Evaluation of GALNT16 polymorphisms to breast cancer risk in Chinese population

Identification and validation of a metabolism-related gene signature for predicting the prognosis of paediatric medulloblastoma

Medulloblastoma (MB) is a malignant brain tumour that is highly common in children and has a tendency to spread to the brain and spinal cord. MB is thought to be a metabolically driven brain tumour. Understanding tumour cell metabolic patterns and characteristics can provide a promising foundation for understanding MB pathogenesis and developing treatments. Here, by analysing RNA-seq data of MB samples from the Gene Expression Omnibus (GEO) database, 12 differentially expressed metabolic-related genes (DE-MRGs) were chosen for the construction of a predictive risk score model for MB. This model demonstrated outstanding accuracy in predicting the outcomes of MB patients and served as a standalone predictor. An evaluation of functional enrichment revealed that the risk score showed enrichment in pathways related to cancer promotion and the immune response. In addition, a high risk score was an independent poor prognostic factor for MB in patients with different ages, sexes, metastasis stages and subgroups (SHH and Group 4). Consistently, the metabolic enzyme ornithine decarboxylase (ODC1) was upregulated in MB patients with poor survival time. Inhibition of ODC1 in primary and metastatic MB cell lines decreased cell proliferation, migration and invasion but increased immune infiltration. This study could aid in identifying metabolic targets for MB as well as optimizing risk stratification systems and individual treatment plans for MB patients via the use of a metabolism-related gene prognostic risk score signature.

Development and validation of glycosyltransferase related-gene for the diagnosis and prognosis of head and neck squamous cell carcinoma

BACKGROUND

Head and neck squamous cell carcinoma (HNSCC) is a highly heterogeneous cancer characterized by difficulties in early diagnosis and outcome prediction. Aberrant glycosylated structures produced by the aberrant expression of glycosyltransferases are prevalent in HNSCC. In this study, we aim to construct glycosyltransferase-related gene signatures with diagnostic and prognostic value to better stratify patients with HNSCC and improve their diagnosis and prognosis.

METHODS

Bioinformatic tools were used to process data of patients with HNSCC from The Cancer Genome Atlas (TCGA) database. The prognostic model was formatted using univariate and multivariate Cox regression methods, while the diagnostic signature was constructed using support vector machine (SVM) and LASSO analysis. The results were verified using the Gene Expression Omnibus (GEO) cohort. The tumor microenvironment and benefits of immune checkpoint inhibitor (ICI) therapy in subgroups defined by glycosyltransferase-related genes were analyzed. Molecular biology experiments, including western blotting, cell counting kit (CCK)-8, colony formation, wound healing, and Transwell assays, were conducted to confirm the oncogenic function of beta-1,4-galactosyltransferase 3 (B4GALT3) in HNSCC.

RESULTS

We established a five-gene prognostic signature and a 15-gene diagnostic model. Based on the median risk score, patients with low risk had longer overall survival than those in the high-risk group, which was consistent with the results of the GEO cohort. The concrete results suggested that high-risk samples were related to a high tumor protein (TP)53 mutation rate, high infiltration of resting memory cluster of differentiation (CD)4 T cells, resting natural killer (NK) cells, and M0 macrophages, and benefited from ICI therapy. In contrast, the low-risk subgroup was associated with a low TP53 mutation rate; and high infiltration of naive B cells, plasma cells, CD8 T cells, and resting mast cells; and benefited less from ICI therapy. In addition, the diagnostic model had an area under curve (AUC) value of 0.997 and 0.978 in the training dataset and validation cohort, respectively, indicating the high diagnostic potential of the model. Ultimately, the depletion of B4GALT3 significantly hindered the proliferation, migration, and invasion of HNSCC cells.

CONCLUSIONS

We established two new biomarkers that could provide clinicians with diagnostic, prognostic, and treatment guidance for patients with HNSCC.

Discovery and characterization of tumor antigens in hepatocellular carcinoma for mRNA vaccine development

BACKGROUND

mRNA vaccines are emerging as new targets for cancer immunotherapy. However, the potential tumor antigens for mRNA vaccine design in hepatocellular carcinoma (HCC) remain to be elucidated.

METHODS

Genetic and RNA-Seq data were obtained from TCGA and ICGC. Tumor-specific antigens (TSAs) were identified by differential expression, mutation status, HLA binding, antigen-presenting cell (APC) correlation, immune checkpoint (ICP) relevance and prognosis. Consensus clustering was used for patient classification. The molecular and immune status of TSAs and clustered patients, including prognostic ability, tumor microenvironment, tumor-related signature and tumor immune dysfunction and exclusion (TIDE), were further characterized.

RESULTS

Five dysregulated and mutated TSAs were identified in HCC (TSA5): FXYD6, JAM2, GALNT16, C7, and CCDC146. Seven immune gene modules and five immune subtypes (IS1-IS5) of HCC were identified. The immune subtypes and TSA5-related modules showed distinct molecular, cellular and clinical characteristics. According to our study, IS1 patients may be suitable for vaccination.

Integrative identification of immune-related key genes in atrial fibrillation using weighted gene coexpression network analysis and machine learning

Background

The immune system significantly participates in the pathologic process of atrial fibrillation (AF). However, the molecular mechanisms underlying this participation are not completely explained. The current research aimed to identify critical genes and immune cells that participate in the pathologic process of AF.

Methods

CIBERSORT was utilized to reveal the immune cell infiltration pattern in AF patients. Meanwhile, weighted gene coexpression network analysis (WGCNA) was utilized to identify meaningful modules that were significantly correlated with AF. The characteristic genes correlated with AF were identified by the least absolute shrinkage and selection operator (LASSO) logistic regression and support vector machine recursive feature elimination (SVM-RFE) algorithm.

