High PYGL Expression Predicts Poor Prognosis in Human Gliomas

Insights of immune cell heterogeneity, tumor-initiated subtype transformation, drug resistance, treatment and detecting technologies in glioma microenvironment

BACKGROUND

With the gradual understanding of glioma development and the immune microenvironment, many immune cells have been discovered. Despite the growing comprehension of immune cell functions and the clinical application of immunotherapy, the precise roles and characteristics of immune cell subtypes, how glioma induces subtype transformation of immune cells and its impact on glioma progression have yet to be understood.

AIM OF THE REVIEW

In this review, we comprehensively center on the four major immune cells within the glioma microenvironment, particularly neutrophils, macrophages, lymphocytes, myeloid-derived suppressor cells (MDSCs), and other significant immune cells. We discuss (1) immune cell subtype markers, (2) glioma-induced immune cell subtype transformation, (3) the mechanisms of each subtype influencing chemotherapy resistance, (4) therapies targeting immune cells, and (5) immune cell-associated single-cell sequencing. Eventually, we identified the characteristics of immune cell subtypes in glioma, comprehensively summarized the exact mechanism of glioma-induced immune cell subtype transformation, and concluded the progress of single-cell sequencing in exploring immune cell subtypes in glioma.

KEY SCIENTIFIC CONCEPTS OF REVIEW

In conclusion, we have analyzed the mechanism of chemotherapy resistance detailly, and have discovered prospective immunotherapy targets, excavating the potential of novel immunotherapies approach that synergistically combines radiotherapy, chemotherapy, and surgery, thereby paving the way for improved immunotherapeutic strategies against glioma and enhanced patient outcomes.

The therapeutic effect of mRNA vaccines in glioma: a comprehensive review

INTRODUCTION

Glioma is the most common primary brain tumor, with glioblastoma being the most lethal type due to its heterogeneous and invasive nature of the cancer. Current therapies have low curative success and are limited to surgery, radiotherapy, and chemotherapy. More than 50% of patients become resistant to chemotherapy, and tumor recurrence occurs in most patients following an initial course of therapy. Therefore, developing novel, effective strategies for glioma treatment is essential. Cancer vaccines are novel therapies that demonstrate advantages over conventional methods and, therefore, may be promising options for treating glioma.

AREAS COVERED

This article provided a critical review of pre-clinical and clinical studies that explored appropriate tumor antigen candidates for developing mRNA vaccines and discussed their clinical application in glioma patients. Medline database, PubMed, and ClinicalTrials.gov were searched for glioma vaccine studies published before 2025 using related keywords.

EXPERT OPINION

mRNA vaccines are promising strategies for treating glioma because they are efficient, cost-beneficial, and have lower side effects than other types such as peptide or DNA-based vaccines.

Amino acid metabolism in glioblastoma pathogenesis, immune evasion, and treatment resistance

Glioblastoma (GBM) ranks among the most lethal primary tumors of the central nervous system. This is partly due to its complex intracellular metabolism and interactions with the surrounding tumor microenvironment (TME). Compelling evidence represents that altered amino acids (AAs) metabolism plays a crucial role in both areas. The role of AAs and their metabolites in glioma biology is an emerging topic. Therefore, this review was conducted to summarize the current knowledge about the molecular mechanisms by which AAs participate in the GBM pathogenesis. AAs can directly influence tumor progression by affecting tumor cell metabolism or indirectly by releasing bioactive agents through particular metabolic pathways. This review begins by examining the metabolic pathways of essential AAs, such as tryptophan, tyrosine, and phenylalanine, which contribute to synthesizing critical neurotransmitters and shape tumor metabolism signatures. We explore how these pathways impact tumor growth and immune modulation, focusing on how AAs and their metabolites can promote malignant properties in GBM cells. AAs also play a pivotal role in reprogramming the TME, contributing to immune evasion and resistance to therapy. The review further discusses how tumor metabolism signatures, influenced by AA metabolism, can enhance the immunosuppressive microenvironment, providing new avenues for targeted immunotherapies. Finally, we outline potential therapeutic strategies to modulate AA metabolism and emphasize critical opportunities for future research to improve GBM management.

PYGL regulation of glycolysis and apoptosis in glioma cells under hypoxic conditions via HIF1α-dependent mechanisms

Background

Gliomas are highly aggressive brain tumors with complex metabolic and molecular alterations. The role of glycolysis in glioma progression and its regulation by hypoxia remain poorly understood. This study investigated the function of glycogen phosphorylase L (PYGL) in glioma and its interaction with glycolytic pathways under hypoxic conditions.

