Multi-omics identification and functional validation of signal regulatory protein gamma as a prognostic biomarker and immune regulator in head and neck squamous cell carcinoma
Aug 2026· Frontiers in Immunology· Vol 17· 0 citations· 44 references
Medicine
TL;DR
SIRPG is identified as an immune-related prognostic hub and context-dependent tumor-cell regulator associated with apoptosis, immune communication and spatial microenvironmental organization in HNSCC.
Abstract
Background Head and neck squamous cell carcinoma (HNSCC) comprises biologically diverse tumors, and durable responses to immune-checkpoint blockade are achieved by only a subset of patients. There remains a need for markers that connect clinical outcome with malignant-cell phenotypes and tissue-level immune organization. Methods We integrated The Cancer Genome Atlas HNSCC cohort (TCGA-HNSC), five Gene Expression Omnibus (GEO) validation cohorts, single-cell RNA sequencing, Visium spatial transcriptomics, cellular indexing of transcriptomes and epitopes by sequencing (CITE-seq)-informed protein-potential inference, pharmacogenomic screening, genetic-risk analysis and experimental validation. A reconstructed 296-pipeline survival modelling framework was used to prioritize prognostic hub genes across validation-cohort-specific analyses. Results SIRPG was repeatedly ranked among the top ten selected genes in all five validation cohorts. At single-cell resolution, SIRPG-high tumor cells showed stronger malignant-cell features, immune-inhibitory and metabolic programs, Scissor-positive risk association, CLCA2/P53-related perturbation signals and inferred SIRPG-CD47/signal regulatory protein (SIRP) communication. Spatial analyses placed this axis within an immune-checkpoint-coupled niche, supported by Maxspin/multiview intercellular spatial modelling (MISTy) spatial coupling, communication analysis by optimal transport (COMMOT)-inferred CD47-SIRPG communication and scProTrans-inferred CD47/SIRPG protein-potential overlap. Functionally, SIRPG knockdown reduced HNSCC cell viability and increased apoptosis, whereas re-expression of short hairpin RNA (shRNA)-resistant SIRPG restored the CLCA2-BAX/BCL2 protein response. Conclusion Together, these findings identify SIRPG as an immune-related prognostic hub and context-dependent tumor-cell regulator associated with apoptosis, immune communication and spatial microenvironmental organization in HNSCC.
Background Epstein–Barr virus–associated gastric cancer (EBVaGC) is a distinct molecular subtype of gastric cancer, but reliable biomarkers linking EBV‐related biology, prognosis, and microenvironmental remodeling remain limited. Methods Differentially expressed genes associated with EBVaGC were identified from TCGA and GEO datasets. Weighted gene co‐expression network analysis and machine learning were used to screen core genes. Functional enrichment, diagnostic and prognostic modeling, immune infiltration analysis, single‐cell transcriptomic analysis of a public scRNA‐seq dataset, cell–cell communication analysis, drug sensitivity prediction, external cohort validation, and RT‐qPCR validation in gastric cancer cell lines were subsequently performed. Results Five core genes (ASPA, CHODL, GNG7, P2RY14, and PI16) were identified. The combined classifier showed high apparent diagnostic performance in the discovery datasets (AUC = 1.000 in the EBV cohort and 0.981 in TCGA–STAD) and retained value in GSE27342 (AUC = 0.771). RT‐qPCR confirmed differential expression of these genes between a gastric epithelial cell line and a gastric cancer cell line, providing general tumor‐versus‐normal experimental support rather than EBV‐specific validation. A five‐gene risk signature stratified overall survival, with 1‐, 2‐, and 3‐year AUCs of 0.634, 0.645, and 0.622, which improved to 0.716, 0.768, and 0.693 after integration with age and stage. Single‐cell analysis localized the strongest signature signal to fibroblasts and B cells and revealed enhanced MIF‐, PTN‐, and TNFSF13B‐related communication in tumors. High‐risk tumors showed higher predicted IC50 values for paclitaxel and 5‐fluorouracil. Conclusion We identified a five‐gene signature with strong diagnostic value and biologically meaningful prognostic relevance in EBVaGC, highlighting fibroblast‐ and B‐cell‐associated microenvironmental programs in aggressive disease.
Luyu Jin, Man Jiang, Yulong Pan et al.· Genetics Research· 0 citations
A seven-gene immune-related prognostic signature that, combined with clinicopathological parameters, provides a robust tool for individualized survival prediction and may guide precision management in CRC patients is developed and validated.
PHLDA3 serves as a robust prognostic biomarker for HNSC and drives the formation of an immunosuppressive microenvironment, highlighting a promising therapeutic target for combined metabolic-immune strategies in HNSC.
Jingxin Guo, Zi-Feng Cui, Jinhang Wang et al.· Discover Oncology· 0 citations
Introduction Head and neck cancer (HNC) is characterized by substantial immune heterogeneity and limited availability of clinically actionable molecular targets. Here, we developed an integrative single-cell eQTL-driven multi-omics framework to identify immune cell-specific causal genes and prioritize drug-repurposing candidates for HNC. Methods Single-cell eQTL data from the OneK1K cohort were integrated with European HNC GWAS summary statistics through two-sample Mendelian randomization, followed by transcriptomic differential expression analysis and weighted gene co-expression network analysis. Candidate targets were further evaluated using diagnostic modeling, immune infiltration analysis, single-cell and spatial transcriptomics, Bayesian colocalization, Western blot validation, molecular docking, molecular dynamics simulations, and FAERS-based safety profiling. Results We identified 494 immune cell-specific eGenes causally associated with HNC risk. Multi-layered target prioritization highlighted AIM1 and ANXA1 as protective immune-related genes, both of which were downregulated in HNC tissues and showed cell-type-preferential expression in T cells and monocytes, respectively. A dual-gene diagnostic model achieved strong discrimination performance with an AUC of 0.917. Colocalization analysis supported shared genetic signals between AIM1 or ANXA1 loci and HNC susceptibility, while Western blotting confirmed reduced AIM1 and ANXA1 protein expression in SCC-9 cells compared with normal HOK cells. Drug screening and molecular docking identified topotecan as a candidate ligand for AIM1 and terbutaline as a candidate ligand for ANXA1. Subsequent molecular dynamics simulations demonstrated stable drug–target complexes with favorable binding free energies. FAERS analysis further characterized the adverse-event spectrum and potential safety considerations for both compounds. Discussion Collectively, this study provides a single-cell genetic and pharmacological framework for defining immune-related causal targets in HNC and supports AIM1 and ANXA1 as promising biomarkers and therapeutic entry points for precision drug development.
Zhangwei Xue, Guo-Hang Shen, Gongbiao Lin et al.· Frontiers in Oncology· 0 citations
This study integrates multi-omics datasets to identify candidate biomarkers that may influence TNBC progression and modulate therapeutic response and nominate CCND2 and KIF1A as candidate biomarkers and potential therapeutic targets in TNBC.
Roberto Aguilar, Victor Wang, Shane Deng· Journal of Immunology· 0 citations
It is suggested that TRIP6 may be involved in linking microenvironmental signaling to invasive phenotypes, with potential value for prognostic stratification and therapeutic exploration.
Qiwei Cui, Xiao-Hong Gao, Xiaoqing Wu et al.· Frontiers in Cell and Develo...· 0 citations
We use cookies to run the site and, with your consent, for analytics and to show ads.
See our Cookie Policy.
