Evidence map›Paper›PMID 38463866›Full record

ArticleHeliyon2024

Identification of immune-related gene signature for non-small cell lung cancer patients with immune checkpoint inhibitors.

Li Wang, Chaonan Han, Chenlei Cai, Jing Wu, Jianing Chen, Chunxia Su

Abstract read
In one paragraph

Article in Heliyon, 2024. 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

6 authors.

Li WangDepartment of Medical Oncology, Shanghai Pulmonary Hospital & Thoracic Cancer Institute, Tongji University School of Medicine, Shanghai, 200433, PR China.
Chaonan HanDepartment of Medical Oncology, Shanghai Pulmonary Hospital & Thoracic Cancer Institute, Tongji University School of Medicine, Shanghai, 200433, PR China.
Chenlei CaiDepartment of Medical Oncology, Shanghai Pulmonary Hospital & Thoracic Cancer Institute, Tongji University School of Medicine, Shanghai, 200433, PR China.
Jing WuDepartment of Medical Oncology, Shanghai Pulmonary Hospital & Thoracic Cancer Institute, Tongji University School of Medicine, Shanghai, 200433, PR China.
Jianing ChenDepartment of Medical Oncology, Shanghai Pulmonary Hospital & Thoracic Cancer Institute, Tongji University School of Medicine, Shanghai, 200433, PR China.
Chunxia SuDepartment of Medical Oncology, Shanghai Pulmonary Hospital & Thoracic Cancer Institute, Tongji University School of Medicine, Shanghai, 200433, PR China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: The utilization of immune checkpoint inhibitors (ICIs) has become the established protocol for treating advanced non-small cell lung cancer (NSCLC). This work aimed to identify the immune-related gene signature that can predict the prognosis of NSCLC patients receiving ICI treatment. Methods: The ImmPort database was queried to obtain a list of immune-related genes (IRGs). Differentially expressed IRGs in NSCLC patients were identified using the TCGA database. RNA-seq data and clinical information from NSCLC patients receiving immunotherapy were obtained from the GEO database (GSE93157 and ////). A gene signature was generated through multivariate Cox and LASSO regression analyses. The prognostic value and function of this gene signature were thoroughly investigated using comprehensive bioinformatics analyses. Results: A total of 6 prognostic-related genes were identified from 617 differentially expressed genes, and two prognostic-related differentially expressed genes (CAMP and IL17A) were determined to construct gene signature. Our gene signature demonstrated superior performance compared to other clinicopathological parameters in predicting the prognosis of NSCLC patients receiving immunotherapy, with an area under the ROC curve (AUC) of 0.812. Furthermore, immune infiltration analysis indicated that the high-risk group was enriched with resting CD4 T cell memory, while the low-risk group showed a "hot" tumor microenvironment that promotes anti-tumor immunity in NSCLC patients. Conclusion: Gene signatures based on immune-related genes exhibited excellent indicator performance of prognosis and immune infiltration, which has the potential to be an effective biomarker for NSCLC with ICI treatment.

Indexed as

Gene signatureImmune checkpoint inhibitorsImmune infiltrationImmune-related geneNSCLC

Identifiers

PMID38463866
PMCPMC10923664

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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.