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. 2024 May 17;24(1):102.
doi: 10.1007/s10238-024-01328-w.

IFN-α/β/IFN-γ/IL-15 pathways identify GBP1-expressing tumors with an immune-responsive phenotype

Lei Wang #  1 , Yuxuan Wei  1 , Zheng Jin #  2   3 , Fangfang Liu  1 , Xuchang Li  1 , Xiao Zhang  4 , Xiumei Bai  4 , Qingzhu Jia  5   6 , Bo Zhu  5   6 , Qian Chu  7
Affiliations

IFN-α/β/IFN-γ/IL-15 pathways identify GBP1-expressing tumors with an immune-responsive phenotype

Lei Wang et al. Clin Exp Med. .

Abstract

Immunotherapy is widely used in cancer treatment; however, only a subset of patients responds well to it. Significant efforts have been made to identify patients who will benefit from immunotherapy. Successful anti-tumor immunity depends on an intact cancer-immunity cycle, especially long-lasting CD8+ T-cell responses. Interferon (IFN)-α/β/IFN-γ/interleukin (IL)-15 pathways have been reported to be involved in the development of CD8+ T cells. And these pathways may predict responses to immunotherapy. Herein, we aimed to analyze multiple public databases to investigate whether IFN-α/β/IFN-γ/IL-15 pathways could be used to predict the response to immunotherapy. Results showed that IFN-α/β/IFN-γ/IL-15 pathways could efficiently predict immunotherapy response, and guanylate-binding protein 1 (GBP1) could represent the IFN-α/β/IFN-γ/IL-15 pathways. In public and private cohorts, we further demonstrated that GBP1 could efficiently predict the response to immunotherapy. Functionally, GBP1 was mainly expressed in macrophages and strongly correlated with chemokines involved in T-cell migration. Therefore, our study comprehensively investigated the potential role of GBP1 in immunotherapy, which could serve as a novel biomarker for immunotherapy and a target for drug development.

Keywords: Biomarker; GBP1; Immunotherapy; Tumor microenvironment.

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Conflict of interest statement

The authors declare that they have no conflict of interest.

Figures

Fig. 1
Fig. 1
Expression of IFN-α/β/IFN-γ/IL-15 pathways is associated with prolonged survival rates and improved clinical response. a Kaplan–Meier estimates of overall survival (OS) were stratified according to expression of the IFN-α/β/IFN-γ/IL-15 pathways in the four immunotherapy and pooled cohorts. b Objective response rates (ORRs) were observed in the four immunotherapy and pooled cohorts for each group. c Percentages of responders segregated by expression of the IFN-α/β/IFN-γ/IL-15 pathways. d Percentage of patients with long-term survival was calculated for the four immunotherapy cohorts based on GBP1 expression
Fig. 2
Fig. 2
GBP1 represents the IFN-α/β/IFN-γ/IL-15 pathways. a The correlation of indicated genes with the IFN-α/β/IFN-γ/IL-15 pathways was ranked by using Pearson’s correlation coefficient based on The Cancer Genome Atlas (TCGA) dataset. b Pearson’s correlation coefficient of GBP1 expression with that of the IFN-α/β/IFN-γ/IL-15 pathways in the immunotherapy cohorts. c Ratios of the pro- to anti-inflammatory cytokines and CD8+ T cells to Tregs, tumor-associated macrophages (TAMs), and myeloid-derived suppressor cells (MDSCs) in the high and low GBP1 expression groups. d Immune checkpoint blockade (ICB) responsiveness score in the high and low GBP1 expression groups
Fig. 3
Fig. 3
GBP1 in the baseline tumor tissue correlates with favorable responses to immune checkpoint blockade. a Overall survival (OS) of patients treated with immune checkpoint inhibitors according to GBP1 expression. b Objective response rates (ORRs) were observed in the immunotherapy and pooled cohorts for each group. c Percentage of responders segregated by GBP1 expression. d Comparison of the hazard ratio of GBP1 and reported predictive markers. e Comparison of AUC values of GBP1 and representative markers (TIDE, MSI score, TMB, CD274, CD8, and B-/T-cell clonality)
Fig. 4
Fig. 4
GBP1 is mainly expressed in macrophages and correlated with T-cell migration and activation. a Uniform Manifold Approximation and Projection (UMAP) and b violin plots displaying cell-type annotations and GBP1 expression in single cells of the melanoma patient cohort. c UMAP and d violin plots exhibiting cell-type annotations and GBP1 expression in single cells of the NSCLC cohort. e Violin plot of GBP1 expression in immune subtypes from the pan-cancer analysis. f–h Gene Set Enrichment Analysis (GSEA) results showing the most significantly enriched pathways in the LUAD (f), LUSC (g), and SKCM (h) patient groups
Fig. 5
Fig. 5
Correlation between GBP1 expression and key chemokines that direct CD8+ T-cell migration. a T-cell migration score between patients with high and low GBP1 expression. b and c Correlation of GBP1 expression and that of CCL5, CXCL9, and CXCL10 in The Cancer Genome Atlas (TCGA) pan-cancer analysis (b) and immunotherapy cohorts (c)
Fig. 6
Fig. 6
GBP1 expression was related to CD8+ T-cell infiltration and the response to immune checkpoint blockade in clinical cohorts. a Representative images of GBP1 expression and CD8+ T-cell infiltration in cohort 1. Scale bar: 50 μm. b Density of CD8+ T cells in the high and low GBP1 expression groups. c Correlation between GBP1 expression and CD8+ T-cell infiltration in cohort 1. d Representative immunohistochemistry (IHC) staining images of GBP1 from patients with different treatment responses in cohort 2. Scale bar: 50 μm. e Overall survival analysis of patients in cohort 2 based on GBP1 expression
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