PYGB facilitates cell proliferation and invasiveness in non-small cell lung cancer by activating the Wnt-β-catenin signaling pathway

Identification and validation of a glycosyltransferase gene signature as a novel prognostic model for lung adenocarcinoma

Background

The role of glycosyltransferase (GT) genes in lung adenocarcinoma (LUAD) needs further elucidation. Thus, our study aims to identify the prognostic gene signature of LUAD and explore its molecular functions.

Methods

We initially extracted GT gene sets from the database, and obtained mRNA expression levels and clinical data from The Cancer Genome Atlas (TCGA) database. For constructing a prognostic model for GT genes, we utilized univariate, least absolute shrinkage and selection operator (LASSO), and multivariate Cox regression analyses. Using the model, patients were categorized into high- and low-risk groups. Additionally, we evaluated differences in tumor immune infiltration between these groups and identified potential therapeutic drugs. Finally, we experimentally validated the expression levels of these crucial prognostic genes.

Results

We developed a risk score comprising nine GT genes (C1GALT1, FUT1, GALNT2, PLOD2, POMK, PYGB, ST3GAL6, UGT2B11, UGT3A1). Patients were then categorized into low- and high-risk groups based on this score. The low-risk group showed superior overall survival (OS) compared to the high-risk group. There were significantly distinct tumor immune microenvironment statuses observed between the two groups. We identified potential therapeutic drugs, including the MEK inhibitor (PD-184352). Finally, we verified the expression of these nine GT genes through immunohistochemistry (IHC) staining and quantitative real-time PCR (qPCR).

Conclusion

We identified a distinct LUAD GT gene signature, and these differentially expressed mRNAs could serve as valuable prognostic biomarkers and therapeutic targets. Furthermore, we experimentally validated their expression levels and identified potential therapeutic agents.

Population-enriched innate immune variants may identify candidate gene targets at the intersection of cancer and cardio-metabolic disease

Both cancer and cardio-metabolic disease disparities exist among specific populations in the US. For example, African Americans experience the highest rates of breast and prostate cancer mortality and the highest incidence of obesity. Native and Hispanic Americans experience the highest rates of liver cancer mortality. At the same time, Pacific Islanders have the highest death rate attributed to type 2 diabetes (T2D), and Asian Americans experience the highest incidence of non-alcoholic fatty liver disease (NAFLD) and cancers induced by infectious agents. Notably, the pathologic progression of both cancer and cardio-metabolic diseases involves innate immunity and mechanisms of inflammation. Innate immunity in individuals is established through genetic inheritance and external stimuli to respond to environmental threats and stresses such as pathogen exposure. Further, individual genomes contain characteristic genetic markers associated with one or more geographic ancestries (ethnic groups), including protective innate immune genetic programming optimized for survival in their corresponding ancestral environment(s). This perspective explores evidence related to our working hypothesis that genetic variations in innate immune genes, particularly those that are commonly found but unevenly distributed between populations, are associated with disparities between populations in both cancer and cardio-metabolic diseases. Identifying conventional and unconventional innate immune genes that fit this profile may provide critical insights into the underlying mechanisms that connect these two families of complex diseases and offer novel targets for precision-based treatment of cancer and/or cardio-metabolic disease.

Unveiling the role of PYGB in pancreatic cancer: a novel diagnostic biomarker and gene therapy target

PURPOSE

Pancreatic cancer (PC) is a highly malignant tumor that poses a severe threat to human health. Brain glycogen phosphorylase (PYGB) breaks down glycogen and provides an energy source for tumor cells. Although PYGB has been reported in several tumors, its role in PC remains unclear.

METHODS

We constructed a risk diagnostic model of PC-related genes by WGCNA and LASSO regression and found PYGB, an essential gene in PC. Then, we explored the pro-carcinogenic role of PYGB in PC by in vivo and in vitro experiments.

RESULTS

We found that PYGB, SCL2A1, and SLC16A3 had a significant effect on the diagnosis and prognosis of PC, but PYGB had the most significant effect on the prognosis. Pan-cancer analysis showed that PYGB was highly expressed in most of the tumors but had the highest correlation with PC. In TCGA and GEO databases, we found that PYGB was highly expressed in PC tissues and correlated with PC's prognostic and pathological features. Through in vivo and in vitro experiments, we found that high expression of PYGB promoted the proliferation, invasion, and metastasis of PC cells. Through enrichment analysis, we found that PYGB is associated with several key cell biological processes and signaling pathways. In experiments, we validated that the MAPK/ERK pathway is involved in the pro-tumorigenic mechanism of PYGB in PC.

CONCLUSION

Our results suggest that PYGB promotes PC cell proliferation, invasion, and metastasis, leading to poor patient prognosis. PYGB gene may be a novel diagnostic biomarker and gene therapy target for PC.

