Evidence map›Paper›PMID 41179681›Full record

ArticleFrontiers in oncology2025

Investigating subregional PD-L1 expression within primary tumors to predict clinical outcomes in advanced NSCLC patients who received ICB-based therapy.

Danhong Zhou, Ziwen Zhu, Jingyu Mao, Meiqin Su, Cheng Chen

Abstract read
In one paragraph

Article in Frontiers in oncology, 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

5 authors.

Danhong ZhouDepartment of Respiratory and Critical Medicine, The First Affiliated Hospital of Soochow University, Suzhou, China.
Ziwen ZhuDepartment of Respiratory and Critical Medicine, The First Affiliated Hospital of Soochow University, Suzhou, China.
Jingyu MaoDepartment of Respiratory and Critical Medicine, The First Affiliated Hospital of Soochow University, Suzhou, China.
Meiqin SuDepartment of Respiratory and Critical Medicine, The First Affiliated Hospital of Soochow University, Suzhou, China.
Cheng ChenDepartment of Respiratory and Critical Medicine, The First Affiliated Hospital of Soochow University, Suzhou, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Programmed cell death-ligand 1 (PD-L1) immunohistochemical expression currently is the only approved useful biomarker associated with the PD-1/PD-L1 immune checkpoint blockade (ICB) efficacy for non-small cell lung carcinoma (NSCLC) patients. However, different tumor biopsy strategies could reflect the substantial heterogeneity of PD-L1 within the same tumor (spatial heterogeneity). Therefore, we aimed to explore the impact of spatial heterogeneity on the predictive value of PD-L1 expression in NSCLC patients on the ICB treatment after two cycles. Methods: All consecutive subjects with NSCLC receiving first-line ICB-based therapy for at least two cycles between January 2020 and March 2024 were enrolled and classified according to the biopsy strategies. Transbronchial lung biopsy (TBLB) or transbronchial mucosal biopsy was performed to obtain samples from the primary tumor superficial (PT Results: Among NSCLC receiving ICB therapy, PT Conclusions: PD-L1 from the deep subregion is a more solid predictive biomarker of both short- and long-time efficacies of ICB-based therapy, and optimizing the assessment of spatial heterogeneity provides a new perspective for clinicians to screen advanced NSCLC patients who can benefit from ICB-based therapy.

Indexed as

heterogeneityimmunotherapyPD-L1predictive biomarkertumor response

Identifiers

PMID41179681
PMCPMC12575117

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

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 OpenQuestion graph.