Methods

Differential expression analysis was conducted using The Cancer Genome Atlas (TCGA) glioma and GSE67089 datasets, revealing significant changes in the expression of genes. A prognostic risk model incorporating PYGL was built by univariate and multivariate Cox regression analyses. The impacts of PYGL on glioma cell proliferation, glycolysis, apoptosis, and metabolic activities were evaluated by in vitro assays. Additionally, the influences of hypoxia and hypoxia-inducible factor 1-alpha (HIF1α) on PYGL expression were evaluated.

Results

Our prognostic prediction model showed a C-index of 0.76 [95% confidence interval (CI): 0.70-0.82], indicating a good predictive accuracy of the model. In addition, genetic predictors included in the nomogram included PYGL, HIF1α, and other genes associated with the glycolytic pathway. Differential expression analysis identified PYGL as a key gene associated with glioma survival. PYGL expression was significantly upregulated in glioma cells. PYGL knockdown inhibited cell invasion, proliferation, migration, and colony formation and enhanced apoptosis via modulation of Bcl-2, caspase-3, and Bax. Glycolysis was impaired in PYGL-knockdown cells, as indicated by increased glycogen levels and a reduced extracellular acidification rate (ECAR), adenosine triphosphate (ATP) levels, lactate levels, and PKM2 and LDHA expression. PYGL overexpression promoted glycolysis and cell viability, which was counteracted by 2-deoxy-D-glucose (2-DG). Hypoxia-induced PYGL expression was regulated by HIF1α, underscoring the interplay between the hypoxia and glycolysis pathways.

Conclusions

PYGL is a crucial regulator of glycolysis in gliomas and contributes to tumor progression under hypoxic conditions. Targeting PYGL and its associated metabolic pathways may offer new therapeutic strategies for glioma treatment.

Evidence for the Quercetin Binding Site of Glycogen Phosphorylase as a Target for Liver-Isoform-Selective Inhibitors against Glioblastoma: Investigation of Flavanols Epigallocatechin Gallate and Epigallocatechin

Glycogen phosphorylase (GP) is the rate-determining enzyme in glycogenolysis, and its druggability has been extensively studied over the years for the development of therapeutics against type 2 diabetes (T2D) and, more recently, cancer. However, the conservation of binding sites between the liver and muscle isoforms makes the inhibitor selectivity challenging. Using a combination of kinetic, crystallographic, modeling, and cellular studies, we have probed the binding of dietary flavonoids epigallocatechin gallate (EGCG) and epigallocatechin (EGC) to GP isoforms. The structures of rmGPb-EGCG and rmGPb-EGC complexes were determined by X-ray crystallography, showing binding at the quercetin binding site (QBS) in agreement with kinetic studies that revealed both compounds as noncompetitive inhibitors of GP, with EGCG also causing a significant reduction in cell viability and migration of U87-MG glioblastoma cells. Interestingly, EGCG exhibits different binding modes to GP isoforms, revealing QBS as a promising site for GP targeting, offering new opportunities for the design of liver-selective GP inhibitors.

Glycogen myophosphorylase loss causes increased dependence on glucose in iPSC-derived retinal pigment epithelium

Loss of glycogen myophosphorylase (PYGM) expression results in an inability to break down muscle glycogen, leading to McArdle disease-an autosomal recessive metabolic disorder characterized by exercise intolerance and muscle cramps. While previously considered relatively benign, this condition has recently been associated with pattern dystrophy in the retina, accompanied by variable sight impairment, secondary to retinal pigment epithelial (RPE) cell involvement. However, the pathomechanism of this condition remains unclear. In this study, we generated a PYGM-null induced pluripotent stem cell line and differentiated it into mature RPE to examine structural and functional defects, along with metabolite release into apical and basal media. Mutant RPE exhibited normal photoreceptor outer segment phagocytosis but displayed elevated glycogen levels, reduced transepithelial resistance, and increased cytokine secretion across the epithelial layer compared to isogenic WT controls. Additionally, decreased expression of the visual cycle component, RDH11, encoding 11-cis-retinol dehydrogenase, was observed in PYGM-null RPE. While glycolytic flux and oxidative phosphorylation levels in PYGM-null RPE were near normal, the basal oxygen consumption rate was increased. Oxygen consumption rate in response to physiological levels of lactate was significantly greater in WT than PYGM-null RPE. Inefficient lactate utilization by mutant RPE resulted in higher glucose dependence and increased glucose uptake from the apical medium in the presence of lactate, suggesting a reduced capacity to spare glucose for photoreceptor use. Metabolic tracing confirmed slower 13C-lactate utilization by PYGM-null RPE. These findings have key implications for retinal health since they likely underlie the vision impairment in individuals with McArdle disease.