Brain-Type Glycogen Phosphorylase (PYGB) in the Pathologies of Diseases: A Systematic Review

Glycogen metabolism is a form of crucial metabolic reprogramming in cells. PYGB, the brain-type glycogen phosphorylase (GP), serves as the rate-limiting enzyme of glycogen catabolism. Evidence is mounting for the association of PYGB with diverse human diseases. This review covers the advancements in PYGB research across a range of diseases, including cancer, cardiovascular diseases, metabolic diseases, nervous system diseases, and other diseases, providing a succinct overview of how PYGB functions as a critical factor in both physiological and pathological processes. We present the latest progress in PYGB in the diagnosis and treatment of various diseases and discuss the current limitations and future prospects of this novel and promising target.

A novel necroptosis signature for predicting survival in lung adenocarcinoma

BACKGROUND

To explore the necroptosis-related genes (NRGs) signature and its predictive values in lung adenocarcinoma (LUAD).

METHODS

The training cohort consisted of tumor samples from The Cancer Genome Atlas, and the validation set comprised data from the Gene Expression Omnibus. Univariate and multivariate Cox regression analyses were applied to identify the prognostic NRG signature as an independent molecular indicator. Correlation analysis was used for the association assessment between the NRG signature and immune checkpoint molecules.

RESULTS

NRGs involved in necroptosis and immune NOD-like receptor signaling. The NRG signature based on eight NRGs can divide tumors into high-risk and low-risk groups, which was significantly associated with worse survival. Multivariate Cox regression analysis showed that this NRG signature remained an independent prognostic indicator. Stratification analyses demonstrated that this NRG signature was still effective for predicting survival in each stratum of age, gender, and tumor stage. The ROC curve showed a good predictive ability using the NRG signature in the validation cohort (AUC = 0.81). The NRG signature was related to immune checkpoint molecules PD - 1, PD-L1, and PD-L2.

CONCLUSIONS

The NRG signature could be a novel predictor of the prognosis and may become a potential therapeutic target in LUAD.

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.

Recent Developments and Challenges in Molecular-Targeted Therapy of Non-Small-Cell Lung Cancer

Treatment of lung cancer with conventional therapies, which include radiation, surgery, and chemotherapy results in multiple undesirable adverse or side effects. The major clinical challenge in developing new drug therapies for lung cancer is resistance, which involves mutations and disturbance in various signaling pathways. Molecular abnormalities related to epidermal growth factor receptor (EGFR), v-Raf murine sarcoma viral oncogene homolog B1 (B-RAF) Kirsten rat sarcoma virus (KRAS) mutations, translocation of the anaplastic lymphoma kinase (ALK) gene, mesenchymal-epithelial transition factor (MET) amplification have been studied to overcome the resistance and to develop new therapies for non-small cell lung cancer (NSCLC). But, inevitable development of resistance presents limits the clinical benefits of various new drugs. Here, we review current progress in the development of molecularly targeted therapies, concerning six clinical biomarkers: EGFR, ALK, MET, ROS-1, KRAS, and B-RAF for NSCLC treatment.

Identification of a glycolysis-related gene signature for survival prediction of ovarian cancer patients

Background

Ovarian cancer (OV) is deemed the most lethal gynecological cancer in women. The aim of this study was to construct an effective gene prognostic model for predicting overall survival (OS) in patients with OV.

Methods

The expression profiles of glycolysis‐related genes (GRGs) and clinical data of patients with OV were extracted from The Cancer Genome Atlas (TCGA) database. Univariate, multivariate, and least absolute shrinkage and selection operator Cox regression analyses were conducted, and a prognostic signature based on GRGs was constructed. The predictive ability of the signature was analyzed using training and test sets.

Results

A gene risk signature based on nine GRGs (ISG20, CITED2, PYGB, IRS2, ANGPTL4, TGFBI, LHX9, PC, and DDIT4) was identified to predict the survival outcome of patients with OV. The signature showed a good prognostic ability for OV, particularly high‐grade OV, in the TCGA dataset, with areas under the curve (AUC) of 0.709 and 0.762 for 3‐ and 5‐year survival, respectively. Similar results were found in the test sets, and the AUCs of 3‐, 5‐year OS were 0.714 and 0.772 in the combined test set. And our signature was an independent prognostic factor. Moreover, a nomogram combining the prediction model and clinical factors was developed.

Conclusion

Our study established a nine‐GRG risk model and nomogram to better predict OS in patients with OV. The risk model represents a promising and independent prognostic predictor for patients with OV. Moreover, our study on GRGs could offer guidance for the elucidation of underlying mechanisms in future studies.

Integration of transcriptomics and metabolomics reveals anlotinib-induced cytotoxicity in colon cancer cells

BACKGROUND

Mounting evidences suggested that anlotinib exhibits effective anti-tumor activity in various cancer types, such as lung cancer, glioblastoma and medullary thyroid cancer. However, its function in colon cancer remains to be further revealed.

