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. 2022 Oct 25:13:1035484.
doi: 10.3389/fgene.2022.1035484. eCollection 2022.

Immunogenic cell death mediation patterns reveal novel paradigm for characterizing the immune microenvironment and immunotherapeutic responses in bladder cancer

Jialei Fu  1 , Wei Zhang  2 , Tao Jiang  1
Affiliations

Immunogenic cell death mediation patterns reveal novel paradigm for characterizing the immune microenvironment and immunotherapeutic responses in bladder cancer

Jialei Fu et al. Front Genet. .

Abstract

Background: Immunogenic cell death (ICD) plays an important role in several malignancies. However, the role of ICD-mediated patterns in bladder cancer (BCA) remains unknown. Methods: For assessing the ICD-mediated patterns based on the expression of IRGs, 4 large BCA cohorts were obtained. The ICD-mediated patterns of individual samples were quantified as an ICD score by principal component analysis. The correlations of the ICD-mediated patterns with the tumor immune microenvironment (TIME) and responses to immunotherapy were comprehensively evaluated. The IRGs with predictive prognostic values were further validated by in vitro loss of function assays. Results: Two distinct ICD-mediated patterns were established, showing distinct clinical features and immune microenvironment features. Although ICD cluster A was associated with a poor prognosis with a high ICD score, it showed an immune activation state with a more favorable response to immunotherapy and treatment that induced ICD. The ICD-related gene, CALR, was significantly upregulated in the T24 BCA cell line relative to the control SV-HUC-1 cells. Knocking down CALR suppressed T24 cell viability and caused ER stress. Conclusion: We identified the existence of distinct ICD-mediated patterns in BCA closely associated with the remodeling of the TIME. Further in-depth examination of ICD-related features is warranted to obtain a broader prospect for therapeutic innovations and improved prognosis of BCA.

Keywords: bladder cancer; immune checkpoint inhibitors; immunogenic cell death; immunotherapy; tumor immune microenvironment.

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Conflict of interest statement

