Integrated Analysis Reveals ENDOU as a Biomarker in Head and Neck Squamous Cell Carcinoma Progression

E2F expression profiling-based subtypes in head and neck squamous cell carcinoma: clinical relevance, prognostic implications, and personalized therapy

BACKGROUND

Head and neck squamous cell carcinoma (HNSCC) is a heterogeneous malignancy with poor prognosis. Dysregulation of E2F transcription factors (E2Fs), which control cell proliferation and apoptosis, is implicated in HNSCC pathogenesis. This study explores HNSCC molecular heterogeneity via E2Fs expression, identifies distinct subtypes, and develops a prognostic model that integrates gene expression, immune infiltration, and drug sensitivity.

METHODS

We analyzed the TCGA-HNSC dataset (n = 494) and classified samples based on the expression of eight E2Fs using ConsensusClusterPlus. The optimal number of clusters (k = 2) was determined with the getOptK() function, which assesses cluster stability via internal consistency metrics. Differentially expressed genes between subtypes were identified with limma, and functional annotation was performed using Gene Ontology and Kyoto Encyclopedia of Genes and Genomes pathway analyses. A prognostic model was constructed using LASSO regression on genes significant in univariate Cox analysis and validated in an independent GSE41613 dataset (n = 97). Immune cell infiltration was estimated using CIBERSORT, and drug sensitivity predicted via pRRophetic. Confounding factors such as HPV and smoking status were not included due to incomplete data.

RESULTS

Two distinct E2F-based subtypes emerged. Cluster 1, characterized by lower E2Fs expression, exhibited poorer overall survival (log-rank, p = 0.035) and was enriched in genes related to epidermal development, keratinocyte differentiation, and IL-17 signaling. In contrast, Cluster 2 showed higher E2Fs expression, better survival, and enrichment in genes associated with DNA replication and repair. Notably, high-risk patients demonstrated increased infiltration of M0 and M2 macrophages (p < 0.05), suggesting an immunosuppressive tumor microenvironment that adversely affects prognosis. Our seven-gene prognostic model (AREG, CXCL14, FAM83E, FDCSP, ARHGAP4, EPHX3, and SPINK6) exhibited robust performance with AUCs of 0.692, 0.673, and 0.679 for 1-, 3-, and 5-year survival, a C-index of 0.66, and good calibration. High-risk patients also showed greater sensitivity to targeted agents such as pazopanib and imatinib.

CONCLUSIONS

These findings reveal two distinct E2F-based molecular subtypes of HNSCC that differ in prognosis, functional pathways, immune infiltration, and drug sensitivity. The prognostic model offers valuable risk stratification and identifies potential biomarkers and therapeutic targets, warranting further experimental and clinical validation.

Molecular basis for the calcium-dependent activation of the ribonuclease EndoU

Ribonucleases (RNases) are ubiquitous enzymes that process or degrade RNA, essential for cellular functions and immune responses. The EndoU-like superfamily includes endoribonucleases conserved across bacteria, eukaryotes, and certain viruses, with an ancient evolutionary link to the ribonuclease A-like superfamily. Both bacterial EndoU and animal RNase A share a similar fold and function independently of cofactors. In contrast, the eukaryotic EndoU catalytic domain requires divalent metal ions for catalysis, possibly due to an N-terminal extension near the catalytic core. In this study, we use biophysical and computational techniques along with in vitro assays to investigate the calcium-dependent activation of human EndoU. We determine the crystal structure of EndoU bound to calcium and find that calcium binding remote from the catalytic triad triggers water-mediated intramolecular signaling and structural changes, activating the enzyme through allostery. Calcium binding involves residues from both the catalytic core and the N-terminal extension, indicating that the N-terminal extension interacts with the catalytic core to modulate activity in response to calcium. Our findings suggest that similar mechanisms may be present across all eukaryotic EndoUs, highlighting a unique evolutionary adaptation that connects endoribonuclease activity to cellular signaling in eukaryotes.

1H, 13C and 15N backbone resonance assignment of the calcium-activated EndoU endoribonuclease

The catalytic domain of the calcium-dependent endoribonuclease EndoU from Homo sapiens was expressed in E. coli with 13C and 15N labeling. A nearly complete assignment of backbone 1H, 15N, and 13C resonances was obtained, as well as a secondary structure prediction based on the assigned chemical shifts. The predicted secondary structures were almost identical to the published crystal structure of calcium-activated EndoU. This is the first NMR study of an eukaryotic member of the EndoU-like superfamily of ribonucleases.

