Comprehensive Analysis of the Potential Prognostic Value of 11 Glycosylation-Related Genes in Head and Neck Squamous Cell Carcinoma and Their Correlation with PD-L1 Expression and Immune Infiltration

Identification of stemness-related glycosylation changes in head and neck squamous cell carcinoma

BACKGROUND

Altered glycosylation is a hallmark of cancer associated with therapy resistance and tumor behavior. In this study, we investigated the glycosylation profile of stemness-related proteins OCT4, CIP2A, MET, and LIMA1 in HNSCC tumors.

METHODS

Tumor, adjacent normal tissue, and blood samples of 25 patients were collected together with clinical details. After tissue processing, lectin-based glycovariant screens were performed.

RESULTS

Strong correlation between glycosylation profiles of all four stemness-related proteins was observed in tumor tissue, whereas glycosylation in tumor tissue, adjacent normal tissue, and serum was differential.

CONCLUSIONS

A mannose- and galactose-rich glycosylation niche associated with stemness-related proteins was identified.

Identification of prognostic models for glycosylation-related subtypes and tumor microenvironment infiltration characteristics in clear cell renal cell cancer

Background

One of the most fatal forms of cancer of the urinary system, renal cell carcinoma (RCC), significantly negatively impacts human health. Recent research reveals that abnormal glycosylation contributes to the growth and spread of tumors. However, there is no information on the function of genes related to glycosylation in RCC.

Methods

In this study, we created a technique that can be used to guide the choice of immunotherapy and chemotherapy regimens for RCC patients while predicting their survival prognosis. The Cancer Genome Atlas (TCGA) provided us with patient information, while the GeneCards database allowed us to collect genes involved in glycosylation. GSE29609 was used as external validation to assess the accuracy of prognostic models. The "ConsensusClusterPlus" program created molecular subtypes based on genes relevant to glycosylation discovered using differential expression analysis and univariate Cox analysis. We examined immune cell infiltration as measured by estimate, CIBERSORT, TIMER, and ssGSEA algorithms, Tumor Immune Dysfunction and Exclusion (TIDE) and exclusion of tumour stemness indices (TSIs) based on glycosylation-related molecular subtypes and risk profiles. Stratification, somatic mutation, nomogram creation, and chemotherapy response prediction were carried out based on risk factors.

Results

We built and verified 16 gene signatures associated with the prognosis of ccRCC patients, which are independent prognostic variables, and identified glycosylation-related genes by bioinformatics research. Cluster 2 is associated with lower human leukocyte antigen expression, worse overall survival, higher immunological checkpoints, and higher immune escape scores. In addition, cluster 2 had significantly better angiogenic activity, mesenchymal EMT, and stem ability scores. Higher immune checkpoint genes and human leukocyte antigens are associated with lower overall survival and a higher risk score. Higher estimated and immune scores, lesser tumor purity, lower mesenchymal EMT, and higher stem scores were all characteristics of the high-risk group. High amounts of tumor-infiltrating lymphocytes, a high mutation load, and a high copy number alteration frequency were present in the high-risk group.Discussion.According to our research, the 16-gene prognostic signature may be helpful in predicting prognosis and developing individualized treatments for patients with renal clear cell carcinoma, which may result in new personalized management options for these patients.

Molecular basis, potential biomarkers, and future prospects of OSCC and PD-1/PD-L1 related immunotherapy methods

Oral squamous cell carcinoma (OSCC) affects a large number of individuals worldwide. Despite advancements in surgery, radiation, and chemotherapy, satisfactory outcomes have not been achieved. In recent years, the success of drugs targeting programmed cell death 1 (PD-1) and programmed cell death ligand 1 (PD-L1) has led to breakthroughs in cancer treatment, but systematic summaries on their effectiveness against OSCC are lacking. This article reviews the latest research on the PD-1/PD-L1 pathway and the potential of combination therapy based on this pathway in OSCC. Further, it explores the mechanisms involved in the interaction of this pathway with exosomes and protein-protein interactions, and concludes with potential future OSCC therapeutic strategies.

