China.
Jin SuKingMed School of Laboratory Medicine, The First Affiliated Hospital of Guangzhou Medical University, Guangzhou Medical University, Guangzhou, Guangdong, China.
Liqiang WangKingMed School of Laboratory Medicine, The First Affiliated Hospital of Guangzhou Medical University, Guangzhou Medical University, Guangzhou, Guangdong, China.
Shiyu SuKingMed School of Laboratory Medicine, The First Affiliated Hospital of Guangzhou Medical University, Guangzhou Medical University, Guangzhou, Guangdong, China.
Yinxiao XiaKingMed School of Laboratory Medicine, The First Affiliated Hospital of Guangzhou Medical University, Guangzhou Medical University, Guangzhou, Guangdong, China.
Zirui WangThe Affiliated Traditional Chinese Medicine Hospital, Guangzhou Medical University, Guangzhou, Guangdong, China.
Xinyi WuKingMed School of Laboratory Medicine, The First Affiliated Hospital of Guangzhou Medical University, Guangzhou Medical University, Guangzhou, Guangdong, China.
Ni SunState Key Laboratory of Respiratory Diseases, National Clinical Research Center for Respiratory Disease, National Center for Respiratory Medicine, Guangzhou Institute of Respiratory Health, Guangzhou, Guangdong, China.
Wenhui GuanKingMed School of Laboratory Medicine, The First Affiliated Hospital of Guangzhou Medical University, Guangzhou Medical University, Guangzhou, Guangdong, China.
Xinqing LinKingMed School of Laboratory Medicine, The First Affiliated Hospital of Guangzhou Medical University, Guangzhou Medical University, Guangzhou, Guangdong, China.
Xiaohong XieKingMed School of Laboratory Medicine, The First Affiliated Hospital of Guangzhou Medical University, Guangzhou Medical University, Guangzhou, Guangdong, China.
Yao LiaoKingMed School of Laboratory Medicine, The First Affiliated Hospital of Guangzhou Medical University, Guangzhou Medical University, Guangzhou, Guangdong, China wanglf@gzhmu.edu.cn doctorzcz@163.com 2023390084@gzhmu.edu.cn.
Chengzhi ZhouKingMed School of Laboratory Medicine, The First Affiliated Hospital of Guangzhou Medical University, Guangzhou Medical University, Guangzhou, Guangdong, China wanglf@gzhmu.edu.cn doctorzcz@163.com 2023390084@gzhmu.edu.cn.ORCID http://orcid.org/0000-0003-0029-6879
Lifu WangKingMed School of Laboratory Medicine, The First Affiliated Hospital of Guangzhou Medical University, Guangzhou Medical University, Guangzhou, Guangdong, China wanglf@gzhmu.edu.cn doctorzcz@163.com 2023390084@gzhmu.edu.cn.ORCID http://orcid.org/0000-0003-1298-4476

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundCheckpoint inhibitor-related pneumonitis (CIP) represents a highly lethal immune-related adverse event. Early diagnosis of CIP is crucial for timely intervention and improved prognosis; however, the absence of precise and effective diagnostic techniques often leads to underdiagnosis and misdiagnosis. This study aims to identify microRNA (miRNA) features from serum and extracellular vesicles (EVs) for the early CIP detection and prognosis.

methodsSmall RNA sequencing identified candidate miRNAs in 27 serum-derived EV samples from persons with lung cancer and CIP (CIP group) and those without, including immunotherapy-treated persons with lung cancer without CIP (immune checkpoint inhibitor, ICI group) and patients with infectious pneumonia (PNE group). These miRNAs were validated in EV samples in a discovery cohort (n=48) using a quantitative reverse transcription-PCR (qRT-PCR). Diagnostic models for the biomarkers were developed using a training cohort (ICI:47, PNE:28, CIP:31) and validated in a separate validation cohort (ICI:32, PNE:19, CIP:21) using qRT-PCR in both EV and serum samples, and logistic regression. Using a Cox regression model, we built a prognostic risk stratification for patients with CIP based on three miRNAs.

resultsSequencing analysis initially screened and identified 13 overexpressed miRNAs in patients with CIP. Subsequently, qRT-PCR demonstrated that three miRNAs (EVs miR-193a-5p, serum miR-193a-5p, and serum miR-378a-3p) effectively distinguished CIP from non-CIP individuals (training cohort: area under the curve (AUC)=0.870; validation cohort: AUC=0.837). Notably, this miRNA signature was equally robust in differentiating CIP from ICI (training cohort: AUC=0.823; validation cohort: AUC=0.845) and PNE groups (training cohort: AUC=0.892; validation cohort: AUC=0.907). Furthermore, when combined with lymphocyte levels, the miRNA signature significantly enhanced the overall diagnostic accuracy in distinguishing CIP from the non-CIP group (training cohort: AUC=0.900; validation cohort: AUC=0.932), and maintained its robustness in distinguishing CIP from the ICI group (training cohort: AUC=0.898; validation cohort: AUC=0.946) and the PNE group (training cohort: AUC=0.938; validation cohort: AUC=0.959). Additionally, the three-miRNA panel was independently and significantly associated with overall survival in patients with CIP (HR: 2.827; p=0.040).

conclusionsOur circulating miRNA-based signature represents a non-invasive and robust diagnostic tool for patients with CIP and could accurately predict their prognosis. This signature may facilitate early detection and personalized management of these patients.

Indexed as

Circulating MicroRNAImmune Checkpoint InhibitorsLung NeoplasmsPneumoniaAgedBiomarkers, TumorFemaleHumansMaleMiddle AgedPrognosisBiomarkers, TumorCirculating MicroRNAImmune Checkpoint InhibitorsImmune related adverse event - irAE

Identifiers

PMID40940134
PMCPMC12519384

What Socratic holds

Textmetadata
LicenceCC BY-NC
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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 Socratic graph.