A six-gene expression signature related to angiolymphatic invasion is associated with poor survival in laryngeal squamous cell carcinoma

The gene signature linked to lactate metabolism predicts the prognosis and correlates with the immune status of head and neck squamous cell carcinoma

Lactate, traditionally viewed as a byproduct of glycolysis, is increasingly recognized as a pivotal regulatory factor in cancer biology. This study addresses the limited understanding of lactate metabolism-related genes in head and neck squamous cell carcinoma (HNSC) by constructing a prognostic risk model centered on these genes to enhance prediction and treatment strategies for HNSC. Utilizing the Lactate Metabolism score (LMs) derived from The Cancer Genome Atlas (TCGA), we identified five key genes significantly associated with prognosis in HNSC patients. These genes were integrated into a prognostic risk model developed through Cox regression analysis, which demonstrated superior predictive performance, achieving area under the curve (AUC) values greater than 0.8 for five-year survival. The risk scores generated by our model were significantly correlated with critical features of the tumor microenvironment, including immune characteristics and markers of immune evasion. Higher risk scores correlated with a more tumor-promoting microenvironment and increased immune suppression, underscoring the model's relevance in understanding HNSC progression. Additionally, eight critical hub genes were identified, revealing significant differences in gene expression between risk score groups. Functional analyses demonstrated that the low-risk group exhibited a more favorable prognosis and enhanced immune characteristics. Our findings suggest that the lactate metabolism-based prognostic model may have implications for guiding the development of personalized treatment approaches, as it highlights the potential for targeted interventions that could modulate the tumor microenvironment and immune response.

Comprehensive Analysis of Clinical and Molecular Features in Cancer Patients Associated With Major Human Oncoviruses

Viral infections contribute to a higher incidence of cancer than any other individual risk factor. This study aimed to compare the clinical and molecular features of four viral-associated cancers: stomach adenocarcinoma (STAD), head and neck squamous cell carcinoma (HNSC), liver hepatocellular carcinoma (LIHC), and cervical squamous cell carcinoma (CESC). Patients were categorized based on viral infection status, as provided in the clinical data, into virus-associated and non-virus-associated groups, followed by a comprehensive comparison of clinical and molecular features. Our analysis disclosed that viral infections confer unique clinical and molecular signatures to their associated tumors. Specifically, human papillomavirus-associated (HPV+) HNSC and hepatitis B virus-associated (HBV+) LIHC patients were predominantly male, younger, and exhibited better clinical prognoses. Virus-associated tumors displayed enhanced immune microenvironments and high DNA damage response scores, while non-virus-associated tumors were enriched in stromal signatures. HPV+ HNSC and Epstein-Barr virus-associated (EBV+) STAD showed similarities across multi-omics features, including better responses to immunotherapy, lower TP53 mutation rates, tumor mutation burden (TMB), and copy number alteration (CNA). Conversely, HBV+, Hepatitis C virus-associated (HCV+) LIHCs and HPV+ CESC were more genomically unstable due to high TP53 mutation rates, TMB, and CNA. At the protein level, Caspase-7 and Syk were upregulated in HPV+ HNSC and EBV+ STAD, and positively correlated with the enrichment levels of CD8 + T cell, PD-L1, and cytolytic activity. Patient stratification based on infection status has significant clinical implications, particularly for patient prognosis and drug response.

Establishment of a prognostic model toward lung squamous cell carcinoma based on m7G-related genes in the cancer genome atlas

Lung squamous cell carcinoma (LUSC) is a non-small cell lung cancer with a poor prognosis owing to late diagnosis. New molecular markers are urgently needed to improve the diagnosis and prognosis of LUSC. 7-Methylguanosine (m7G) modifications, a tRNA modification, are common in eubacteria, eukaryotes, and a few archaea. These modifications promote the turnover and stability of some mRNAs to prevent mRNA decay, improve translation efficiency, and reduce ribosomal pausing but are associated with poor survival in human cancer cells. However, expression of m7G-related genes in LUSC and their association with prognosis remain unclear. In the present study, we identified nine differentially expressed genes related to prognosis by comparing the expression profiles of tumor tissues (502 LUSC reports) with normal tissues (49 adjacent nontumor lung tissue reports). The genes included six upregulated genes (KLK7, LCE3E, AREG, KLK6, ZBED2, and MAPK4) and three downregulated genes (ADH1C, NTS, and ERLIN2). Based on these nine genes, patients with LUSC were classified into low- and high-risk groups to analyze the trends in prognosis. We found that the nine m7G-related genes play important roles in immune regulation, hormone regulation, and drug sensitivity through pathways including antigen processing and presentation, adherent plaques, extracellular matrix receptor interactions, drug metabolism of cytochrome P-450, and metabolism of cytochrome P-450 to xenobiotics; the functions of these genes are likely accomplished in part by m6A modifications. The effect of m7G-related genes on the diagnosis and prognosis of LUSC was further indicated by population analysis.NEW & NOTEWORTHY Based on the differential expression of 7-methylguanosine (m7G) modification-associated genes between normal and lung squamous cell carcinoma (LUSC) tissues, and considering the performance of our m7G-related gene risk profiles as independent risk factors in predicting overall survival, we conclude that m7G modification is closely linked to the development of LUSC. In addition, this study offers a new genetic marker for predicting the prognosis of patients with LUSC and presents a crucial theoretical foundation for future investigations on the relationship between m7G modification-related genes, immunity, and drug sensitivity in LUSC.

