PRKCSH serves as a potential immunological and prognostic biomarker in pan-cancer

Glycosylation in cancer as a source of biomarkers

INTRODUCTION

Glycosylation, the process of glycan synthesis and attachment to target molecules, is a crucial and common post-translational modification (PTM) in mammalian cells. It affects the protein's hydrophilicity, charge, solubility, structure, localization, function, and protection from proteolysis. Aberrant glycosylation in proteins can reveal new detection and therapeutic Glyco-biomarkers, which help to improve accurate early diagnosis and personalized treatment. This review underscores the pivotal role of glycans and glycoproteins as a source of biomarkers in human diseases, particularly cancer.

AREAS COVERED

This review delves into the implications of glycosylation, shedding light on its intricate roles in cancer-related cellular processes influencing biomarkers. It is underpinned by a thorough examination of literature up to June 2024 in PubMed, Scopus, and Google Scholar; concentrating on the terms: (Glycosylation[Title/Abstract]) OR (Glycan[Title/Abstract]) OR (glycoproteomics[Title/Abstract]) OR (Proteoglycans[Title/Abstract]) OR (Glycomarkers[Title/Abstract]) AND (Cancer[Title/Abstract]) AND ((Diagno*[Title/Abstract]) OR (Progno*[Title/Abstract])).

EXPERT OPINION

Glyco-biomarkers enhance early cancer detection, allow early intervention, and improve patient prognoses. However, the abundance and complex dynamic glycan structure may make their scientific and clinical application difficult. This exploration of glycosylation signatures in cancer biomarkers can provide a detailed view of cancer etiology and instill hope in the potential of glycosylation to revolutionize cancer research.

A-to-I Editing Is Subtype-Specific in Non-Hodgkin Lymphomas

Cancer is a complex and heterogeneous disease, in which a number of genetic and epigenetic changes occur in tumor onset and progression. Recent studies indicate that changes at the RNA level are also involved in tumorigenesis, such as adenosine-to-inosine (A-to-I) RNA editing. Here, we systematically investigate transcriptome-wide A-to-I editing events in a large number of samples from Non-Hodgkin lymphomas (NHLs). Using a computational pipeline that determines significant differences in editing level between NHL and normal samples at known A-to-I editing sites, we identify a number of differentially edited editing sites between NHL subtypes and normal samples. Most of the differentially edited sites are located in non-coding regions, and many such sites show a strong correlation between gene expression level and editing efficiency, indicating that RNA editing might have direct consequences for the cancer cell's aberrant gene regulation status in these cases. Moreover, we establish a strong link between RNA editing and NHL by demonstrating that NHL and normal samples and even NHL subtypes can be distinguished based on genome-wide RNA editing profiles alone. Our study establishes a strong link between RNA editing, cancer and aberrant gene regulation in NHL.

Identification and validation of a novel risk model based on cuproptosis‑associated m6A for head and neck squamous cell carcinoma

BACKGROUND

Head and neck squamous cell carcinoma (HNSCC) is a prevalent cancer with a poor survival rate due to anatomical limitations of the head and a lack of reliable biomarkers. Cuproptosis represents a novel cellular regulated death pathway, and N6-methyladenosine (m6A) is the most common internal RNA modification in mRNA. They are intricately connected to tumor formation, progression, and prognosis. This study aimed to construct a risk model for HNSCC using a set of mRNAs associated with m6A regulators and cuproptosis genes (mcrmRNA).

METHODS

RNA-seq and clinical data of HNSCC patients from The Cancer Genome Atlas (TCGA) database were analyzed to develop a risk model through the least absolute shrinkage and selection operator (LASSO) analysis. Survival analysis and receiver operating characteristic (ROC) analysis were performed for the high- and low-risk groups. Additionally, the model was validated using the GSE41613 dataset from the Gene Expression Omnibus (GEO) database. GSEA and CIBERSORT were applied to investigate the immune microenvironment of HNSCC.

RESULTS

A risk model consisting of 32 mcrmRNA was developed using the LASSO analysis. The risk score of patients was confirmed to be an independent prognostic indicator by multivariate Cox analysis. The high-risk group exhibited a higher tumor mutation burden. Additionally, CIBERSORT analysis indicated varying levels of immune cell infiltration between the two groups. Significant disparities in drug sensitivity to common medications were also observed. Enrichment analysis further unveiled significant differences in metabolic pathways and RNA processing between the two groups.

CONCLUSIONS

Our risk model can predict outcomes for HNSCC patients and offers valuable insights for personalized therapeutic approaches.

Navigating PRKCSH's impact on cancer: from N-linked glycosylation to death pathway and anti-tumor immunity

PRKCSH, also known as Glucosidase II beta subunit (GluIIβ), is a crucial component of the endoplasmic reticulum (ER) quality control system for N-linked glycosylation, essential for identifying and eliminating misfolded proteins. Glucosidase II consists of the catalytic alpha subunit (GluIIα) and the regulatory beta subunit (GluIIβ), ensuring proper protein folding and release from the ER. The induction of PRKCSH in cancer and its interaction with various cellular components suggest broader roles beyond its previously known functions. Mutations in the PRKCSH gene are linked to autosomal dominant polycystic liver disease (ADPLD). Alternative splicing generates distinct PRKCSH isoforms, which can influence processes like epithelial-mesenchymal transition (EMT) and the proliferation of lung cancer cells. PRKCSH's involvement in cancer is multifaceted, impacting cell growth, metastasis, and response to growth factors. Additionally, PRKCSH orchestrates cell death programs, affecting both autophagy and apoptosis. Its role in facilitating N-linked glycoprotein release from the ER is hypothesized to assist cancer cells in managing increased demand and ER stress. Moreover, PRKCSH modulates anti-tumor immunity, with its suppression augmenting NK cell and T cell activity, promising enhanced cancer therapy. PRKCSH's diverse functions, including regulation of IGF1R and IRE1α, implicate it as a therapeutic target and biomarker in cancer immunotherapy. However, targeting its glucosidase II activity alone may not fully counteract its effects, suggesting broader mechanisms in cancer development. Further investigations are needed to elucidate PRKCSH's precise role and validate its therapeutic potential in cancer treatment.