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.

A glycosylation-related gene signature predicts prognosis, immune microenvironment infiltration, and drug sensitivity in glioma

Glioma represents the most common primary cancer of the central nervous system in adults. Glycosylation is a prevalent post-translational modification that occurs in eukaryotic cells, leading to a wide array of modifications on proteins. We obtained the clinical information, bulk RNA-seq data, and single-cell RNA sequencing (scRNA-seq) from The Cancer Genome Atlas (TCGA), Chinese Glioma Genome Atlas (CGGA), Gene Expression Omnibus (GEO), and Repository of Molecular Brain Neoplasia Data (Rembrandt) databases. RNA sequencing data for normal brain tissues were accessed from the Genotype-Tissue Expression (GTEx) database. Then, the glycosylation genes that were differentially expressed were identified and further subjected to variable selection using a least absolute shrinkage and selection operator (LASSO)-regularized Cox model. We further conducted enrichment analysis, qPCR, nomogram, and single-cell transcriptome to detect the glycosylation signature. Drug sensitivity analysis was also conducted. A five-gene glycosylation signature (CHPF2, PYGL, GALNT13, EXT2, and COLGALT2) classified patients into low- or high-risk groups. Survival analysis, qPCR, ROC curves, and stratified analysis revealed worse outcomes in the high-risk group. Furthermore, GSEA and immune infiltration analysis indicated that the glycosylation signature has the potential to predict the immune response in glioma. In addition, four drugs (crizotinib, lapatinib, nilotinib, and topotecan) showed different responses between the two risk groups. Glioma cells had been classified into seven lines based on single-cell expression profiles. The five-gene glycosylation signature can accurately predict the prognosis of glioma and may offer additional guidance for immunotherapy.

METTL3-mediated m6A methylation of PYGB facilitates pancreatic ductal adenocarcinoma progression through the activation of NF-κB signaling

Brain Type Glycogen Phosphorylase (PYGB) has been revealed to participate in the progression of multiple human cancers. Nevertheless, the clinical significance and biological function of PYGB in pancreatic ductal adenocarcinoma (PAAD) remains unclarified. This study first analyzed the expression pattern, diagnostic value, and prognostic significance of PYGB in PAAD using the TCGA database. Subsequently, western blot assessed the protein expression of genes in PAAD cells. The viability, apoptosis, migration, and invasion of PAAD cells were assessed by CCK-8, TUNEL, and Transwell assays. Finally, in vivo experiment evaluated the effect of PYGB on PAAD tumor growth and metastasis. Through our investigation, it was revealed that PYGB had extremely high expression in PAAD and predicted a worse prognosis in patients with PAAD. Besides, the aggressiveness of PAAD cells could be suppressed or enhanced by depleting or supplementing PYGB. In addition, we demonstrated that METTL3 enhanced the translation of PYGB mRNA in an m6A-YTHDF1-dependent manner. Moreover, PYGB was revealed to regulate the malignant behaviors of PAAD cells by the mediation of the NF-κB signaling. Finally, PYGB depletion suppressed the growth and distant metastasis of PAAD in vivo. To conclude, our results indicated that METTL3-mediated m6A modification of PYGB exerted the tumor-promotive effect on PAAD through NF-κB signaling, suggesting PYGB is a potential therapeutic target in PAAD.

Cellular hierarchy framework based on single-cell/multi-patient sample sequencing reveals metabolic biomarker PYGL as a therapeutic target for HNSCC

BACKGROUND

A growing body of research has revealed the connection of metabolism reprogramming and tumor progression, yet how metabolism reprogramming affects inter-patient heterogeneity and prognosis in head and neck squamous cell carcinoma (HNSCC) still requires further explorations.