A glycosylation-related signature predicts survival in pancreatic cancer

BACKGROUND

Tumor initiation and progression are closely associated with glycosylation. However, glycosylated molecules have not been the subject of extensive studies as prognostic markers for pancreatic cancer. The objectives of this study were to identify glycosylation-related genes in pancreatic cancer and use them to construct reliable prognostic models.

MATERIALS AND METHODS

The Cancer Genome Atlas and Gene Expression Omnibus databases were used to assess the differential expression of glycosylation-related genes; four clusters were identified based on consistent clustering analysis. Kaplan-Meier analyses identified three glycosylation-related genes associated with overall survival. LASSO analysis was then performed on The Cancer Genome Atlas and International Cancer Genome Consortium databases to identify glycosylation-related signatures. We identified 12 GRGs differently expressed in pancreatic cancer and selected three genes (SEL1L, TUBA1C, and SDC1) to build a prognostic model. Thereafter, patients were divided into high and low-risk groups. Eventually, we performed Quantitative real-time PCR (qRT-PCR) to validate the signature.

RESULTS

Clinical outcomes were significantly poorer in the high-risk group than in the low-risk group. There were also significant correlations between the high-risk group and several risk factors, including no-smoking history, drinking history, radiotherapy history, and lower tumor grade. Furthermore, the high-risk group had a higher proportion of immune cells. Eventually, three glycosylation-related genes were validated in human PC cell lines.

CONCLUSION

This study identified the glycosylation-related signature for pancreatic cancer. It is an effective predictor of survival and can guide treatment decisions.

Glycosylation-related molecular subtypes and risk score of hepatocellular carcinoma: Novel insights to clinical decision-making

BACKGROUND

Hepatocellular carcinoma (HCC) is the fifth most common cancer and the third leading cause of cancer deaths worldwide, seriously affecting human community health and care. Emerging evidence has shown that aberrant glycosylation is associated with tumor progression and metastasis. However, the role of glycosylation-related genes in HCC has notbeen reported.

METHODS

Weighted gene coexpression network analysis and non-negative matrix factorization analysis were applied to identify functional modules and molecularm subtypes in HCC. The least absolute shrinkage and selection operator Cox regression was used to construct the glycosylation-related signature. The independent prognostic value of the risk model was confirmed and validated by systematic techniques, including principal component analysis, T-distributed random neighbor embedding analysis, Kaplan-Meier survival analysis, the ROC curve, multivariate Cox regression, the nomogram, and the calibration curve. The single-sample gene set enrichment analysis, gene set variation analysis, Gene Ontology, and Kyoto Encyclopedia of Genes and Genomes analyses were evaluated by the immune microenvironment and potential biological processes. The quantitative real-time polymerase chain reaction and immunohistochemistry analysis were used to verify the expression of five genes.

RESULTS

We identified the glycosylation-related genes with bioinformatics analysis to construct and validate a five-gene signature for the prognosis of HCC patients. Patients with HCC in the high-risk group had a worse prognosis. The risk score could be an independent factor and was associated with clinical features, such as the grade and stage. The nomogram exhibited an accurate score that included the risk score and clinical parameters. The infiltration levels of antitumor cells were upregulated in the low-risk group, including B_cells, Mast_cells, neutrophils, NK_cells, and T_helper_cells. Moreover, glycosylation was more sensitive to immunotherapy, and may play a critical role in the metabolic processes of HCC, such as bile acid metabolism and fatty acid metabolism. In addition, the five-gene messenger RNA (mRNA) and protein expression were overexpressed in HCC cells and tissues.

CONCLUSIONS

The glycosylation-related signature is effective for prognostic recognition, immune efficacy evaluation, and substance metabolism in HCC, providing a novel insight for therapeutic target prediction and clinical decision-making.