Increased Expression of PDK4 Was Displayed in Gastric Cancer and Exhibited an Association With Glucose Metabolism

Integrated single-cell sequencing, spatial transcriptome sequencing and bulk RNA sequencing highlights the molecular characteristics of parthanatos in gastric cancer

BACKGROUND

Parthanatos is a novel programmatic form of cell death based on DNA damage and PARP-1 dependency. Nevertheless, its specific role in the context of gastric cancer (GC) remains uncertain.

METHODS

In this study, we integrated multi-omics algorithms to investigate the molecular characteristics of parthanatos in GC. A series of bioinformatics algorithms were utilized to explore clinical heterogeneity of GC and further predict the clinical outcomes.

RESULTS

Firstly, we conducted a comprehensive analysis of the omics features of parthanatos in various human tumors, including genomic mutations, transcriptome expression, and prognostic relevance. We successfully identified 7 cell types within the GC microenvironment: myeloid cell, epithelial cell, T cell, stromal cell, proliferative cell, B cell, and NK cell. When compared to adjacent non-tumor tissues, single-cell sequencing results from GC tissues revealed elevated scores for the parthanatos pathway across multiple cell types. Spatial transcriptomics, for the first time, unveiled the spatial distribution characteristics of parthanatos signaling. GC patients with different parthanatos signals often exhibited distinct immune microenvironment and metabolic reprogramming features, leading to different clinical outcomes. The integration of parthanatos signaling and clinical indicators enabled the creation of novel survival curves that accurately assess patients' survival times and statuses.

CONCLUSIONS

In this study, the molecular characteristics of parthanatos' unicellular and spatial transcriptomics in GC were revealed for the first time. Our model based on parthanatos signals can be used to distinguish individual heterogeneity and predict clinical outcomes in patients with GC.

Prognostic value of RNA methylation-related genes in gastric adenocarcinoma based on bioinformatics

Background

Gastric cancer (GC) is a malignant tumor that originates from the epithelium of the gastric mucosa and has a poor prognosis. Stomach adenocarcinoma (STAD) covers 95% of total gastric cancer. This study aimed to identify the prognostic value of RNA methylation-related genes in gastric cancer.

Methods

In this study, The Cancer Genome Atlas (TCGA)-STAD and GSE84426 cohorts were downloaded from public databases. Patients were classified by consistent cluster analysis based on prognosis-related differentially expressed RNA methylation genes Prognostic genes were obtained by differential expression, univariate Cox and least absolute shrinkage and selection operator (LASSO) analyses. The prognostic model was established and validated in the training set, test set and validation set respectively. Independent prognostic analysis was implemented. Finally, the expression of prognostic genes was affirmed by reverse transcription quantitative PCR (RT-qPCR).

Results

In total, four prognostic genes (ACTA2, SAPCD2, PDK4 and APOD) related to RNA methylation were identified and enrolled into the risk signature. The STAD patients were divided into high- and low-risk groups based on the medium value of the risk score, and patients in the high-risk group had a poor prognosis. In addition, the RNA methylation-relevant risk signature was validated in the test and validation sets, and was authenticated as a reliable independent prognostic predictor. The nomogram was constructed based on the independent predictors to predict the 1/3/5-year survival probability of STAD patients. The gene set enrichment analysis (GSEA) result suggested that the poor prognosis in the high-risk subgroup may be related to immune-related pathways. Finally, the experimental results indicated that the expression trends of RNA methylation-relevant prognostic genes in gastric cancer cells were in agreement with the result of bioinformatics.

Conclusion

Our study established a novel RNA methylation-related risk signature for STAD, which was of considerable significance for improving prognosis of STAD patients and offering theoretical support for clinical therapy.