METHODS

A cellular hierarchy framework based on metabolic properties discrepancy, METArisk, was introduced to re-analyze the cellular composition from bulk transcriptomes of 486 patients through deconvolution utilizing single-cell reference profiles from 25 primary and 8 metastatic HNSCC sample integration of previous studies. Machine learning methods were used to identify the correlations between metabolism-related biomarkers and prognosis. The functions of the genes screened out in tumor progression, metastasis and chemotherapy resistance were validated in vitro by cellular functional experiments and in vivo by xenograft tumor mouse model.

RESULTS

Incorporating the cellular hierarchy composition and clinical properties, the METArisk phenotype divided multi-patient cohort into two classes, wherein poor prognosis of METArisk-high subgroup was associated with a particular cluster of malignant cells with significant activity of metabolism reprogramming enriched in metastatic single-cell samples. Subsequent analysis targeted for phenotype differences between the METArisk subgroups identified PYGL as a key metabolism-related biomarker that enhances malignancy and chemotherapy resistance by GSH/ROS/p53 pathway, leading to poor prognosis of HNSCC.

CONCLUSION

PYGL was identified as a metabolism-related oncogenic biomarker that promotes HNSCC progression, metastasis and chemotherapy resistance though GSH/ROS/p53 pathway. Our study revealed the cellular hierarchy composition of HNSCC from the cell metabolism reprogramming perspective and may provide new inspirations and therapeutic targets for HNSCC in the future.

Identification of glycogen phosphorylase L as a potential target for lung cancer

Traditional Chinese medicine (TCM) has been widely used for cancer treatment. Identification of anti-cancer targets of TCM is the first and principal step in discovering molecular mechanisms of TCM as well as obtaining novel targets for cancer therapy. In this study, glycogen phosphorylase L (PYGL) was identified as one of the targeted proteins for several TCMs and was upregulated in various cancer types. The expression level of PYGL was positively correlated with the stage of lung cancer and the poor prognosis of patients. Meanwhile, knockdown of PYGL significantly inhibited proliferation and migration in lung cancer cells. In addition, PYGL was associated with spindle, kinetochore, and microtubule, the cellular components that are closely related to mitosis, in lung cancer. Moreover, PYGL was more susceptible to be upregulated by 144 mutated genes. Taken together, PYGL is a potential target for lung cancer treatment and its molecular mechanism probably influences the mitotic function of cells by regulating energy metabolism.

Differentially Expressed Genes and Molecular Susceptibility to Human Age-Related Diseases

Mainstream transcriptome profiling of susceptibility versus resistance to age-related diseases (ARDs) is focused on differentially expressed genes (DEGs) specific to gender, age, and pathogeneses. This approach fits in well with predictive, preventive, personalized, participatory medicine and helps understand how, why, when, and what ARDs one can develop depending on their genetic background. Within this mainstream paradigm, we wanted to find out whether the known ARD-linked DEGs available in PubMed can reveal a molecular marker that will serve the purpose in anyone's any tissue at any time. We sequenced the periaqueductal gray (PAG) transcriptome of tame versus aggressive rats, identified rat-behavior-related DEGs, and compared them with their known homologous animal ARD-linked DEGs. This analysis yielded statistically significant correlations between behavior-related and ARD-susceptibility-related fold changes (log₂ values) in the expression of these DEG homologs. We found principal components, PC1 and PC2, corresponding to the half-sum and the half-difference of these log₂ values, respectively. With the DEGs linked to ARD susceptibility and ARD resistance in humans used as controls, we verified these principal components. This yielded only one statistically significant common molecular marker for ARDs: an excess of Fcγ receptor IIb suppressing immune cell hyperactivation.

Identification and immunological characterization of endoplasmic reticulum stress-related molecular subtypes in bronchopulmonary dysplasia based on machine learning

