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Updated: Sep 22, 2025
Predictive Immune Modeling of Solid Tumors
Published on: February 25, 2020
A novel four-gene signature predicts immunotherapy response of patients with different cancers
Yuanli Liu1, Mingyue Ni1, Lamei Li2
1Department of Biochemistry and Molecular Biology, School of Basic Medical Sciences, Anhui Medical University, Hefei, China.
Background:
Immune checkpoint blockade (ICB) therapy has demonstrated favorable clinical efficacy, particularly for advanced or difficult-to-treat cancer types. However, this therapy is ineffective for many patients displaying lack of immune response or resistance to ICB. This study aimed to establish a novel four-gene signature (CD8A, CD8B, TCF7, and LEF1) to provide a prognostic immunotherapy biomarker for different cancers.
Methods:
Transcriptome profiles and clinical data were obtained from The Cancer Genome Atlas database. Multivariate Cox regression analysis was used to establish a four-gene signature. The R package estimate was used to obtain the immune score for every patient.
Results:
Risk scores of the novel four-gene signature could effectively divided all patients into high- and low-risk groups, with distinct outcomes. The immune score calculated via the estimate package demonstrated that the four-gene signature was significantly associated with the immune infiltration level. Furthermore, the four-gene signature could predict the response to atezolizumab immunotherapy in patients with metastatic urothelial cancer.
Conclusions:
The novel four-gene signature developed in this study is a good prognostic biomarker, as it could identify many kinds of patients with cancer who are likely to respond to and benefit from immunotherapy.
Insights
A new four-gene signature shows promise as a prognostic biomarker for immunotherapy response in various cancers. This signature helps identify patients likely to benefit from immune checkpoint blockade therapy.
Area of Science:
- Oncology
- Immunotherapy
- Genomics
Background:
- Immune checkpoint blockade (ICB) therapy is effective for some advanced cancers but fails in many patients due to lack of immune response or resistance.
- Identifying reliable biomarkers is crucial for predicting ICB efficacy and patient outcomes.
Purpose of the Study:
- To develop and validate a novel four-gene signature (CD8A, CD8B, TCF7, LEF1) as a prognostic biomarker for immunotherapy.
- To assess the signature's association with immune infiltration and its ability to predict treatment response.
Main Methods:
- Utilized transcriptome profiles and clinical data from The Cancer Genome Atlas (TCGA) database.
- Employed multivariate Cox regression analysis to establish the four-gene signature.
- Calculated immune scores using the R package 'estimate' to assess immune infiltration levels.
Main Results:
- The four-gene signature effectively stratified patients into high- and low-risk groups with distinct clinical outcomes.
- The signature demonstrated a significant correlation with immune infiltration levels.
- The gene signature successfully predicted response to atezolizumab immunotherapy in metastatic urothelial cancer patients.
Conclusions:
- The novel four-gene signature serves as a valuable prognostic biomarker for immunotherapy.
- This biomarker can identify diverse cancer patient populations likely to respond to and benefit from ICB therapy.
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