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Figures

FIGURE 1
FIGURE 1
Landscape of genetic variations in IRGs in bladder cancer. (A) CNV distributions of IRGs in bladder cancer. (B) Different expressions of IRGs in tumour and normal tissues. (C) CNV locations of IRGs on 23 human chromosomes. (D) Waterfall plot demonstrating the somatic mutation status of IRGs in bladder cancer. Each column represents a single sample and the upper bar graph represents the TMB value. The number on the right represents the frequency of somatic mutations.
FIGURE 2
FIGURE 2
The prognostic role of IRGs in the merged cohort. (A) A network illustrating interactions between 28 IRGs. (B–X) Kaplan-Meier analysis of 23 IRGs with prognostic roles in bladder cancer in the merged cohort.
FIGURE 3
FIGURE 3
GO, KEGG and ssGSEA analyses based on DEGs in distinct ICD clusters. (A) ssGSEA analysis of two distinct ICD clusters. (B) Bubble chart presenting KEGG enrichment analysis. (C) Bubble chart presenting GO enrichment analysis. The asterisk symbol indicated the statistical p-value. (*p < 0.05; **p < 0.01; ***p < 0.001).
FIGURE 4
FIGURE 4
ICD gene clusters in the merged cohort. (A) Consensus clustering matrix for k = 2. (B) Kaplan–Meier curve survival analysis among two distinct gene clusters. (C) Heatmap demonstrating various clinicopathological features of two distinct gene clusters. (D) Different expression levels of 28 IRGs in distinct gene clusters. The asterisk symbol indicated the statistical p-value. (*p < 0.05; **p < 0.01; ***p < 0.001).
FIGURE 5
FIGURE 5
ICD score is a quantification indicator of individual samples in the merged cohort. (A) Kaplan–Meier curve analysis of different ICD score groups. (B) Sankey diagram demonstrating correlations among ICD clusters, ICD score and ICD gene clusters. (C) Differences in ICD scores among two ICD clusters in the merged cohort. (D) Differences in ICD scores among two gene clusters in the merged cohort. (E) ssGSEA analysis showing a correlation between ICD score and the infiltration abundance of various immune cell.
FIGURE 6
FIGURE 6
Relationship between ICD score and tumour mutation burden. (A) Correlation between ICD score and TMB in bladder cancer. (B) Differences in the TMB value between the different ICD score groups. (C) Kaplan–Meier curve analysis showing prognosis benefits of high TMB. (D) Kaplan–Meier curve analysis concerning the combination of ICD score and TMB.
FIGURE 7
FIGURE 7
Relationship between ICD score and different clinical parameters and Kaplan–Meier survival analysis of different ICD scores in different subgroups of the merged cohort. (A) Relationships between ICD score and age. (B) Relationship between ICD score and tumour T stage. (C) Relationship between ICD score and alive/dead status. (D) Relationship between ICD score and gender. (E) Kaplan–Meier survival analysis in male patients. (F) Kaplan–Meier survival analysis in female patients. (G) Kaplan–Meier survival analysis in patients aged ≤ 65 years. (H) Kaplan–Meier survival analysis in patients aged > 65 years. (I) Kaplan–Meier survival analysis in patients with Ta–T1 stage disease. (J) Kaplan–Meier survival analysis in patients with T2–T4 stage disease.
FIGURE 8
FIGURE 8
The indication of ICD score on immune microenvironment and prediction of immunotherapy response in bladder cancer. (A–C) ESTIMATE immune score between different ICD score groups. (D–F) Differences in the expression of IL10, TGFβ2 and TGFβ3 between different ICD score groups. (G–I) Differences in the expression of PD-1, PD-L1 and CTLA-4 between different ICD score groups. (J–M) Differences in the immunotherapeutic effects of four different strategies between the different ICD score groups.
FIGURE 9
FIGURE 9
CALR expression in bladder cancer cell lines. (A) CALR expression of bladder cancer cell lines in different data sets in CCLE database. (B) Evaluation of the relative CALR/β-Actin mRNA expression levels, normalized with the SV-HUC-1 cell group. (C) Evaluation of the mRNA expression levels of CALR in si-NC, si-CALR-1 and si-CALR-2 T24 cells using quantitative PCR, with the expression levels normalized to those of β-ACTIN. (D) CCK8 assay was used for cell viability of si-NC, si-CALR-1 and si-CALR-2 T24 cells and normalized with the si-NC group. (E) Evaluation of the mRNA expression levels of CD47, HSPA5, DDIT3, BAX and BCL-2 in T24 cells treated with si-NC, si-CALR-1, or si-CALR-2. Experiments were performed in triplicates. All data are expressed as mean ± standard error (SE). The asterisk symbol indicated the statistical p-value. (*p < 0.05; **p < 0.01; ***p < 0.001).
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References

    1. Abdollah F., Gandaglia G., Thuret R., Schmitges J., Tian Z., Jeldres C., et al. (2013). Incidence, survival and mortality rates of stage-specific bladder cancer in United States: A trend analysis. Cancer Epidemiol. 37 (3), 219–225. 10.1016/j.canep.2013.02.002 - DOI - PubMed
    1. Antoni S., Ferlay J., Soerjomataram I., Znaor A., Jemal A., Bray F. (2017). Bladder cancer incidence and mortality: A global overview and recent trends. Eur. Urol. 71 (1), 96–108. 10.1016/j.eururo.2016.06.010 - DOI - PubMed
    1. Berdik C. (2017). Unlocking bladder cancer. Nature 551 (7679), S34-S35–s35. 10.1038/551S34a - DOI - PubMed
    1. Bowers J. S., Nelson M. H., Majchrzak K., Bailey S. R., Rohrer B., Kaiser A. D., et al. (2017). Th17 cells are refractory to senescence and retain robust antitumor activity after long-term ex vivo expansion. JCI Insight 2 (5), e90772. 10.1172/jci.insight.90772 - DOI - PMC - PubMed
    1. Chen D. S., Mellman I. (2017). Elements of cancer immunity and the cancer-immune set point. Nature 541 (7637), 321–330. 10.1038/nature21349 - DOI - PubMed