Explore the vast range of titles available.

Gastric cancer (GC) is one of the most common malignant tumors and a leading cause of cancer-related death worldwide. Although advances in surgical techniques and novel treatment techniques such as immunotherapy have improved the prognosis of many tumors, the effectiveness of treatment for advanced GC patients is still limited. Immunohistochemistry (IHC) staining analysis was conducted to compare the expression of ALDOA and ENO1 in GC tissues and adjacent normal tissues, complemented by bioinformatics analysis using GEPIA, LinkedOmics, and TIMER databases to explore their association with glycolysis and immune cell infiltration. A survival prediction nomogram was constructed based on Cox proportional hazard model data to evaluate prognostic significance. In this study, through IHC staining analysis, it was observed that the expression levels of ALDOA and ENO1 in GC tissues were significantly higher than those in adjacent normal tissues. Moreover, the aberrant expression of ALDOA/ENO1 was associated with a poor prognosis in GC patients. Bioinformatics analysis revealed a positive correlation between ALDOA and ENO1 expression, both intricately associated with glycolysis pathway activation. A survival prediction nomogram, constructed based on the univariate analysis of data from the Cox proportional hazard model, demonstrated that the expression of ALDOA and ENO1 significantly impacts the prognosis of GC patients. ALDOA/ENO1 may play a crucial role in GC, which may potentially offer new perspectives and directions for the development of targeted therapies specifically designed for GC patients.

Identify the hypoxia genes related to chemotherapy resistance of oral cancer, and construct a chemotherapy response model by machine learning algorithm. 72 oral cancer patients with complete chemotherapy records and chemotherapy reactions were screened from the Cancer Genome Atlas (TCGA) database. According to the chemotherapy reactions, they were divided into chemotherapy sensitive group and chemotherapy resistant group. The differential genes were screened by Limma package. Then the chemotherapy response gene were screened by univariate analysis. Based on the gene expression profile of chemotherapy response, four machine learning algorithms were used to construct the prediction model of chemotherapy response. The core genes were screened by lasso regression analysis. Finally, the prognosis and immune infiltration of the core genes were analyzed. The results were verified by immunohistochemistry (IHC). We obtained 22 hypoxia related differential genes. Univariate analysis found 6 Chemotherapy response genes. Machine learning algorithms show that XGBoost have the best predictive performance for chemotherapy response. ALDOA is the core gene of chemotherapy resistance. Successfully constructed a chemotherapy prediction model for oral cancer by machine learning algorithm. Under hypoxia, the high expression of ALDOA is associated with chemotherapy resistance in oral cancer.

Colorectal cancer (CRC) is one of the most common malignant tumors of the digestive tract and a leading cause of cancer-related death worldwide. Since many CRC patients are diagnosed already in the advanced stage, and traditional chemoradiotherapy is prone to drug resistance, it is important to find new therapeutic targets. In this study, the expression levels of ALDOA and p-AKT were detected in cancer tissues and paired normal tissues, and it was found that they were significantly increased in CRC tissues, and their high expression indicated poor prognosis. Moreover, a positive correlation between the expression of ALDOA and p-AKT was found in CRC tissues and paired normal tissues. In addition, the Kaplan–Meier analysis revealed that the group with both negative of ALDOA/p-AKT expression had longer five-year survival rates compared with the other group. Besides, the group with both high expression of ALDOA/p-AKT had a worse prognosis compared with the other group. Based on the expression of ALDOA and p-AKT in tumor tissues, we can effectively distinguish tumor tissues from normal tissues through cluster analysis. Furthermore, we constructed nomograms to predict 3-year and 5-year overall survival, showing that the expression of ALDOA/p-AKT plays a crucial role in predicting the prognosis of CRC patients. Therefore, ALDOA/p-AKT may act as a crucial role in CRC, which may provide new horizons for targeted therapies for CRC.