Inhibition of Pyruvate Dehydrogenase Kinase 4 Protects Cardiomyocytes from lipopolysaccharide-Induced Mitochondrial Damage by Reducing Lactate Accumulation

Mitochondrial dysfunction is considered one of the major pathogenic mechanisms of sepsis-induced cardiomyopathy (SIC). Pyruvate dehydrogenase kinase 4 (PDK4), a key regulator of mitochondrial metabolism, is essential for maintaining mitochondrial function. However, its specific role in SIC remains unclear. To investigate this, we established an in vitro model of septic cardiomyopathy using lipopolysaccharide (LPS)-induced H9C2 cardiomyocytes. Our study revealed a significant increase in PDK4 expression in LPS-treated H9C2 cardiomyocytes. Inhibiting PDK4 with dichloroacetic acid (DCA) improved cell survival, reduced intracellular lipid accumulation and calcium overload, and restored mitochondrial structure and respiratory capacity while decreasing lactate accumulation. Similarly, Oxamate, a lactate dehydrogenase inhibitor, exhibited similar effects to DCA in LPS-treated H9C2 cardiomyocytes. To further validate whether PDK4 causes cardiomyocyte and mitochondrial damage in SIC by promoting lactate production, we upregulated PDK4 expression using PDK4-overexpressing lentivirus in H9C2 cardiomyocytes. This resulted in elevated lactate levels, impaired mitochondrial structure, and reduced mitochondrial respiratory capacity. However, inhibiting lactate production reversed the mitochondrial dysfunction caused by PDK4 upregulation. In conclusion, our study highlights the pathogenic role of PDK4 in LPS-induced cardiomyocyte and mitochondrial damage by promoting lactate production. Therefore, targeting PDK4 and its downstream product lactate may serve as promising therapeutic approaches for treating SIC.

Energy metabolism: a new target for gastric cancer treatment

Gastric cancer is the fifth most common malignancy worldwide having the fourth highest mortality rate. Energy metabolism is key and closely linked to tumour development. Most important in the reprogramming of cancer metabolism is the Warburg effect, which suggests that tumour cells will utilise glycolysis even with normal oxygen levels. Various molecules exert their effects by acting on enzymes in the glycolytic pathway, integral to glycolysis. Second, mitochondrial abnormalities in the reprogramming of energy metabolism, with consequences for glutamine metabolism, the tricarboxylic acid cycle and oxidative phosphorylation, abnormal fatty acid oxidation and plasma lipoprotein metabolism are important components of tumour metabolism. Third, inflammation-induced oxidative stress is a danger signal for cancer. Fourth, patterns of signalling pathways involve all aspects of metabolic transduction, and many clinical drugs exert their anticancer effects through energy metabolic signalling. This review summarises research on energy metabolism genes, enzymes and proteins and transduction pathways associated with gastric cancer, and discusses the mechanisms affecting their effects on postoperative treatment resistance and prognoses of gastric cancer. We believe that an in-depth understanding of energy metabolism reprogramming will aid the diagnosis and subsequent treatment of gastric cancer.

Deficiency of TOP1MT enhances glycolysis through the stimulation of PDK4 expression in gastric cancer

BACKGROUND

Abnormal glucose metabolism is one of the determinants of maintaining malignant characteristics of cancer. Targeting cancer metabolism is regarded as a new strategy for cancer treatment. Our previous studies have found that TOP1MT is a crucial gene that inhibits glycolysis and cell metastasis of gastric cancer (GC) cells, but the mechanism of its regulation of glycolysis remains unclear.

METHODS

Transcriptome sequencing data, clinic-pathologic features of GC from a variety of public databases, and WGCNA were used to identify novel targets of TOP1MT. Immunohistochemical results of 250 patients with GC were used to analyze the relative expression relationship between TOP1MT and PDK4. The function of TOP1MT was investigated by migration assays and sea-horse analysis in vitro.

RESULTS

We discovered a mitochondrial topoisomerase I, TOP1MT, which correlated with a higher risk of metastasis. Functional experiments revealed that TOP1MT deficiency promotes cell migration and glycolysis through increasing PDK4 expression. Additionally, the stimulating effect of TOP1MT on glycolysis may be effectively reversed by PDK4 inhibitor M77976.