Circular RNA circSLC7A11 contributes to progression and stemness of laryngeal squamous cell carcinoma via sponging miR-877-5p from LASP1

Background

Laryngeal squamous cell carcinoma (LSCC) belongs to tumors of head and neck. Circular RNA circSLC7A11 functions as oncogenes in various tumors. However, the role of circSLC7A11 in LSCC remains largely unknown. Here, we aimed to clarify the circSLC7A11 function in LSCC.

Methods

Relevance between circSLC7A11 expressions and LSCC clinicopathological was checked using chi-square. Relevance between circSLC7A11 expressions and LSCC patients' survival time was validated using Kaplan-Meier analysis. CircSLC7A11 expressions in LSCC tissues and cells were determined using quantitative real-time PCR. CircSLC7A11 functions in LSCC were examined by Cell Counting Kit-8, EdU analysis, Western blot, flow cytometry, sphere formation assay, and Transwell analysis. Meanwhile, circSLC7A11 mechanism in LSCC was determined using dual-luciferase reporter analysis, RNA pull-down, RNA Immunoprecipitation.

Results

CircSLC7A11 was highly expressed in LSCC, and high circSLC7A11 expressions were interrelated to the TNM stage. Also, LSCC patients with high circSLC7A11 owned shorter overall survival. Functional studies revealed that circSLC7A11 knockdown reduced LSCC cell proliferation, migration, invasion, stemness characteristics, and enhanced cell apoptosis. Mechanistic study data corroborated that circSLC7A11 targeted miR-877-5p, miR-877-5p targeted LASP1. LASP1 was negatively interrelated to miR-877-5p and was positively interrelated to circSLC7A11 in LSCC tissues. Also, circSLC7A11 knockdown reduced the LASP1 levels, and miR-877-5p inhibitor co-transfection reversed this reduction. Rescue assays further demonstrated that circSLC7A11 accelerated LSCC through miR-877-5p/LASP1.

Conclusion

CircSLC7A11 exerted oncogenic functions in LSCC by miR-877-5p/LASP1, hinting that circSLC7A11 was a novel biomarker for LSCC.

Identification of molecular classification and gene signature for predicting prognosis and immunotherapy response in HNSCC using cell differentiation trajectories

Head and neck squamous cell carcinoma (HNSCC) is a highly heterogeneous malignancy with poor prognosis. This article aims to explore the clinical significance of cell differentiation trajectory in HNSCC, identify different molecular subtypes by consensus clustering analysis, and develop a prognostic risk model on the basis of differentiation-related genes (DRGs) for predicting the prognosis of HNSCC patients. Firstly, cell trajectory analysis was performed on single-cell RNA sequencing (scRNA-seq) data, four molecular subtypes were identified from bulk RNA-seq data, and the molecular subtypes were predictive of patient survival, clinical features, immune infiltration status, and expression of immune checkpoint genes (ICGs)s. Secondly, we developed a 10-DRG signature for predicting the prognosis of HNSCC patients by using weighted correlation network analysis (WGCNA), differential expression analysis, univariate Cox regression analysis, and multivariate Cox regression analysis. Then, a nomogram integrating the risk assessment model and clinical features can successfully predict prognosis with favorable predictive performance and superior accuracy. We projected the response to immunotherapy and the sensitivity of commonly used antitumor drugs between the different groups. Finally, we used the quantitative Reverse Transcription-Polymerase Chain Reaction (qRT-PCR) analysis and western blot to verify the signature. In conclusion, we identified distinct molecular subtypes by cell differentiation trajectory and constructed a novel signature based on differentially expressed prognostic DRGs, which could predict the prognosis and response to immunotherapy for patients and may provide valuable clinical applications in the treatment of HNSCC.