Background Glioma is one of the most aggressive malignant brain tumors that is characterized with inevitably infiltrative growth and poor prognosis. ARST is a novel lncRNA whose expression level is significantly decreased in the patients with glioblastoma multiforme. However, the exact mechanisms of ARST in gliomagenesis are largely unknown. Methods The expressions of ARST in the glioma samples and cell lines were analyzed by qRT-PCR. FISH was utilized to detect the distribution of ARST in the glioma cells. CCK-8, EdU and flow cytometry were used to examine cellular viability, proliferation and apoptosis. Transwell and wound-healing assays were performed to determine the migratory and invasive abilities of the cells. Intracranial tumorigenesis models were established to explore the roles of ARST in vivo. RNA pulldown assay was used to examine proteins that bound to ARST. The activities of key enzymes in the glycolysis and production of lactate acid were measured by colorimetry. In addition, RIP, Co-IP, western blot and immunofluorescence were used to investigate the interaction and regulation between ARST, F-actin, ALDOA and cofilin. Results In this study, we reported that ARST was downregulated in the gliomas. Overexpression of ARST in the glioma cells significantly suppressed various cellular vital abilities such as cell growth, proliferation, migration and invasion. The tumorigenic capacity of these cells in vivo was reduced as well. We further demonstrated that the tumor suppressive effects of ARST could be mediated by a direct binding to a glycolytic enzyme aldolase A (ALDOA), which together with cofilin, keeping the polymerization and depolymerization of actin filaments in an orderly dynamic equilibrium. Upregulation of ARST interrupted the interaction between ALDOA and actin cytoskeleton, which led to a rapid cofilin-dependent loss of F-actin stress fibers. Conclusions Taken together, it is concluded that ARST performs its function via a non-metabolic pathway associated with ALDOA, which otherwise modifies the morphology and invasive properties of the glioma cells. This has added new perspective to its role in tumorigenesis, thus providing potential target for glioma diagnosis, therapy, and prognosis.

Amyotrophic lateral sclerosis (ALS) is characterized by progressive motor neuron degeneration. Glycolytic dysregulation is implicated in disease progression, yet the underlying mechanisms remain unclear. This study investigates how Aldolase A (ALDOA) drives ALS progression through glycolysis-mediated motor neuron pyroptosis. In vivo, tamoxifen-induced TDP-43 cKO mice were assessed for motor function (rotarod/suspension tests), motor cortex L-lactic acid, and ALDOA/NLRP3/GSDMD expression. The ALDOA inhibitor Aldometanib was administered. In vitro, TDP-43 KO NSC34 cells were used to measure viability, glucose uptake, and L-lactic acid. ALS model mice exhibited significant motor deficits, progressive weight loss, and reduced survival. Their motor cortex showed elevated ALDOA expression, L-lactic acid accumulation, and NLRP3/GSDMD inflammasome activation. Aldometanib treatment suppressed glycolysis, prolonged survival, and slowed disease progression by inhibiting NLRP3/GSDMD-mediated pyroptosis. In vitro, TDP-43-deficient NSC34 cells displayed increased ALDOA levels, enhanced glycolytic flux, NLRP3/GSDMD pathway activation, and impaired proliferation. We show that ALDOA-mediated glycolytic dysregulation activates the NLRP3/GSDMD inflammasome, leading to pyroptosis in motor neurons. Pharmacological inhibition of ALDOA alleviates glycolytic dysregulation and extends survival, identifying ALDOA as a potential therapeutic target.

ALDOA-related specific transcript (ARST) is a recently identified long non-coding RNA (lncRNA) that suppresses glioma progression, while its role in other cancers is unclear. This study explored the role of ARST in colorectal cancer (CRC). The present study included 60 CRC patients, 60 patients with colon polyps (CP), 60 colitis patients, 60 hemorrhoid patients and 60 healthy controls. All participants were subjected to the collection of plasma, and paired CRC and non-tumor tissues were collected from CRC patients. All samples were subjected to RNA isolation and RT-qPCR to detect the expression of ARST. ROC curve and survival curve analysis were performed to evaluate the diagnostic and prognostic values of plasma ARST for CRC. The expression levels of ARST were lower in CRC plasma samples compared to that in the patient groups and controls ( < 0.01), while other patient groups and controls showed no significant difference. The expression levels of ARST were also lower in CRC tissues compared to that in non-tumor tissues ( < 0.01). Plasma expression levels of ARST effectively distinguished CRC patients from other patients and controls. The expression levels of ARST were closely correlated with patients' survival. Chi-squared test analysis showed that ARST was closely associated with patients' distant metastasis but not tumor size. ARST is downregulated in CRC, and it might be applied in the diagnosis and prognosis of CRC.