Molecular Basis for the Calcium-Dependent Activation of the Ribonuclease EndoU

Ribonucleases (RNases) are ubiquitous enzymes that process or degrade RNA, essential for cellular functions and immune responses. The EndoU-like superfamily includes endoribonucleases conserved across bacteria, eukaryotes, and certain viruses, with an ancient evolutionary link to the ribonuclease A-like superfamily. Both bacterial EndoU and animal RNase A share a similar fold and function independently of cofactors. In contrast, the eukaryotic EndoU catalytic domain requires divalent metal ions for catalysis, possibly due to an N-terminal extension near the catalytic core. In this study, we used biophysical and computational techniques along with in vitro assays to investigate the calcium-dependent activation of human EndoU. We determined the crystal structure of EndoU bound to calcium and found that calcium binding remote from the catalytic triad triggers water-mediated intramolecular signaling and structural changes, activating the enzyme through allostery. Calcium-binding involves residues from both the catalytic core and the N-terminal extension, indicating that the N-terminal extension interacts with the catalytic core to modulate activity in response to calcium. Our findings suggest that similar mechanisms may be present across all eukaryotic EndoUs, highlighting a unique evolutionary adaptation that connects endoribonuclease activity to cellular signaling in eukaryotes.

The Upstream 1350~1250 Nucleotide Sequences of the Human ENDOU-1 Gene Contain Critical Cis-Elements Responsible for Upregulating Its Transcription during ER Stress

ENDOU-1 encodes an endoribonuclease that overcomes the inhibitory upstream open reading frame (uORF)-trap at 5'-untranslated region (UTR) of the CHOP transcript, allowing the downstream coding sequence of CHOP be translated during endoplasmic reticulum (ER) stress. However, transcriptional control of ENDOU-1 remains enigmatic. To address this, we cloned an upstream 2.1 kb (-2055~+77 bp) of human ENDOU-1 (pE2.1p) fused with reporter luciferase (luc) cDNA. The promoter strength driven by pE2.1p was significantly upregulated in both pE2.1p-transfected cells and pE2.1p-injected zebrafish embryos treated with stress inducers. Comparing the luc activities driven by pE2.1p and -1125~+77 (pE1.2p) segments, we revealed that cis-elements located at the -2055~-1125 segment might play a critical role in ENDOU-1 upregulation during ER stress. Since bioinformatics analysis predicted many cis-elements clustered at the -1850~-1250, we further deconstructed this segment to generate pE2.1p-based derivatives lacking -1850~-1750, -1749~-1650, -1649~-1486, -1485~-1350 or -1350~-1250 segments. Quantification of promoter activities driven by these five internal deletion plasmids suggested a repressor binding element within the -1649~-1486 and an activator binding element within the -1350~-1250. Since luc activities driven by the -1649~-1486 were not significantly different between normal and stress conditions, we herein propose that the stress-inducible activator bound at the -1350~-1250 segment makes a major contribution to the increased expression of human ENDOU-1 upon ER stresses.

Molecular classification of human papilloma virus-negative head and neck squamous cell carcinomas: Cell cycle-based classifier and prognostic signature

The molecular classification of human papillomavirus (HPV)-negative head and neck squamous cell carcinomas (HNSCCs) remains questionable. Differentially expressed genes were detected between tumor and normal tissues and GSEA showed they are associated with cell cycle pathways. This study aimed to classify HPV-negative HNSCCs based on cell cycle-related genes. The established gene pattern was correlated with tumor progression, clinical prognosis, and drug treatment efficacy. Biological analysis was performed using HNSCC patient sample data obtained from the Cancer Genome Atlas (TCGA), Clinical Proteomic Tumor Analysis Consortium (CPTAC), and Gene Expression Omnibus (GEO) databases. All samples included in this study contained survival information. RNA sequencing data from 740 samples were used for the analysis. Previously characterized cell cycle-related genes were included for unsupervised consensus clustering. Two subtypes of HPV-negative HNSCCs (C1, C2) were identified. Subtype C1 displayed low cell cycle activity, 'hot' tumor microenvironment (TME), earlier N stage, lower pathological grade, better prognosis, and higher response rate to the immunotherapy and targeted therapy. Subtype C2 was associated with higher cell cycle activity, 'cold' TME, later N stage, higher pathological grade, worse prognosis, and lower response rate to the treatment. According to the nearest template prediction method, classification rules were established and verified. Our work explored the molecular mechanism of HPV-negative HNSCCs in the view of cell cycle and might provide new sights for personalized anti-cancer treatment.

The endoribonuclease Arlr is required to maintain lipid homeostasis by downregulating lipolytic genes during aging

While disorders in lipid metabolism have been associated with aging and age-related diseases, how lipid metabolism is regulated during aging is poorly understood. Here, we characterize the Drosophila endoribonuclease CG2145, an ortholog of mammalian EndoU that we named Age-related lipid regulator (Arlr), as a regulator of lipid homeostasis during aging. In adult adipose tissues, Arlr is necessary for maintenance of lipid storage in lipid droplets (LDs) as flies age, a phenotype that can be rescued by either high-fat or high-glucose diet. Interestingly, RNA-seq of arlr mutant adipose tissues and RIP-seq suggest that Arlr affects lipid metabolism through the degradation of the mRNAs of lipolysis genes - a model further supported by the observation that knockdown of Lsd-1, regucalcin, yip2 or CG5162, which encode genes involved in lipolysis, rescue the LD defects of arlr mutants. In addition, we characterize DendoU as a functional paralog of Arlr and show that human ENDOU can rescue arlr mutants. Altogether, our study reveals a role of ENDOU-like endonucleases as negative regulator of lipolysis.