A multifaceted and feasible prognostic model of amino acid metabolism-related genes in the immune response and tumor microenvironment of head and neck squamous cell carcinomas

We investigated the role of amino acid metabolism (AAM) in head and neck squamous cell carcinoma (HNSCC) tissues to explore its prognostic value and potential therapeutic strategies. A risk score based on four AAM-related genes (AMG) was constructed that could predict the prognosis of HNSCC. These four genes were up-regulated in HNSCC tissues and might act as oncogenes. Internal validation in The Cancer Genome Atlas (TCGA) by bootstrapping showed that patients with high-risk scores had a poorer prognosis than patients with low-risk scores, and this was confirmed in the Gene Expression Omnibus (GEO) cohort. There were also differences between the high-risk and low-risk groups in clinical information and different anatomical sites such as age, sex, TNM stage, grade stage, surgery or no surgery, chemotherapy, radiotherapy, no radiotherapy, neck lymph node dissection or not, and neck lymphovascular invasion, larynx, overlapping lesion of lip, and oral cavity and pharynx tonsil of overall survival (OS). Immune-related characteristics, tumor microenvironment (TME) characteristics, and immunotherapy response were significantly different between high- and low-risk groups. The four AMGs were also found to be associated with the expression of markers of various immune cell subpopulations. Therefore, our comprehensive approach revealed the characterization of AAM in HNSCC to predict prognosis and guide clinical therapy.

SLC18A3 promoted renal cancer development through acetylcholine/cAMP signaling

Renal cancer displays a high metastatic potential and a poor response to chemotherapy. However, the critical contributors to renal cancer development remain elusive. This study focused on acetylcholine (ACh) signaling. We identified the vesicular acetylcholine transporter (SLC18A3) that upregulates in patients with renal cancer. We further discovered that SLC18A3 enhanced the uptake of ACh, a classical neurotransmitter mediating synaptic transmission. The elevated ACh activated the protein kinase A (PKA)/cAMP-response element binding protein (CREB) pathway, which contributed to renal cancer cell proliferation and invasive migration. Consistently, SLC18A3 overexpression caused sustained tumor growth and increased lung metastases in A489-bearing mice. In summary, our study demonstrated that SLC18A3 contributed to cancer spread in an ACh/PKA/CREB-dependent manner, which may drive the design of efficacious treatment strategies.

Epigenome-wide gene–age interaction study reveals reversed effects of MORN1 DNA methylation on survival between young and elderly oral squamous cell carcinoma patients

DNA methylation serves as a reversible and prognostic biomarker for oral squamous cell carcinoma (OSCC) patients. It is unclear whether the effect of DNA methylation on OSCC overall survival varies with age. As a result, we performed a two-phase gene–age interaction study of OSCC prognosis on an epigenome-wide scale using the Cox proportional hazards model. We identified one CpG probe, cg11676291_MORN1, whose effect was significantly modified by age (HR_discovery = 1.018, p = 4.07 × 10⁻⁰⁷, FDR-q = 3.67 × 10⁻⁰²; HR_validation = 1.058, p = 8.09 × 10⁻⁰³; HR_combined = 1.019, p = 7.36 × 10⁻¹⁰). Moreover, there was an antagonistic interaction between hypomethylation of cg11676291_MORN1 and age (HR_interaction = 0.284; 95% CI, 0.135–0.597; p = 9.04 × 10⁻⁰⁴). The prognosis of OSCC patients was well discriminated by the prognostic score incorporating cg11676291_MORN1–age interaction (HR_{high vs. low} = 3.66, 95% CI: 2.40–5.60, p = 1.93 × 10⁻⁰⁹). By adding 24 significant gene–age interactions using a looser criterion, we significantly improved the area under the receiver operating characteristic curve (AUC) of the model at 3- and 5-year prognostic prediction (AUC_3-year = 0.80, AUC_5-year = 0.79, C-index = 0.75). Our study identified a significant interaction between cg11676291_MORN1 and age on OSCC survival, providing a potential therapeutic target for OSCC patients.

