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.
Abstract
Background
Head and neck squamous cell carcinoma (HNSC) is a highly aggressive malignancy characterized by a complex tumor microenvironment (TME). Despite advances in immunotherapy, the immunosuppressive microenvironment driven by metabolic reprogramming remains a critical factor contributing to treatment failure. The prognostic value of PHLDA3, a target gene of the p53 family, in HNSC and its specific mechanisms in shaping TME heterogeneity remain ill-defined.
Methods
This study integrated large-scale transcriptomic data from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases, alongside single-cell RNA sequencing (scRNA-seq) data. A prognostic nomogram incorporating PHLDA3 and clinical characteristics was constructed using multivariate Cox regression analysis. Biological functions were assessed utilizing Weighted Gene Co-expression Network Analysis (WGCNA), Gene Set Variation Analysis (GSVA), and the drug sensitivity prediction algorithm, oncoPredict. At the single-cell resolution, algorithms including Seurat, CellChat, scMetabolism, and Monocle 2 were employed to comprehensively characterize cell type annotation, intercellular communication, metabolic activity scoring, and pseudotime differentiation trajectories.
Results
PHLDA3 was significantly upregulated in HNSC tissues and strongly correlated with poor overall survival (OS). The PHLDA3-based nomogram demonstrated superior calibration and discrimination capabilities in both the training and validation cohorts. Genomic analysis revealed that high PHLDA3 expression was associated with a lower Tumor Mutation Burden (TMB) but an increased sensitivity to the PLK1 inhibitor, BI-2536. Single-cell analysis further unveiled that PHLDA3 expression was not ubiquitous; rather, it was specifically enriched in tumor-associated macrophage (TAM) subsets characterized by hypoxic and lipid metabolic signatures (Hypoxic TAMs and Lipid TAMs). These subpopulations exhibited transcriptomic signatures indicative of enhanced glycolysis and orchestrated immunosuppressive communication networks within the TME, predominantly via the SPP1-CD44 and MIF-CD74 signaling axes. Ultimately, through its specific enrichment in these metabolically reprogrammed TAM subsets, PHLDA3 intimately participates in remodeling an immunosuppressive TME, thereby facilitating tumor progression and immune evasion.
Conclusions
PHLDA3 serves as a robust prognostic biomarker for HNSC. Its elevated expression is indicative not only of a low TMB status but also of a critical association with metabolically reprogrammed SPP1+ TAM subpopulations. By potentially sustaining the survival and function of these specific TAMs under hypoxic conditions, PHLDA3 drives the formation of an immunosuppressive microenvironment, highlighting a promising therapeutic target for combined metabolic-immune strategies in HNSC.
Head and neck squamous cell carcinoma (HNSCC) is among the leading cancers across the globe and continues to be related to unfavorable clinical outcomes. In many cases, limited survival and poor prognosis remain major challenges. Recent studies revealed that the tumor microenvironment (TME) is key to HNSCC progression and might partly account for the suboptimal response to immunotherapy observed in a large proportion of patients. To better characterize TME heterogeneity, the research combines single-cell RNA sequencing (scRNA-seq) with bulk RNA sequencing (bulk RNA-seq) data to develop a prognostic model for HNSCC using publicly available datasets. The scRNA-seq data were obtained from the Gene expression omnibus (GEO) database, while bulk RNA-seq data were retrieved from the UCSC Xena platform. Cell populations within HNSCC samples were annotated using R-based analytical workflows. Malignant cell populations were inferred through infer copy number variation (inferCNV) analysis. Differentially expressed genes (DEGs) were observed via bioinformatic approaches, and weighted gene co-expression network analysis (WGCNA) was applied to detect modules associated with tumor-related traits. Overlapping genes were subsequently selected for downstream analyses, including prognostic model construction, gene set enrichment analysis (GSEA), gene set variation analysis (GSVA), immune infiltration assessment, mutation profiling, along with drug sensitivity evaluation. 8 cell clusters were identified from scRNA-seq data. Among them, epithelial cells exhibited the strongest malignant features, as indicated by higher CNV levels compared with T cells. Integration of 106 epithelial marker genes, 279 DEGs, and 1089 module genes led to the identification of 2 key genes, KRT5 and TUBA1B. A prognostic model incorporating risk score, clinical stage, and age was subsequently established, showing a significant difference in overall survival between high- and low-risk groups. Enrichment analyses revealed that cancer-related pathways, including proteoglycans in cancer and HIF-1 signaling cascade, were prominently involved. GSVA indicated increased activity in telomere tethering at the nuclear periphery in the high-expression group, whereas pathways related to cilium movement were relatively suppressed. Immune infiltration analysis suggested a generally limited responsiveness of HNSCC to immunotherapy in the absence of specific clinical indicators. In addition, several compounds, including BRD.K37390332, NSC.74859, fluvastatin, and pifithrin-α, were identified as potential therapeutic candidates, although further validation is required. Through the combination of scRNA-seq and bulk RNA-seq data, this study establishes a prognostic model with moderate predictive performance for HNSCC. The genes KRT5 and TUBA1B emerge as potential biomarkers. Despite these findings, the predicted sensitivity to immunotherapy remains limited derived from computational analyses, highlighting the necessity for additional experimental and clinical confirmation.
Jia-Yi Chen· Journal of King Saud Univers...· 0 citations
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.
Jiaqi Tang, Yu-Lun He, Yuqi Wang et al.· Frontiers in Immunology· 0 citations
A robust 17-gene ASIG-based prognostic signature that effectively stratified BRCA patients into high- and low-risk groups and served as an independent prognostic predictor is established, providing a robust tool for patient risk stratification and offering biological insights into senescence-driven microenvironmental remodeling.