CONCLUSIONS

In brief, our work demonstrated the critical function of TOP1MT in the regulation of glycolysis by PDK4 in gastric cancer. Inhibiting glycolysis and limiting tumor metastasis in GC may be accomplished by suppressing PDK4.

High glucose promotes benign prostatic hyperplasia by downregulating PDK4 expression

As men age, a growing number develop benign prostatic hyperplasia (BPH). According to previous research, diabetes may be a risk factor. Pyruvate dehydrogenase kinase 4 (PDK4) is closely related to glucose metabolism and plays a role in the onset and progression of numerous illnesses. This study aimed to determine the direct effects of high glucose environment on prostate epithelial cells, in particular by altering PDK4 expression levels. In this investigation, normal prostatic epithelial cells (RWPE-1) and human benign prostatic hyperplasia epithelial cells (BPH-1) were treated with 50 mM glucose to show the alteration of high glucose in prostate cells. PDK4-target siRNA, PDK4-expression plasmid were used to investigate the effects of PDK4. Rosiglitazone (RG), a PPARγ agonist, with the potential to up-regulate PDK4 expression was also used for treating prostate cells. The expression of PDK4 in human prostate samples was also analyzed. The effects of high glucose therapy on BPH-1 and RWPE-1 cells were demonstrated to enhance proliferation, epithelial-mesenchymal transition (EMT), suppress apoptosis, and down-regulate PDK4 expression. Additionally, diabetes-related BPH patients had reduced PDK4 expression. Following the application of PDK4-target siRNA, a comparable outcome was seen. The PDK4-expression plasmid therapy, however, produced the opposite results. RG with the ability to elevate PDK4 expression might be used to treat BPH. Changes in the metabolism of lipids and glucose may be the cause of these consequences. These findings showed that high glucose treatment might facilitate BPH development, and may be related to the down-regulation of PDK4. PDK4 might be a potential therapeutic target of BPH.

Baicalin mitigated IL-1β-Induced osteoarthritis chondrocytes damage through activating mitophagy

Mitophagy is related to chondrocyte homeostasis and plays a key role in the progress of osteoarthritis (OA). Baicalin has a protective effect on OA chondrocytes, the aim of this study was to explore whether the effect of Baicalin on IL-1β-induced chondrocyte injury is related to the regulation of mitophagy. The expression of collagen II in chondrocytes was detected to identify chondrocytes. The effects of different concentrations of Baicalin (10, 20 and 40 μM), autophagy inhibitor (3-Methyladenine), autophagy activator (rapamycin) and Baicalin combined with PI3K agonist (740Y-P) on the viability (cell counting kit 8), apoptosis (flow cytometry), autophagy activation (Monodansylcadaverine staining) and mitochondrial membrane potential (JC-1 kit) of IL-1β-induced chondrocytes were evaluated. The co-localization of autophagosome and mitochondria was determined by immunofluorescence. Apoptosis-, autophagy-, PI3K/AKT/mTOR pathway- and mitophagy-related proteins were detected by western blot. Our result revealed that Baicalin and rapamycin facilitated cell viability, autophagy and mitophagy, elevated mitochondrial membrane potential and suppressed apoptosis of IL-1β-induced rat chondrocytes. In addition, Baicalin and rapamycin upregulated the levels of Bcl-2, Beclin 1, LC3-II/LC3-I, p-Drp1, PINK1 and Parkin as well as downregulated the levels of Bax, cleaved caspase-3, P62, p-PI3K/PI3K, p-mTOR/mTOR and Drp1 in IL-1β-induced rat chondrocytes. However, 3-Methyladenine did the opposite effects of Baicalin and 740Y-P reversed the effects of Baicalin on IL-1β-induced rat chondrocytes. In conclusion, Baicalin activated mitophagy in IL-1β-induced chondrocytes by inhibiting PI3K/AKT/mTOR pathway and activating PINK1/Parkin and PINK1/Drp-1 pathway, thereby reducing the chondrocyte injury.