Knockdown of circMYOF inhibits cell growth, metastasis, and glycolysis through miR-145-5p/OTX1 regulatory axis in laryngeal squamous cell carcinoma

New evidence suggests that abnormal expression of circular RNA (circRNA) is associated with the development of human cancers. This study aims to reveal circMYOF roles in the malignant phenotype of laryngeal squamous cell carcinoma (LSCC). The expression of circMYOF, microRNA (miR)-145-5p, and orthodenticle homeobox 1 (OTX1) was detected by quantitative real-time PCR. Cell proliferation, migration, invasion, and apoptosis were determined using colony formation assay and EdU assay, wound healing assay, transwell assay, and flow cytometry, respectively. Protein expression was examined by western blot analysis. Cell glycolysis was assessed by detecting glucose consumption and lactate production. Mice xenograft models were constructed to evaluate the regulation of circMYOF on LSCC tumorigenesis. The regulatory relationships among circMYOF, miR-145-5p, and OTX1 were identified using dual-luciferase reporter assay and RIP assay. Serum exosomes were isolated to confirm the existence of circMYOF in LSCC patients. CircMYOF was upregulated in LSCC tissues and cells, and its knockdown suppressed LSCC cell growth, metastasis, and glycolysis, as well as inhibited LSCC tumor growth. MiR-145-5p had decreased expression in LSCC, and it could be sponged by circMYOF. The inhibition effect of circMYOF lentivirus short hairpin RNA (sh-circMYOF) on LSCC progression was restored by the inhibitor of miR-145-5p (in-miR-145-5p). Also, OTX1 was targeted by miR-145-5p and was positively regulated by circMYOF. MiR-145-5p could repress LSCC progression, and OTX1 overexpression also eliminated this effect. In addition, we found that circMYOF was significantly overexpressed in the serum exosomes of LSCC patients. Our data revealed that circMYOF contributed to LSCC progression by promoting cell growth, metastasis, and glycolysis through miR-145-5p/OTX1 axis.

FAM3B Serves as a Biomarker for the Development and Malignancy of Oral Lichen Planus

PURPOSE

Oral lichen planus (OLP) is a potentially malignant condition with unclear etiology. This study aimed to identify potential biomarkers and mechanisms for OLP progression through bioinformatics analyses.

METHODS

Gene Expression Omnibus (GEO) datasets were screened to identify differentially expressed genes (DEGs) between OLP patients and healthy individuals. The functions and enriched pathways of the DEGs were identified. Sequencing dataset GSE70665 was then used to analyze the role of DEGs in the development of OLP to oral squamous cell carcinoma (OSCC). Oncomine and The Cancer Genome Atlas (TCGA) databases were utilized to evaluate clinicopathological characters of OSCC. Univariate and multivariate Cox regression models were used to identify independent prognostic factors.

RESULTS

A total of 24 DEGs were identified between OLP and normal samples. FAM3B was under-expressed in OLP compared with normal samples and was further significantly downregulated in OSCC compared with OLP. Under-expression of FAM3B was significantly correlated with tumor stage and disease-specific survival (DSS), progression-free interval (PFI) and overall survival (OS) of OSCC patients. With univariate and multivariate Cox regression analysis, FAM3B was an independent prognostic factor.

CONCLUSION

Under-expression of FAM3B was associated with the development and malignancy of OLP. FAM3B may serve as a potential prognostic biomarker for OLP.

Artificial Neural Network Analysis of Gene Expression Data Predicted Non-Hodgkin Lymphoma Subtypes with High Accuracy

Predictive analytics using artificial intelligence is a useful tool in cancer research. A multilayer perceptron neural network used gene expression data to predict the lymphoma subtypes of 290 cases of non-Hodgkin lymphoma (GSE132929). The input layer included both the whole array of 20,863 genes and a cancer transcriptome panel of 1769 genes. The output layer was lymphoma subtypes, including follicular lymphoma, mantle cell lymphoma, diffuse large B-cell lymphoma, Burkitt lymphoma, and marginal zone lymphoma. The neural networks successfully classified the cases consistent with the lymphoma subtypes, with an area under the curve (AUC) that ranged from 0.87 to 0.99. The most relevant predictive genes were LCE2B, KNG1, IGHV7_81, TG, C6, FGB, ZNF750, CTSV, INGX, and COL4A6 for the whole set; and ARG1, MAGEA3, AKT2, IL1B, S100A7A, CLEC5A, WIF1, TREM1, DEFB1, and GAGE1 for the cancer panel. The characteristic predictive genes for each lymphoma subtypes were also identified with high accuracy (AUC = 0.95, incorrect predictions = 6.2%). Finally, the topmost relevant 30 genes of the whole set, which belonged to apoptosis, cell proliferation, metabolism, and antigen presentation pathways, not only predicted the lymphoma subtypes but also the overall survival of diffuse large B-cell lymphoma (series GSE10846, n = 414 cases), and most relevant cancer subtypes of The Cancer Genome Atlas (TCGA) consortium including carcinomas of breast, colorectal, lung, prostate, and gastric, melanoma, etc. (7441 cases). In conclusion, neural networks predicted the non-Hodgkin lymphoma subtypes with high accuracy, and the highlighted genes also predicted the survival of a pan-cancer series.