Introduction: Bronchopulmonary dysplasia (BPD) is a life-threatening lung illness that affects premature infants and has a high incidence and mortality. Using interpretable machine learning, we aimed to investigate the involvement of endoplasmic reticulum (ER) stress-related genes (ERSGs) in BPD patients. Methods: We evaluated the expression profiles of endoplasmic reticulum stress-related genes and immune features in bronchopulmonary dysplasia using the GSE32472 dataset. The endoplasmic reticulum stress-related gene-based molecular clusters and associated immune cell infiltration were studied using 62 bronchopulmonary dysplasia samples. Cluster-specific differentially expressed genes (DEGs) were identified utilizing the WGCNA technique. The optimum machine model was applied after comparing its performance with that of the generalized linear model, the extreme Gradient Boosting, the support vector machine (SVM) model, and the random forest model. Validation of the prediction efficiency was done by the use of a calibration curve, nomogram, decision curve analysis, and an external data set. Results: The bronchopulmonary dysplasia samples were compared to the control samples, and the dysregulated endoplasmic reticulum stress-related genes and activated immunological responses were analyzed. In bronchopulmonary dysplasia, two distinct molecular clusters associated with endoplasmic reticulum stress were identified. The analysis of immune cell infiltration indicated a considerable difference in levels of immunity between the various clusters. As measured by residual and root mean square error, as well as the area under the curve, the support vector machine machine model showed the greatest discriminative capacity. In the end, an support vector machine model integrating five genes was developed, and its performance was shown to be excellent on an external validation dataset. The effectiveness in predicting bronchopulmonary dysplasia subtypes was further established by decision curves, calibration curves, and nomogram analyses. Conclusion: We developed a potential prediction model to assess the risk of endoplasmic reticulum stress subtypes and the clinical outcomes of bronchopulmonary dysplasia patients, and our work comprehensively revealed the complex association between endoplasmic reticulum stress and bronchopulmonary dysplasia.

Prognostic value of lactate metabolism-related gene expression signature in adult primary gliomas and its impact on the tumor immune microenvironment

Glioma is one of the most malignant intracerebral tumors, whose treatment means was limited, and prognosis was unsatisfactory. Lactate metabolism patterns have been shown to be highly heterogenous among different tumors and produce diverse impact on the tumor microenvironment. To understand the characteristics and implications of lactate metabolism gene expression, we developed a lactate metabolism-related gene expression signature of gliomas based on RNA-sequencing data of a total of 965 patient samples from TCGA, CGGA, and our own glioma cohort. Sixty-three lactate metabolism-related genes (LMGs) were differentially expressed between glioma and normal brain tissue, and consensus clustering analysis identified two clusters distinct LMG expression patterns. The consensus clusters differed in prognosis, molecular characteristics and estimated immune microenvironment landscape involving immune checkpoint proteins, T cell dysfunction and exclusion, as well as tumor purity. Univariate Cox regression and Least Absolute Shrinkage and Selection Operator (LASSO) Cox hazard regression was applied in determining of prognosis-related lactate metabolism genes (PRLMGs), on which prognostic lactate metabolism risk score (PLMRS) was constructed. The high PLMRS group was associated with significantly poorer patient outcome. A nomogram containing PLMRS and other independent prognostic variables was established with remarkable predictive performance on patient survival. Exploration on the somatic mutations and copy number variations of the high- and low-PLMRS groups demonstrated their distinct genetic background. Together, our results indicated that the expression signature of LMG was associated with the prognosis of glioma patients and influenced the activity of immune cells in the tumor microenvironment, which may serve as a potential biomarker for predicting response of gliomas to immunotherapy.

A Proteomic Platform Unveils the Brain Glycogen Phosphorylase as a Potential Therapeutic Target for Glioblastoma Multiforme

In the last few years, several efforts have been made to identify original strategies against glioblastoma multiforme (GBM): this requires a more detailed investigation of the molecular mechanism of GBM so that novel targets can be identified for new possible therapeutic agents. Here, using a combined biochemical and proteomic approach, we evaluated the ability of a blood–brain barrier-permeable 2,3-benzodiazepin-4-one, called 1g, to interfere with the activity and the expression of brain glycogen phosphorylase (PYGB) on U87MG cell line in parallel with the capability of this compound to inhibit the cell growth and cycle. Thus, our results highlighted PYGB as a potential therapeutic target in GBM prompting 1g as a capable anticancer drug thanks to its ability to negatively modulate the uptake and metabolism of glucose, the so-called “Warburg effect”, whose increase is considered a common feature of cancer cells in respect of their normal counterparts.

