Mutual regulation between phosphofructokinase 1 platelet isoform and VEGF promotes glioblastoma tumor growth

Integrative bioinformatics analysis of miRNA and mRNA expression profiles and identification of associated miRNA-mRNA network in intracranial aneurysms

Background

Intracranial aneurysms (IAs) represent protrusions in the vascular wall, with their growth and wall thinning influenced by various factors. These processes can culminate in the rupture of the aneurysm, leading to subarachnoid hemorrhage (SAH). Unfortunately, over half of the patients prove unable to withstand SAH, succumbing to adverse outcomes despite intensive therapeutic interventions, even in premier medical facilities. This study seeks to discern the pivotal microRNAs (miRNAs) and genes associated with the formation and progression of IAs.

Methods

The investigation gathered expression data of miRNAs (from GSE66240) and mRNAs (from GSE158558) within human aneurysm tissue and superficial temporal artery (STA) samples, categorizing them into IA and normal groups. This classification was based on the Gene Expression Omnibus (GEO) database.

Results

A total of 70 differentially expressed microRNAs (DEMs) and 815 differentially expressed mRNAs (DEGs) were pinpointed concerning IA. Subsequently, a miRNA-mRNA network was constructed, incorporating 9 significantly upregulated DEMs and 211 significantly downregulated DEGs. Simultaneously, functional enrichment and pathway analyses were conducted on both DEMs and DEGs. Through protein-protein interaction (PPI) network analysis and functional enrichment, 9 significantly upregulated DEMs (hsa-miR-188-5p, hsa-miR-590-5p, hsa-miR-320b, hsa-miR-423-5p, hsa-miR-140-5p, hsa-miR-486-5p, hsa-miR-320a, hsa-miR-342-3p, and hsa-miR-532-5p) and 50 key genes (such as ATP6V1G1, KBTBD6, VIM, PA2G4, DYNLL1, METTL21A, MDH2, etc.) were identified, suggesting their potential significant role in IA. Among these genes, ten were notably negatively regulated by at least two key miRNAs.

Conclusions

The findings of this study provide valuable insights into the potential pathogenic mechanisms underlying IA by elucidating a miRNA-mRNA network. This comprehensive approach sheds light on the intricate interplay between miRNAs and genes, offering a deeper understanding of the molecular dynamics involved in IA development and progression.

Understanding the Role of Endothelial Cells in Glioblastoma: Mechanisms and Novel Treatments

Glioblastoma is a highly aggressive neoplasm and the most common primary malignant brain tumor. Endothelial tissue plays a critical role in glioblastoma growth and progression, facilitating angiogenesis, cellular communication, and tumorigenesis. In this review, we present an up-to-date and comprehensive summary of the role of endothelial cells in glioblastomas, along with an overview of recent developments in glioblastoma therapies and tumor endothelial marker identification.

Hitting the Sweet Spot: How Glucose Metabolism Is Orchestrated in Space and Time by Phosphofructokinase-1

Glycolysis is the central metabolic pathway across all kingdoms of life. Intensive research efforts have been devoted to understanding the tightly orchestrated processes of converting glucose into energy in health and disease. Our review highlights the advances in knowledge of how metabolic and gene networks are integrated through the precise spatiotemporal compartmentalization of rate-limiting enzymes. We provide an overview of technically innovative approaches that have been applied to study phosphofructokinase-1 (PFK1), which represents the fate-determining step of oxidative glucose metabolism. Specifically, we discuss fast-acting chemical biology and optogenetic tools that have delineated new links between metabolite fluxes and transcriptional reprogramming, which operate together to enact tissue-specific processes. Finally, we discuss how recent paradigm-shifting insights into the fundamental basis of glycolytic regulatory control have shed light on the mechanisms of tumorigenesis and could provide insight into new therapeutic vulnerabilities in cancer.

AMPK-HIF-1α signaling enhances glucose-derived de novo serine biosynthesis to promote glioblastoma growth

BACKGROUND

Cancer cells undergo cellular adaptation through metabolic reprogramming to sustain survival and rapid growth under various stress conditions. However, how brain tumors modulate their metabolic flexibility in the naturally serine/glycine (S/G)-deficient brain microenvironment remain unknown.

METHODS

We used a range of primary/stem-like and established glioblastoma (GBM) cell models in vitro and in vivo. To identify the regulatory mechanisms of S/G deprivation-induced metabolic flexibility, we employed high-throughput RNA-sequencing, transcriptomic analysis, metabolic flux analysis, metabolites analysis, chromatin immunoprecipitation (ChIP), luciferase reporter, nuclear fractionation, cycloheximide-chase, and glucose consumption. The clinical significances were analyzed in the genomic database (GSE4290) and in human GBM specimens.

