Evidence map›Paper›PMID 42779146›Full record

ReviewThoracic cancer2026

Guiding the Application of Immunotherapy in Nonsmall Cell Lung Cancer: The Role of Biomarkers.

Yuting Sun, Xuelei Chu, Xinmiao Wang, Weina Li, Xiaoyu Zhu, Guanghui Zhu, Xinyi Ma, Xue He, Jie Li

Abstract readReview
In one paragraph

Review in Thoracic cancer, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

9 authors.

Yuting SunDepartment of Oncology, Guang'anmen Hospital, China Academy of Chinese Medical Sciences, Beijing, China.ORCID https://orcid.org/0000-0002-6451-1526
Xuelei ChuDepartment of Oncology, Guang'anmen Hospital, China Academy of Chinese Medical Sciences, Beijing, China.ORCID https://orcid.org/0000-0002-1311-3907
Xinmiao WangDepartment of Oncology, Guang'anmen Hospital, China Academy of Chinese Medical Sciences, Beijing, China.ORCID https://orcid.org/0000-0002-9367-4471
Weina LiDepartment of Oncology, Guang'anmen Hospital, China Academy of Chinese Medical Sciences, Beijing, China.
Xiaoyu ZhuDepartment of Oncology, Guang'anmen Hospital, China Academy of Chinese Medical Sciences, Beijing, China.
Guanghui ZhuDepartment of Oncology, Guang'anmen Hospital, China Academy of Chinese Medical Sciences, Beijing, China.
Xinyi MaDepartment of Oncology, Guang'anmen Hospital, China Academy of Chinese Medical Sciences, Beijing, China.
Xue HeDepartment of Oncology, Guang'anmen Hospital, China Academy of Chinese Medical Sciences, Beijing, China.
Jie LiDepartment of Oncology, Guang'anmen Hospital, China Academy of Chinese Medical Sciences, Beijing, China.ORCID https://orcid.org/0000-0002-3461-8816

Funding

National Key Research and Development Program of China 2023YFC3503300, 2023YFC3503305The Science and Technology Innovation Projects for Graduate Students at China Academy of Chinese Medical Sciences KC2025006
6 · The paper itself

Abstract

Although immunotherapy has completely transformed the treatment landscape of nonsmall cell lung cancer (NSCLC), its wide application is still limited by the heterogeneity of patient responses, primary and acquired resistance, as well as the management challenges of immune-related adverse events (irAEs). To achieve precise individualized immunotherapy, this review systematically summarizes the multidimensional biomarker profiles that can predict the efficacy, resistance, and safety of immunotherapy. Beyond the single PD-L1 expression, the efficacy prediction system has expanded to integrate multimodal information such as dynamic tumor microenvironment, tumor genomic characteristics, systemic inflammation/immune status, and radiomics. At the same time, studies have revealed that immune-suppressive microenvironments and specific genetic variations are key mechanisms mediating treatment resistance. Moreover, clinical characteristics, blood markers, and imaging findings provide a basis for predicting the risk of irAEs. Looking to the future, the core to overcoming current bottlenecks lies in constructing dynamic and integrated prediction models. By integrating multiomics data, longitudinal liquid biopsies, and artificial intelligence algorithms, an intelligent decision-making system is expected to be developed to achieve real-time monitoring of treatment response, early identification of resistance mechanisms, and proactive management of toxicity risks, ultimately optimizing the clinical practice of NSCLC immunotherapy and advancing it towards higher-order precision medicine.

Indexed as

Biomarkers, TumorCarcinoma, Non-Small-Cell LungImmunotherapyLung NeoplasmsHumansBiomarkers, Tumorbiomarkersimmunotherapeuticnonsmall cell lung carcinomapersonalized treatment strategies

Identifiers

PMID42779146
PMCPMC13601740

What OpenQuestion holds

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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 OpenQuestion graph.