Abstract
Immunogenic cell death (ICD) induces anti-tumor immunity and aids in dismantling the immunosuppressive immune microenvironment (TME), which belongs to a type of regulated cell death. The differentiation of gastric cancer (GC) subtypes and the discovery of prognostic biomarkers are crucial for its treatment because GC is a disease that is both highly heterogeneous and aggressive. However, although the induction of ICD in tumor cells is associated with a favorable prognosis, the exact mechanism of its role in GC remains unclear. Transcriptome profiling data and clinical data of GC patients were retrieved from The Cancer Genome Atlas (TCGA) database. Herein, patients were classified with the consensus clustering algorithm, and the associated biological functions and immune microenvironment infiltration were explored based on the expression of ICD-associated genes. A risk score signature consisting of 11 ICD-related genes was established via the least absolute shrinkage and selection operator regression (LASSO) method. We have retrieved similar studies in recent years and compared them with our study using the time-dependent receiver operating characteristic (ROC) curves. Gene set variation analysis (GSVA) and single sample gene set enrichment analysis (ssGSEA) were performed to explore the association between the signature and tumor microenvironment (TME). Two distinct subtypes associated with ICD in GC were identified, each with a different prognosis. The ICD-high expression subtype was associated with higher immune cell infiltration and a better prognosis. The ICD-related gene signature containing 11 genes (CGB5, Z84468.1, APOA5, EPHA8, CLEC18C, TLR7, MUC7, MUC15, CTLA4, CALB2, and UGT2B28), could independently and accurately predict the prognosis of GC. In this study, an ICD-based classification was conducted to assist in the diagnosis and personalized therapy for GC. The ICD-related genes risk score model was established to predict prognosis.
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Data Availability
All data generated and described in this paper are available from the corresponding web servers. Further inquiries can be directed to the corresponding authors.
Abbreviations
- GC:
-
Gastric cancer
- ICD:
-
Immunogenic cell death
- IRGs:
-
ICD-related genes
- TCGA:
-
The Cancer Genome Atlas
- GEO:
-
The Gene Expression Omnibus
- LASSO:
-
Least absolute shrinkage and selection operator regression
- TME:
-
Tumor microenvironment
- CDF:
-
Cumulative distribution function
- PCA:
-
Principal component analysis
- OS:
-
Overall survival
- ssGSEA:
-
Single sample gene set enrichment analysis
- ICGs:
-
Immune checkpoint genes
- ICB:
-
Immune checkpoint blockade
- TIDE:
-
The Tumor Immune Dysfunction and Exclusion
- IPS:
-
The immunophenoscore
- ICIs:
-
Immune checkpoint inhibitors
- DEGs:
-
Differentially expressed genes
- GO:
-
Gene Ontology
- KEGG:
-
Kyoto Encyclopedia of Genes and Genomes
- ROC:
-
Receiver operating characteristic
- AUC:
-
Areas under the curve
- C-index:
-
The concordance index
- TMB:
-
Tumor mutation burden
- IC50:
-
The semi-inhibitory concentration
- GSVA:
-
Gene Set Enrichment Analysis
- TLRs:
-
Toll-like receptors
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This study was supported by the National Key Research and Development Program of China (2018YFC2002000).
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The authors confirm contribution to the paper as follows: study conception and design: YM; data collection: ZJ; analysis and interpretation of results: DC; validation of results: MW; visualization of results: MZ and YH; draft manuscript preparation: YM and SX; manuscript review & editing: ZX; All authors reviewed the results and approved the final version of the manuscript.
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Meng, Y., Jin, Z., Wang, M. et al. Definition of a Novel Immunogenic Cell Death-Relevant Gene Signature Associated with Immune Landscape in Gastric Cancer. Biochem Genet 61, 2092–2115 (2023). https://doi.org/10.1007/s10528-023-10361-5
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DOI: https://doi.org/10.1007/s10528-023-10361-5