METHODS

Colon cancer cells (HCT-116) were treated with or without anlotinib. Transcript and metabolite data were generated through RNA sequencing and liquid chromatography-tandem mass spectrometry, respectively. The integrated analysis transcriptomics and metabolomics was conducted using R programs and online tools, including ClusterProfiler R program, GSEA, Prognoscan and Cytoscape.

RESULTS

We found that differentially expressed genes (DEGs) were mainly involved in metabolic pathways and ribosome pathway. Structural maintenance of chromosome 3 (SMC3), Topoisomerase II alpha (TOP2A) and Glycogen phosphorylase B (PYGB) are the most significant DEGs which bring poor clinical prognosis in colon cancer. The analysis of metabolomics presented that most of the differentially accumulated metabolites (DAMs) were amino acids, such as L-glutamine, DL-serine and aspartic acid. The joint analysis of DEGs and DAMs showed that they were mainly involved in protein digestion and absorption, ABC transporters, central carbon metabolism, choline metabolism and Gap junction. Anlotinib affected protein synthesis and energy supporting of colon cancer cells by regulating amino acid metabolism.

CONCLUSIONS

Anlotinib has a significant effect on colon cancer in both transcriptome and metabolome. Our research will provide possible targets for colon cancer treatment using anlotinib.

Identification of metabolism-associated genes and construction of a prognostic signature in bladder cancer

BACKGROUND

Bladder cancer (BC) is a commonly diagnosed malignant tumor in the urinary system, with a high morbidity and a high recurrence rate. Current studies indicated that metabolism-associated genes (MAGs) having critical roles in the etiology of BC. The present study aims to identify differentially expressed MAGs and construct a MAGs based prognostic risk signature for BC by using The Cancer Genome Atlas (TCGA) database and proteomics data.

METHODS

RNA-sequence data from the TCGA database and proteomics data from our BC samples were used to identify differentially expressed MAGs and construct a MAGs based prognostic signature in BC. Subsequently, survival analysis and nomogram were used to evaluate the prognostic and predictive value of the MAGs based signature in BC. RNA isolation and reverse transcription‑quantitative PCR (RT-qPCR) were further performed to investigate the expression levels of MAGs in BC cells and explore the relationship between MAGs and M2 tumor associated macrophages (TAMs) secreted transforming growth factor-β1 (TGF-β1) in BC cells.

RESULTS

A total of 23 differentially expressed MAGs were identified and five MAGs were finally used to construct a MAGs based signature. Survival analysis revealed that the MAGs based signature was closely correlated with the survival outcomes of patients with BC. A nomogram with the MAGs based signature risk score and clinical features was also constructed to facilitate the individualized prediction of BC patients. RT-qPCR showed that five MAGs were significantly differentially expressed and the expression levels of three MAGs were positively correlated with M2 TAMs secreted TGF-β1 in T24 cells.

CONCLUSIONS

Our study identified novel prognostic MAGs and constructed a MAGs based signature, which can be used as an independent factor in evaluating the prognosis of patients with BC. Furthermore, M2 TAMs may promote the expression of MAGs via the TGF-β1 signaling pathway in the microenvironment of BC. Further clinical trials and experimental explorations are needed to validate our observations in BC.

Integrative analysis of genomic alteration, immune cells infiltration and prognosis of lung squamous cell carcinoma (LUSC) to identify smoking-related biomarkers

Lung squamous cell carcinoma (LUSC) is the most common histologic type of smoking-related non-small cell lung cancer (NSCLC). However, there are no identified potential biomarkers for smoking-related LUSC diagnosis and prognosis. Especially, the characteristics of genetic alteration and tumor microenvironment induced by cigarette smoking remain unknown. Here, we performed integrative analysis of 463 LUSC with smoking history information from The Cancer Genome Atlas (TCGA). Non-smokers had the best prognosis, and current reformed smokers had better overall survival (OS) than current smokers in all and stage I-II cohort. Then, pathway enrichment analysis might suggest that smoking may play a role in regulating tumor metabolism and invasion and metastasis via those pathways. We constructed an eight-gene signature and identified WNT7A, Solute carrier-7A5 (SLC7A5) and Brain‑type glycogen phosphorylase (PYGB), which may be served as biomarkers related to the smoking. Notably, the single copy deletion of WNT7A and SLC17A5 and the low-level amplification of PYGB may be related to the epigenetic mechanism of smoking on tumorigenesis. We also estimated the relative proportion of 24 immune cell subtypes within tumor microenvironment in different smoking status. Interestingly, we found NK cells activated, NK cells resting and endothelial cells might play an important role in immunologic dysfunction and harmful tumor microenvironment induced by cigarette smoking. Our research has identified potential biomarkers for smoking-related LUSC diagnosis and prognosis, which would help to further understand the pathogenesis of LUSC.