Evidence map›Paper›PMID 40230863›Full record

ArticleFrontiers in immunology2025

Small extracellular vesicle miRNAs as biomarkers for predicting antitumor efficacy in lung adenocarcinoma treated with chemotherapy and checkpoint blockade.

Si Sun, Fuchuang Zhang, Jiyang Zhang, Hui Yu, Zhihuang Hu, Xiaoya Xu, Xinmin Zhao, Sheng Chen, Yao Zhang, Baoning Nian and 9 more

Abstract read
In one paragraph

Article in Frontiers in immunology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. 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

19 authors.

Si Sun *Department of Thoracic Medical Oncology, Fudan University Shanghai Cancer Center, Shanghai, China.
Fuchuang Zhang *Department of Clinical and Translational Medicine, 3D Medicines Inc., Shanghai, China.
Jiyang Zhang *Department of Clinical and Translational Medicine, 3D Medicines Inc., Shanghai, China.
Hui YuDepartment of Thoracic Medical Oncology, Fudan University Shanghai Cancer Center, Shanghai, China.
Zhihuang HuDepartment of Thoracic Medical Oncology, Fudan University Shanghai Cancer Center, Shanghai, China.
Xiaoya XuDepartment of Clinical and Translational Medicine, 3D Medicines Inc., Shanghai, China.
Xinmin ZhaoDepartment of Thoracic Medical Oncology, Fudan University Shanghai Cancer Center, Shanghai, China.
Sheng ChenDepartment of Clinical and Translational Medicine, 3D Medicines Inc., Shanghai, China.
Yao ZhangDepartment of Thoracic Medical Oncology, Fudan University Shanghai Cancer Center, Shanghai, China.
Baoning NianDepartment of Clinical and Translational Medicine, 3D Medicines Inc., Shanghai, China.
Ying LinDepartment of Thoracic Medical Oncology, Fudan University Shanghai Cancer Center, Shanghai, China.
Zhikuan LiDepartment of Clinical and Translational Medicine, 3D Medicines Inc., Shanghai, China.
Zhenhua WuDepartment of Thoracic Medical Oncology, Fudan University Shanghai Cancer Center, Shanghai, China.
Bo YuDepartment of Thoracic Medical Oncology, Fudan University Shanghai Cancer Center, Shanghai, China.
Xianghua WuDepartment of Thoracic Medical Oncology, Fudan University Shanghai Cancer Center, Shanghai, China.
Huijie WangDepartment of Thoracic Medical Oncology, Fudan University Shanghai Cancer Center, Shanghai, China.
Xiaohua HuiDepartment of Thoracic Medical Oncology, Fudan University Shanghai Cancer Center, Shanghai, China.
Dadong ZhangDepartment of Clinical and Translational Medicine, 3D Medicines Inc., Shanghai, China.
Jialei WangDepartment of Thoracic Medical Oncology, Fudan University Shanghai Cancer Center, Shanghai, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Checkpoint blockade combined with chemotherapy has become an important treatment option for lung cancer patients in clinical settings. However, biomarkers that effectively identify true responders remain lacking. We assessed the potential of plasma small extracellular vesicle (sEV)-derived microRNAs (miRNAs) as biomarkers for predicting and identifying responders to combined immunochemotherapy. A total of 29 patients with lung adenocarcinoma who received pembrolizumab combined with pemetrexed and carboplatin were enrolled. The efficacy evaluation revealed that 24 patients obtained durable clinical benefits from combined immunochemotherapy, and the rest experienced disease progression. Using unsupervised hierarchical clustering, 56 differentially expressed miRNAs (DEMs) were identified between responders and nonresponders. Efficacy prediction models incorporating a combination of sEV miRNAs were established and showed good performance (area under the curve (AUC) > 0.9). In addition, we found that miR-96-5p and miR-6815-5p were notably downregulated in the nonresponder group, while miR-99b-3p, miR-100-5p, miR-193a-5p, and miR-320d were upregulated. These findings were further confirmed by clinical imaging. sEV miRNAs derived from patients with lung cancer showed promise for identifying true responders to combined immunochemotherapy.

Indexed as

Adenocarcinoma of LungAntineoplastic Combined Chemotherapy ProtocolsBiomarkers, TumorExtracellular VesiclesImmune Checkpoint InhibitorsLung NeoplasmsMicroRNAsAgedAntibodies, Monoclonal, HumanizedCarboplatinFemaleGene Expression Regulation, NeoplasticHumansMaleMiddle AgedPemetrexedAntibodies, Monoclonal, HumanizedBiomarkers, TumorCarboplatinImmune Checkpoint InhibitorsMicroRNAspembrolizumabPemetrexedchemotherapyimmune checkpoint inhibitorslung cancer. sEV miRNAs predicting immunochemotherapy efficacymiRNAsEVs

Identifiers

PMID40230863
PMCPMC11994727

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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.