Anti-Metastatic Effect of Pyruvate Dehydrogenase Kinase 4 Inhibition in Bladder Cancer via the ERK, SRC, and JNK Pathways

Bladder cancer is a common global cancer with a high percentage of metastases and high mortality rate. Thus, it is necessary to identify new biomarkers that can be helpful in diagnosis. Pyruvate dehydrogenase kinase 4 (PDK4) belongs to the PDK family and plays an important role in glucose utilization in living organisms. In the present study, we evaluated the role of PDK4 in bladder cancer and its related protein changes. First, we observed elevated PDK4 expression in high-grade bladder cancers. To screen for changes in PDK4-related proteins in bladder cancer, we performed a comparative proteomic analysis using PDK4 knockdown cells. In bladder cancer cell lines, PDK4 silencing resulted in a lower rate of cell migration and invasion. In addition, a PDK4 knockdown xenograft model showed reduced bladder cancer growth in nude mice. Based on our results, PDK4 plays a critical role in the metastasis and growth of bladder cancer cells through changes in ERK, SRC, and JNK.

A novel anoikis-related prognostic signature associated with prognosis and immune infiltration landscape in clear cell renal cell carcinoma

Background: Clear cell renal cell carcinoma (ccRCC) is the most common histological subtype of renal cell carcinoma (RCC). Anoikis plays an essential function in tumourigenesis, whereas the role of anoikis in ccRCC remains unclear. Methods: Anoikis-related genes (ARGs) were collected from the MSigDB database. According to univariate Cox regression analysis, the least absolute shrinkage and selection operator (LASSO) algorithm was utilized to select the ARGs associated with the overall rate (OS). Multivariate Cox regression analysis was conducted to identify 5 prognostic ARGs, and a risk model was established. The Kaplan-Meier survival analysis was used to evaluate the OS rate of ccRCC patients. Gene ontology (GO), Kyoto encyclopedia of genes and genomes (KEGG), and Gene set enrichment analysis (GSVA) were utilized to investigate the molecular mechanism of patients in the low- and high-risk group. ESTIMATE, CIBERSOT, and single sample gene set enrichment analysis (ssGSEA) algorithms were conducted to estimate the immune infiltration landscape. Consensus clustering analysis was performed to divide the patients into different subgroups. Results: A fresh risk model was constructed based on the 5 prognostic ARGs (CHEK2, PDK4, ZNF304, SNAI2, SRC). The Kaplan-Meier survival analysis indicated that the OS rate of patients with a low-risk score was significantly higher than those with a high-risk score. Consensus clustering analysis successfully clustered the patients into two subgroups, with a remarkable difference in immune infiltration landscape and prognosis. The ESTIMATE, CIBERSORT, and ssGSEA results illustrated a significant gap in immune infiltration landscape of patients in the low- and high-risk group. Enrichment analysis and GSVA revealed that immune-related signaling pathways might mediate the role of ARGs in ccRCC. The nomogram results illustrated that the ARGs prognostic signature was an independent prognostic predictor that distinguished it from other clinical characteristics. TIDE score showed a promising immunotherapy response of ccRCC patients in different risk subgroups and cluster subgroups. Conclusion: Our study revealed that ARGs play a carcinogenic role in ccRCC. Additionally, we firstly integrated multiple ARGs to establish a risk-predictive model. This study highlights that ARGs could be implemented as a stratification factor for individualized and precise treatment in ccRCC patients.

m7G regulator-mediated molecular subtypes and tumor microenvironment in kidney renal clear cell carcinoma

Background: RNA methylation modification plays an important role in immune regulation. m7G RNA methylation is an emerging research hotspot in the RNA methylation field. However, its role in the tumor immune microenvironment of kidney renal clear cell carcinoma (KIRC) is still unclear.