Results

In comparison to sinus rhythm (SR) individuals, we observed that fewer activated mast cells and regulatory T cells (Tregs), as well as more gamma delta T cells, resting mast cells, and M2 macrophages, were infiltrated in AF patients. Three significant modules (pink, red, and magenta) were identified to be significantly associated with AF. Gene enrichment analysis showed that all 717 genes were associated with immunity- or inflammation-related pathways and biological processes. Four hub genes (GALNT16, HTR2B, BEX2, and RAB8A) were revealed to be significantly correlated with AF by the SVM-RFE algorithm and LASSO logistic regression. qRT–PCR results suggested that compared to the SR subjects, AF patients exhibited significantly reduced BEX2 and GALNT16 expression, as well as dramatically elevated HTR2B expression. The AUC measurement showed that the diagnostic efficiency of BEX2, HTR2B, and GALNT16 in the training set was 0.836, 0.883, and 0.893, respectively, and 0.858, 0.861, and 0.915, respectively, in the validation set.

Conclusions

Three novel genes, BEX2, HTR2B, and GALNT16, were identified by WGCNA combined with machine learning, which provides potential new therapeutic targets for the early diagnosis and prevention of AF.

Seven-gene signature on tumor microenvironment for predicting the prognosis of patients with pancreatic cancer

Background

The aim of the present study was to construct a novel gene signature on the tumor microenvironment (TME) to predict the prognosis of patients with pancreatic ductal adenocarcinoma (PDAC).

Methods

We downloaded gene expression profiles and clinical information of PDAC from The Cancer Genome Atlas (TCGA) datasets, as well as Gene Expression Omnibus (GEO) datasets (GSE78229, GSE62452, and GSE28735). Differentially expressed genes were generated by comparing high versus low score groups of immune/stromal subgroups based on the Estimation of STromal and Immune cells in MAlignant Tumor tissues using Expression data algorithm. Subsequently, a prognostic risk score model was constructed and validated through univariate and multivariate Cox regression analyses. Finally, functional enrichment analysis and protein-protein interactions were performed to predict the functional implication of the prognostic model.

Results

We picked out 1,797 upregulated genes in immune groups and stromal groups. Through further analysis, we constructed a 7-gene signature on the TME. The risk score from the model effectively differentiated patients into high-risk and low-risk groups with different overall survival and was validated by GEO datasets. A functional analysis suggested that 7 selected genes and their co-expressed genes were mainly enriched in immune response, extracellular structure organization, and cell adhesion molecule binding.

Conclusions

Our results showed that the 7-gene model on the TME can be used to assess the prognosis of patients with PDAC.

Development and validation of a custom panel including 183 Y-SNPs for Chinese Y-chromosomal haplogroups dissection using a MALDI-TOF MS system

Y-chromosome SNP haplogroups exhibit geographic structuring in many populations around the world. Therefore, Y-chromosome haplogroups have been widely used to infer paternal biogeographical ancestry and high-resolution paternal lineage classification. In the present study, we designed a customized panel containing 183 Y-SNPs based on previous studies and evaluated the genotyping performance and repeatability, concordance, sensitivity, and ability of analysing case-type samples using a MALDI-TOF MS platform. The average call rate for duplicate typing of any one SNP in the panel was 97.0%. In the concordance and accuracy study, the results of haplogroup designation obtained from MALDI-TOF MS platform were fully consistent with those obtained from the next-generation sequencing (NGS) platform. The optimal amount of template DNA in the PCR seemed to be 10 ng. However, if less DNA (≥156.25 pg) was available, it was still possible to obtain meaningful haplogroup information. For the application part, this panel could be applied for the detection of blood, semen, and buccal swabs samples. Particularly, blood stain on FTA card samples could be dissected by direct PCR amplification on the MALDI-TOF MS platform. Besides, 371 unrelated male individuals from four Chinese ethnic groups (Han, Hui, Mongolian, and Kazak) were detected using this panel. Total 78 terminal haplogroups were found and the haplogroup diversity was 0.933576. The results demonstrate that this panel could be an accurate, fast, and cost-effective method for database construction where the amount of sample material is less of a concern and when the cost of the assay is taken into consideration.

Evaluation of GALNT16 polymorphisms to breast cancer risk in Chinese population

BACKGROUND

Polypeptide N-acetylgalactosaminyltransferase 16 (GALNT16) is an N-acetylgalactosaminyltransferase gene that alters protein O-glycosylation, which plays a role in tumor development. This study aims to explore the association of eight GALNT16 polymorphisms with susceptibility to breast cancer (BC).

METHODS

This case-control study included 563 BC patients and 552 age-matched healthy controls from the Chinese Han population. The genotypes of GALNT16 polymorphisms were detected using the Agena MassARRAY. The relationship between GALNT16 polymorphisms and BC risk was evaluated using a chi-squared test with an odds ratio (OR) and 95% confidence intervals (CI) under five genetic models.

RESULTS

We observed that rs2105269 and rs72625676 were associated with higher BC risk in younger patients with age ≤51 (rs2105269, codominant: p = .006; recessive: p = .005 additive: p = .018; and allele: p = .012; rs72625676, codominant: p = .038; recessive: p = .037). For rs1275678 polymorphism, there was a significantly decreased risk of BC among elder patients (codominant: p = .017; dominant: p = .019; additive: p = .030; and allele: p = .029). Further analysis by clinical characteristics showed rs2105269 was associated with tumor size and lymph node metastasis.

CONCLUSION

Our study suggests that GALNT16 polymorphisms are associated with BC susceptibility in Chinese population.