Peng-Cheng Chen, Yindan Lin, Jingjia Li et al.· Genes· 0 citations
Background: Head and neck squamous cell carcinoma (HNSCC) is biologically heterogeneous, and many public-data gene signatures lack cross-platform replication and unbiased evaluation.
Objective: We sought reproducible tumor–normal expression programs and tested the transportability of a derived seven-gene score.
Methods: TCGA-HNSC RNA-sequencing defined differentially expressed genes (DEGs) between 520 tumors and 44 normal tissues using TMM normalization and voom–limma, with paired sensitivity analysis. Concordant genes were replicated in 22 GSE6631 matched pairs and analyzed for GO and KEGG enrichment. A seven-gene overall-survival score was developed in event-stratified TCGA training data (n=361), evaluated in held-out TCGA (n=156), repeated nested resampling, and examined in GSE65858 (n=253). ESTIMATE and marker scores characterized tumor-microenvironment features.
Results: Among 5,657 TCGA and 168 GSE6631 DEGs, 151 replicated. Upregulated genes were enriched for extracellular-matrix organization, ECM–receptor interaction, integrin signaling, focal adhesion, and PI3K–Akt signaling. The score was associated with survival in training (HR per SD=1.68; C-index=0.642) but not held-out TCGA (HR=1.02; C-index=0.546) or unadjusted GSE65858 (HR=1.15; C-index=0.548). Median nested C-index was 0.564. HPV adjustment attenuated the GSE65858 association. The score correlated with CAF/fibroblast (ρ=0.269) and stromal scores (ρ=0.228).
Conclusion: Replicated expression changes support an ECM–CAF program, but the seven-gene score did not generalize and is not a validated prognostic model.
Reisha Notonegoro, Bjorka Alma, P. Wulandari et al.· Sriwijaya Journal of Otorhin...· 0 citations
Background: Although the tumor coagulome interacts with the tumor immune microenvironment (TME) in solid tumors, its role in osteosarcoma (OS) remains uncharacterized. This study aimed to delineate this transcriptomic interplay and identify potential prognostic targets. Methods: This study was performed with bulk RNA sequencing (RNA-seq), single-cell RNA sequencing (scRNA-seq), and clinical phenotype data. Bioinformatic approaches were employed at the transcriptomic level to investigate the impact of the tumor coagulome on the TME and prognosis in OS. We validated the above findings using immunohistochemistry and immunofluorescence. Results: The activity of a coagulation-related transcriptional signature was found to correlate with the degree of malignancy in OS. Its activity score demonstrated predictive value for OS prognosis, with a maximum area under the curve (AUC) of 0.802. scRNA-seq analysis indicated that inflammatory cancer-associated fibroblasts (iCAFs) and APOE+ macrophages were predominantly enriched in the high coagulation score subgroup. Our data further suggest that iCAFs may facilitate the M2 polarization of APOE+ macrophages via the C3–C3AR1 axis, potentially contributing to poorer clinical outcomes in patients with OS. Conclusions: These findings imply that within a high coagulation-related transcriptional score group, the interaction between iCAFs and APOE+ macrophages, likely mediated by the C3–C3AR1 axis, could facilitate OS progression. Consequently, the C3–C3AR1 signaling pathway might represent a promising target for future therapeutic strategies and coagulome monitoring in OS.
Jianhua Mu, Yi-Tian Wang, Han Liu et al.· Biomedicines· 0 citations
Background Esophageal squamous cell carcinoma (ESCC) has high mortality, and metastasis is the leading cause of patient death. Neuromedin B (NMB) promotes tumor development in various cancers, yet its role in ESCC metastasis remains unclear. Methods We integrated single-cell transcriptomic data from matched primary and metastatic ESCC lesions (GSE309392) with bulk transcriptomic cohorts from TCGA and GSE53624. In silico gene perturbation, ligand-receptor communication analysis, and single-cell prognostic model construction were performed, followed by functional validation through siRNA-mediated NMB knockdown in TE-1 and KYSE30 cell lines. Results NMB was identified as a key gene enriched in metastatic ESCC lesions, and its high expression was associated with coordinated upregulation of oxidative phosphorylation pathway genes and aldo-keto reductase family antioxidant enzymes (AKR1C1, AKR1C2, AKR1B10). Genomic analysis revealed that NMB-high tumors carried a higher clonal mutation burden and a markedly increased frequency of NFE2L2 activating mutations (23% vs. 8%, P = 0.04). In silico knockout and correlation analysis identified AKR1C1 as a downstream effector of NMB. NMB expression was negatively correlated with CD8+ T cell and activated NK cell infiltration. CellChat analysis revealed communication between NMB-positive cells and monocytes via the TGM2–ADGRG1 axis, and specifically detected IFNG signaling. In the single-cell prognostic model, NMB-positive cells accounted for 50% of the high-risk group but only 20% of the low-risk group. TCGA-based survival analysis demonstrated that high NMB expression was associated with shorter overall survival (HR = 2.98, P = 0.03). In vitro NMB-targeted RNA interference markedly inhibited proliferation, colony formation, and migration in TE-1 and KYSE30 cells. CMap screening identified the endothelin-PDE5-cGMP axis as a potential therapeutic target. Conclusion NMB serves as a key driver of metastatic adaptation in ESCC, conferring a survival advantage to tumor cells during metastatic colonization through genomic evolution and immune remodeling, with metabolic adaptation as a downstream consequence of genomic alterations.
Zhi-Kai Cao, Dong-Chen Tian, Long He et al.· Frontiers in Cell and Develo...· 0 citations
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