RESULTS

The high-throughput RNA-sequencing and transcriptomic analysis demonstrate that the de novo serine synthesis pathway (SSP) and glycolysis are highly activated in GBM cells under S/G deprivation conditions. Mechanistically, S/G deprivation rapidly induces reactive oxygen species (ROS)-mediated AMP-activated protein kinase (AMPK) activation and AMPK-dependent hypoxia-inducible factor (HIF)-1α stabilization and transactivation. Activated HIF-1α in turn promotes the expression of SSP enzymes phosphoglycerate dehydrogenase (PHGDH), phosphoserine aminotransferase 1 (PSAT1), and phosphoserine phosphatase (PSPH). In addition, the HIF-1α-induced expression of glycolytic genes (GLUT1, GLUT3, HK2, and PFKFB2) promotes glucose uptake, glycolysis, and glycolytic flux to fuel SSP, leading to elevated de novo serine and glycine biosynthesis, NADPH/NADP+ ratio, and the proliferation and survival of GBM cells. Analyses of human GBM specimens reveal that the levels of overexpressed PHGDH, PSAT1, and PSPH are positively correlated with levels of AMPK T172 phosphorylation and HIF-1α expression and the poor prognosis of GBM patients.

CONCLUSION

Our findings reveal that metabolic stress-enhanced glucose-derived de novo serine biosynthesis is a critical metabolic feature of GBM cells, and highlight the potential to target SSP for treating human GBM.

PFKP is upregulated in 5-fluorouracil-resistant patients and suppresses the antitumor activity of 5-fluorouracil in colorectal cancer in vitro and in vivo

As a long-established chemotherapy drug, 5-fluorouracil (5-FU) is widely used to clinically manage colorectal cancer (CRC). However, a substantial portion of patients develop 5-FU resistance at some stage, which poses a great challenge. Therefore, revealing the mechanisms that could guide the development of effective strategies to overcome 5-FU resistance is required. Here, we report that the expression of PFKP was higher in HCT116/5-FU CRC. Furthermore, genetic suppression of PFKP suppresses glycolysis, NF-κB activation, and expression of GLUT1 and HK2 in HCT116/5-FU cells. PFKP overexpression promotes glycolysis and expression of GLUT1 and HK2 via the NF-κB signaling pathway in HCT116 cells. Our functional assays demonstrated that PFKP silencing could sensitize HCT116/5-FU cells to 5-FU with an elevated population of apoptotic cells. In contrast, forced expression of PFKP conferred 5-FU resistance in HCT116 cells. Furthermore, PFKP silencing significantly inhibited CRC xenograft tumor growth. Notably, the combination of PFKP silencing and 5-FU inhibited tumor growth. Therefore, our results demonstrated that PFKP enhances 5-FU resistance by promoting glycolysis, indicating that PFKP could be a novel candidate for targeted therapy for 5-FU-resistant CRC.

Correlation between preoperative systemic immune inflammation index, nutritional risk index, and prognosis of radical resection of liver cancer

BACKGROUND

Radical surgery is the most commonly used treatment for hepatocellular carcinoma (HCC). However, the surgical effect remains not ideal, and prognostic evaluation is insufficient. Furthermore, clinical intervention is rife with uncertainty and not conducive to prolonging patient survival.

AIM

To explore correlations between the systemic immune inflammatory index (SII) and geriatric nutritional risk index (GNRI) and HCC operation prognosis.

METHODS

This retrospective study included and collected follow up data from 100 HCC. Kaplan-Meier survival curves were used to analyze the correlation between SII and GNRI scores and survival. SII and GNRI were calculated as follows: SII = neutrophil count × platelet count/lymphocyte count; GNRI = [1.489 × albumin (g/L) + 41.7 × actual weight/ideal weight]. We analyzed the predictive efficacy of the SII and GNRI in HCC patients using receiver operating characteristic (ROC) curves, and the relationships between the SII, GNRI, and survival rate using Kaplan-Meier survival curves. Cox regression analysis was utilized to analyze independent risk factors influencing prognosis.

RESULTS

After 1 year of follow-up, 24 patients died and 76 survived. The area under the curve (AUC), sensitivity, specificity, and the optimal cutoff value of SII were 0.728 (95% confidence interval: 0.600-0.856), 79.2%, 63.2%, and 309.14, respectively. According to ROC curve analysis results for predicting postoperative death in HCC patients, the AUC of SII and GNRI combination was higher than that of SII or GNRI alone, and SII was higher than that of GNRI (P < 0.05). The proportion of advanced differentiated tumors, tumor maximum diameter (5-10 cm, > 10 cm), lymph node metastasis, and TNM stage III-IV in patients with SII > 309.14 was higher than that in patients with SII ≤ 309.14 (P < 0.05). The proportion of patients aged > 70 years was higher in patients with GNRI ≤ 98 than that in patients with GNRI > 98 (P < 0.05). The 1-year survival rate of the SII > 309.14 group (compared with the SII ≤ 309.14 group) and GNRI ≤ 98 group (compared with the GNRI > 98 group) was lower (P < 0.05).

CONCLUSION

The prognosis after radical resection of HCC is related to the SII and GNRI and poor in high SII or low GNRI patients.