Methods: We analyzed the expression profiles of 29 m7G regulators in KIRC, integrated multiple datasets to identify a novel m7G regulator-mediated molecular subtype, and developed the m7G score. We evaluated the immune tumor microenvironments in m7G clusters and analyzed the correlation of the m7G score with immune cells and drug sensitivity. We tested the predictive power of the m7G score for prognosis of patients with KIRC and verified the predictive accuracy of the m7G score by using the GSE40912 and E-MTAB-1980 datasets. The genes used to develop the m7G score were verified by qRT-PCR. Finally, we experimentally analyzed the effects of WDR4 knockdown on KIRC proliferation, migration, invasion, and drug sensitivity.

Results: We identified three m7G clusters. The expression of m7G regulators was higher in cluster C than in other clusters. m7G cluster C was related to immune activation, low tumor purity, good prognosis, and low m7G score. Cluster B was related to drug metabolism, high tumor purity, poor survival, and high m7G score. Cluster A was related to purine metabolism. The m7G score can well-predict the prognosis of patients with KIRC, and its prediction accuracy based on the m7G score nomogram was very high. Patients with high m7G scores were more sensitive to rapamycin, gefitinib, sunitinib, and vinblastine than other patients. Knocking down WDR4 can inhibit the proliferation, migration, and invasion of 786-0 and Caki-1 cells and increase sensitivity to sorafenib and sunitinib.

Conclusion: We proposed a novel molecular subtype related to m7G modification and revealed the immune cell infiltration characteristics of different subtypes. The developed m7G score can well-predict the prognosis of patients with KIRC, and our research provides a basis for personalized treatment of patients with KIRC.

Pyroptosis, apoptosis, and necroptosis molecular subtype derived prognostic signature universal applicable for gastric cancer-A large sample and multicenter retrospective analysis

BACKGROUND

Whether pyroptosis, apoptosis, and necroptosis (PAN) molecular subtypes exist in gastric cancer (GC) remains unclear.

METHODS

Seven independent cohorts including a total of 1901 GC patients were enrolled in our research. TCGA (n = 371) and GSE84437 (n = 433) were combined into one cohort (n = 804) to screen for prognosis-related PAN genes using a univariate Cox regression analysis. The R package "ConsensusClusterPlus" was applied to conduct a clustering analysis of the combination set based on prognosis-related PAN genes. The R package "limma" was used for the identification of differentially expressed genes (DEGs) between different PAN clusters (FDR <0.05 and |logFC|>1). The combined cohort was randomly divided into a training group (n = 484) and a test group (n = 320) at a ratio of 6:4 to establish and verify the prognostic model. A univariate Cox regression analysis, least absolute shrinkage and selection operator method (LASSO) regression analysis, and multivariate Cox regression analysis were used for the identification of prognostic genes and the construction of risk scores. Another five independent cohorts (GSE62254, n = 300; GSE15459, n = 191; GSE26901, n = 109; GSE26253, n = 432; and GSE13861, n = 65) were used for external validation to verify the accuracy and stability of the prognostic signature.

RESULTS

The internal and external validation demonstrated that the 5-gene risk score (LOXL4, SLCO2A1, CST2, PDK4, and MMP11) was an effective instrument for the prognostic risk classification of GC patients. The overall survival (OS) and relapse-free survival (RFS) in the high-risk group were significantly lower than those in the low-risk group and were accompanied by a larger proportion of macrophage and regulatory T cell infiltration. The low-risk group had a good prognosis, with a high tumor mutation burden (TMB), strong cytolytic activity, and a higher proportion of activated CD4 T cell infiltration. In addition, compared with the low-risk group, the cancer-related pathways in the high-risk group were overactivated, and the function of DNA damage repair (DDR) was significantly weakened. Regarding drug sensitivity, the high-risk group was more suitable for targeted drugs, such as axitinib, lapatinib, and nilotinib. The low-risk group was more sensitive to chemotherapy, such as cisplatin, gemcitabine, and vinorelbine.

CONCLUSION

A universally applicable prognostic signature of GC is proposed in this research based on pyroptosis, apoptosis, and necroptosis (PAN) molecular subtypes.