Evidence map›Paper›PMID 41523257›Full record

ReviewAmerican journal of cancer research2025

The role of EGFR mutations in sensitivity of PD-1/PD-L1 blockade in non-small cell lung cancer.

Jiayi Guo, Liting Yang, Xinyi Li, Xinyu Rao, Fengyun Chen, Panpan Wu, Mengting Bi, Zhenbang Yuan, Jingpeng Yang, Shen Wang and 4 more

Abstract readReview
In one paragraph

Review in American journal of cancer research, 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. Article
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

14 authors.

Jiayi GuoSchool of Pharmacy and Department of Respiratory Medicine Affiliated Hospital, Hangzhou Normal University Hangzhou 310015, Zhejiang, China.
Liting YangSchool of Pharmacy and Department of Respiratory Medicine Affiliated Hospital, Hangzhou Normal University Hangzhou 310015, Zhejiang, China.
Xinyi LiSchool of Pharmacy and Department of Respiratory Medicine Affiliated Hospital, Hangzhou Normal University Hangzhou 310015, Zhejiang, China.
Xinyu RaoSchool of Pharmacy and Department of Respiratory Medicine Affiliated Hospital, Hangzhou Normal University Hangzhou 310015, Zhejiang, China.
Fengyun ChenSchool of Pharmacy and Department of Respiratory Medicine Affiliated Hospital, Hangzhou Normal University Hangzhou 310015, Zhejiang, China.
Panpan WuSchool of Pharmacy and Department of Respiratory Medicine Affiliated Hospital, Hangzhou Normal University Hangzhou 310015, Zhejiang, China.
Mengting BiSchool of Pharmacy and Department of Respiratory Medicine Affiliated Hospital, Hangzhou Normal University Hangzhou 310015, Zhejiang, China.
Zhenbang YuanSchool of Pharmacy and Department of Respiratory Medicine Affiliated Hospital, Hangzhou Normal University Hangzhou 310015, Zhejiang, China.
Jingpeng YangSchool of Pharmacy and Department of Respiratory Medicine Affiliated Hospital, Hangzhou Normal University Hangzhou 310015, Zhejiang, China.
Shen WangSchool of Pharmacy and Department of Respiratory Medicine Affiliated Hospital, Hangzhou Normal University Hangzhou 310015, Zhejiang, China.
Zehai XiaDepartment of Respiratory Medicine, The Affiliated Hospital of Hangzhou Normal University, Hangzhou Normal University Hangzhou 310015, Zhejiang, China.
Jianjun WangDepartment of Respiratory Medicine, The Affiliated Hospital of Hangzhou Normal University, Hangzhou Normal University Hangzhou 310015, Zhejiang, China.
Shuiping LiuSchool of Pharmacy and Department of Respiratory Medicine Affiliated Hospital, Hangzhou Normal University Hangzhou 310015, Zhejiang, China.
Qun LvDepartment of Respiratory Medicine, The Affiliated Hospital of Hangzhou Normal University, Hangzhou Normal University Hangzhou 310015, Zhejiang, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

In non-small cell lung cancer (NSCLC), epidermal growth factor receptor (EGFR) is one of the most prevalent driver gene, whose expression and recurrent mutations are closely related to the prognosis of patients. EGFR tyrosine kinase inhibitors (EGFR-TKIs) are ones of the most used among the first line treatment of NSCLC, but their efficacy is significantly reduced due to the inevitable development of acquired EGFR-TKI resistance. Consequently, searching for innovative drugs to overcome this challenge is urgent. Immune checkpoint inhibitors such as antibodies against the programmed cell death protein-1 (PD-1) or its ligand (PD-L1), have exhibited remarkable potential in NSCLC therapy. While the response rates of PD-1/PD-L1 blockade in EGFR-mutated NSCLC patients remain controversial. To gain deeper insights, we first analyzed the different therapeutic effect of PD-1/PD-L1 blockade between EGFR wild-type and mutated NSCLC patients. Meanwhile, the factors and the mechanisms that affect therapeutic effect of PD-1/PD-L1 blockade were summarized, including PD-1/PD-L1 expression levels, the tumor microenvironment (TME), and the adoption of combination therapy strategies. Furthermore, we comprehensively evaluated the combinatorial therapeutic effect with established synergistic potential within these factors. Moreover, we further explored the potential of PD-1/PD-L1 as a predictive biomarker for EGFR mutations by conducting a systematic and multidimensional analysis, aiming to refine therapeutic decision-making and facilitate personalized treatment strategies for EGFR-mutated NSCLC. Additionally, we also discussed the novel strategies that could alleviate the EGFR-TKIs resistance in NSCLC base on PD-1/PD-L1 immune inhibitors, shedding light on challenges facing future research.

Indexed as

combination therapyEGFRPD-L1TMEtumor mutation burden

Identifiers

PMID41523257
PMCPMC12789927

What OpenQuestion holds

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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.