Liver glycogen phosphorylase is upregulated in glioblastoma and provides a metabolic vulnerability to high dose radiation

Channelling of glucose via glycogen, known as the glycogen shunt, may play an important role in the metabolism of brain tumours, especially in hypoxic conditions. We aimed to dissect the role of glycogen degradation in glioblastoma (GBM) response to ionising radiation (IR). Knockdown of the glycogen phosphorylase liver isoform (PYGL), but not the brain isoform (PYGB), decreased clonogenic growth and survival of GBM cell lines and sensitised them to IR doses of 10-12 Gy. Two to five days after IR exposure of PYGL knockdown GBM cells, mitotic catastrophy and a giant multinucleated cell morphology with senescence-like phenotype developed. The basal levels of the lysosomal enzyme alpha-acid glucosidase (GAA), essential for autolysosomal glycogen degradation, and the lipidated forms of gamma-aminobutyric acid receptor-associated protein-like (GABARAPL1 and GABARAPL2) increased in shPYGL U87MG cells, suggesting a compensatory mechanism of glycogen degradation. In response to IR, dysregulation of autophagy was shown by accumulation of the p62 and the lipidated form of GABARAPL1 and GABARAPL2 in shPYGL U87MG cells. IR increased the mitochondrial mass and the colocalisation of mitochondria with lysosomes in shPYGL cells, thereby indicating reduced mitophagy. These changes coincided with increased phosphorylation of AMP-activated protein kinase and acetyl-CoA carboxylase 2, slower ATP generation in response to glucose loading and progressive loss of oxidative phosphorylation. The resulting metabolic deficiencies affected the availability of ATP required for mitosis, resulting in the mitotic catastrophy observed in shPYGL cells following IR. PYGL mRNA and protein levels were higher in human GBM than in normal human brain tissues and high PYGL mRNA expression in GBM correlated with poor patient survival. In conclusion, we show a major new role for glycogen metabolism in GBM cancer. Inhibition of glycogen degradation sensitises GBM cells to high-dose IR indicating that PYGL is a potential novel target for the treatment of GBMs.

Stress Reactivity, Susceptibility to Hypertension, and Differential Expression of Genes in Hypertensive Compared to Normotensive Patients

Although half of hypertensive patients have hypertensive parents, known hypertension-related human loci identified by genome-wide analysis explain only 3% of hypertension heredity. Therefore, mainstream transcriptome profiling of hypertensive subjects addresses differentially expressed genes (DEGs) specific to gender, age, and comorbidities in accordance with predictive preventive personalized participatory medicine treating patients according to their symptoms, individual lifestyle, and genetic background. Within this mainstream paradigm, here, we determined whether, among the known hypertension-related DEGs that we could find, there is any genome-wide hypertension theranostic molecular marker applicable to everyone, everywhere, anytime. Therefore, we sequenced the hippocampal transcriptome of tame and aggressive rats, corresponding to low and high stress reactivity, an increase of which raises hypertensive risk; we identified stress-reactivity-related rat DEGs and compared them with their known homologous hypertension-related animal DEGs. This yielded significant correlations between stress reactivity-related and hypertension-related fold changes (log2 values) of these DEG homologs. We found principal components, PC1 and PC2, corresponding to a half-difference and half-sum of these log2 values. Using the DEGs of hypertensive versus normotensive patients (as the control), we verified the correlations and principal components. This analysis highlighted downregulation of β-protocadherins and hemoglobin as whole-genome hypertension theranostic molecular markers associated with a wide vascular inner diameter and low blood viscosity, respectively.

The analysis of metabolomics and transcriptomics data in head and neck squamous cell carcinoma

OBJECTIVE

Studies have shown that cancer progression of head and neck squamous cell carcinoma (HNSCC) is related with metabolic alterations. The aim of this study is to identify the clinical roles of metabolic alterations in HNSCC.

MATERIALS AND METHODS

Metabolism-related genes associated with HNSCC were searched in public databases. A predictive and efficacious LASSO model was fabricated to optimize the diagnosis that was based on these genes. Meantime, Ultra-Performance Liquid Chromatography-Quadrupole/Orbitrap High Resolution Mass Spectrometry (UHPLC-Q-Orbitrap HRMS) was used to compare patients with HNSCC (n=73) with healthy controls (HC) (n=51) for serum metabolites. Potential biomarkers and alterations in serum metabolites were analysed and evaluated using t-test analysis, principal component analysis and orthogonal partial least square discrimination analysis (OPLS-DA).

RESULTS

Overall, 21 differential metabolites were probed in serum, of which 8 metabolites had potential for clinical uses. Transcriptome analysis showed that 4 genes in the constructed LASSO model were found to be associated with 7 differential metabolites. Metabolic pathway analysis by MetaboAnalyst showed that the biomarkers that were related with HNSCC were closely related to 4 metabolism pathways (p<0.05).

CONCLUSION

To conclude, future research on HNSCC should be directed toward multi-omics to provide treatment, intervention, or diagnosis of the disease.