Reprogramming of the transcriptome after heat stress mediates heat hormesis in Caenorhabditis elegans

Transient stress experiences not only trigger acute stress responses, but can also have long-lasting effects on cellular functions. In Caenorhabditis elegans, a brief exposure to heat shock during early adulthood extends lifespan and improves stress resistance, a phenomenon known as heat hormesis. Here, we investigated the prolonged effect of hormetic heat stress on the transcriptome of worms and found that the canonical heat shock response is followed by a profound transcriptional reprogramming in the post-stress period. This reprogramming relies on the endoribonuclease ENDU-2 but not the heat shock factor 1. ENDU-2 co-localizes with chromatin and interacts with RNA polymerase II, enabling specific regulation of transcription after the stress period. Failure to activate the post-stress response does not affect the resistance of animals to heat shock but eliminates the beneficial effects of hormetic heat stress. In summary, our work discovers that the RNA-binding protein ENDU-2 mediates the long-term impacts of transient heat stress via reprogramming transcriptome after stress exposure.

Integrative meta-analysis of gene expression profiles identifies FEN1 and ENDOU as potential diagnostic biomarkers for cervical squamous cell carcinoma

Cervical carcinoma is a global public health burden. Given that it is usually asymptomatic at potentially curative stages, the development of clinically accurate tests is critical for early detection and individual risk stratification. The present study performed an integrative meta-analysis of the transcriptomes from 10 cervical carcinoma cohorts, with the aim of identifying biomarkers that are associated with malignant transformation of cervical epithelium, and establish their clinical applicability. From among the top ranked differentially expressed genes, flap structure-specific endonuclease 1 (FEN1) and poly (U)-specific endoribonuclease (ENDOU) were selected for further validation, and their clinical applicability was assessed using immunohistochemically stained microarrays comprising 110 tissue cores, using p16 and Ki67 staining as the comparator tests. The results demonstrated that FEN1 expression was significantly upregulated in 65% of tumor specimens (P=0.0001), with no detectable expression in the non-tumor tissues. Furthermore, its expression was significantly associated with Ki67 staining in tumor samples (P<0.0001), but no association was observed with p16 expression or the presence of human papilloma virus types 16/18, patient age, tumor grade or stage. FEN1 staining demonstrated lower sensitivity than p16 (69.3 vs. 96.8%) and Ki67 (69.3 vs. 76.3%); however, the specificity was identical to p16 and higher than that of Ki67 (100 vs. 71.4%).ENDOU staining was consistent with the microarray results, demonstrating 1% positivity in tumors and 40% positivity in non-tumor tissues. Gene set enrichment analysis of cervical tumors overexpressing FEN1 revealed its association with enhanced growth factor signaling, immune response inhibition and extracellular matrix remodeling, whereas tumors with low ENDOU expression exhibited inhibition of epithelial development and differentiation processes. Taken together, the results of the present study demonstrate the feasibility of the integrative meta-analysis approach to identify relevant biomarkers associated with cervical carcinogenesis. Thus, FEN1 and ENDOU may be useful diagnostic biomarkers for squamous cervical carcinoma. However, further studies are required to determine their diagnostic performance in larger patient cohorts and validate the results presented here.

A Transcriptomic Analysis of Head and Neck Squamous Cell Carcinomas for Prognostic Indications

Survival analysis of the Cancer Genome Atlas (TCGA) dataset is a well-known method for discovering gene expression-based prognostic biomarkers of head and neck squamous cell carcinoma (HNSCC). A cutoff point is usually used in survival analysis for patient dichotomization when using continuous gene expression values. There is some optimization software for cutoff determination. However, the software's predetermined cutoffs are usually set at the medians or quantiles of gene expression values. There are also few clinicopathological features available in pre-processed datasets. We applied an in-house workflow, including data retrieving and pre-processing, feature selection, sliding-window cutoff selection, Kaplan-Meier survival analysis, and Cox proportional hazard modeling for biomarker discovery. In our approach for the TCGA HNSCC cohort, we scanned human protein-coding genes to find optimal cutoff values. After adjustments with confounders, clinical tumor stage and surgical margin involvement were found to be independent risk factors for prognosis. According to the results tables that show hazard ratios with Bonferroni-adjusted p values under the optimal cutoff, three biomarker candidates, CAMK2N1, CALML5, and FCGBP, are significantly associated with overall survival. We validated this discovery by using the another independent HNSCC dataset (GSE65858). Thus, we suggest that transcriptomic analysis could help with biomarker discovery. Moreover, the robustness of the biomarkers we identified should be ensured through several additional tests with independent datasets.