Background Aldolase A (ALDOA), a key glycolytic enzyme, has been implicated in tumor progression and metabolic reprogramming across multiple cancers [ 1 ]. However, its role in lung squamous cell carcinoma (LUSC) remains largely unexplored. Recent studies suggest that ALDOA may influence the tumor immune microenvironment, particularly through its association with macrophages [ 2 , 3 ]. This study aims to investigate the prognostic value of ALDOA in LUSC and its role in macrophage-mediated immune suppression. Methods We conducted a comprehensive pan-cancer analysis to evaluate ALDOA expression, genomic alterations, and prognostic relevance across different cancer types. In LUSC, we validated its prognostic value using immunohistochemical (IHC) staining and independent patient cohorts. Immune infiltration was assessed using multiple bioinformatics algorithms and single-cell RNA sequencing (scRNA-seq) from the TISCH2 database. Spatial transcriptomics and immunofluorescence (IF) staining were performed to determine ALDOA’s co-localization with CD68 + macrophages in LUSC tissues. Functional enrichment and drug sensitivity analyses were conducted to explore ALDOA’s role in tumor progression and therapeutic resistance. Results ALDOA was significantly overexpressed in multiple cancers, with LUSC showing one of the highest expression levels. Elevated ALDOA expression was strongly correlated with poor overall survival (OS), disease-specific survival (DSS), and progression-free interval (PFI) in LUSC patients. Copy number variations and promoter hypomethylation were identified as potential mechanisms driving ALDOA overexpression. ALDOA-high tumors exhibited increased M0 macrophage and reduced CD8 + T-cell infiltration, suggesting a role in immune suppression and evasion. Spatial transcriptomic and immunofluorescence analyses confirmed the co-localization of ALDOA with CD68 + tumor-associated macrophages (TAMs). Additionally, ALDOA-high tumors demonstrated increased resistance to multiple chemotherapeutic agents and EGFR-TKIs, highlighting its potential as a predictive biomarker for drug response. Conclusion Our findings establish ALDOA as a robust prognostic biomarker and a key regulator of macrophage-mediated immune suppression in LUSC. Its involvement in tumor metabolism, immune evasion, and therapy resistance suggests that targeting ALDOA could enhance both metabolic inhibition strategies and immune checkpoint blockade therapies. Future research should focus on mechanistic studies and therapeutic interventions targeting ALDOA to improve treatment outcomes in LUSC.

The mean survival of metastatic lung adenocarcinoma is less than 1 year, highlighting the urgent need to understand the mechanisms underlying its high mortality rate. The role of Extracellular vesicles (EVs) in facilitating the interactions between cancer cells and the metastatic microenvironment has garnered increasing attention. Previous studies on the role of EVs in metastasis have been primarily focused on cancer cell-derived EVs in modulating the functions of stromal cells. However, whether cancer stem cells (CSCs) can alter the metastatic properties of non-CSC cells, and whether EV crosstalk can mediate such interaction, have not been demonstrated prior to this report. In the present study, we integrated multi-omics sequencing and public database analysis with experimental validation to demonstrate, for the first time, the exosomal Mir100hg, derived from CSCs, could enhance the metastatic potential of non-CSCs both in vitro and in vivo. Mechanistically, HNRNPF and HNRNPA2B1 directly binds to Mir100hg, facilitating its trafficking via exosomes to non-CSCs. In non-CSCs, Mir100hg upregulates ALDOA expression, subsequently leading to elevated lactate production. Consequently, the increased lactate levels enhance H3K14 lactylation by 2.5-fold and promote the transcription of 169 metastasis-related genes. This cascade of events ultimately results in enhanced ALDOA-driven glycolysis and histone lactylation-mediated metastatic potential of non-CSC lung cancer cells. We have delineated a complex regulatory network utilized by CSCs to transfer their high metastatic activity to non-CSCs through exosomal Mir100hg, providing new mechanistic insights into the communication between these two heterogeneous tumor cell populations. These mechanistic insights provide novel therapeutic targets for metastatic lung cancer, including HNRNPF/HNRNPA2B1-mediated Mir100hg trafficking and the histone lactylation pathway, advancing our understanding of CSC-mediated metastasis while suggesting promising strategies for clinical intervention. Graphical Abstract

Several malignant tumors have been shown to overexpress aldolase A (ALDOA), a crucial enzyme in the glycolytic cycle. Though, it is still unknown how ALDOA contributes to breast cancer (BC). Using GEPIA, TIMER, UALCAN, BC-GenExMiner v5.1 database, and immunohistochemistry on 96 BC patients, the expression of ALDOA was investigated. The correlation between ALDOA expression and the prognosis was evaluated by employing the Kaplan-Meier (KM) plotter in breast cancer patients. The expression of ALDOA mRNA was higher in BC compared to the normal tissues. Certain subtypes of BC showed higher ALDOA expression, including micropapillary, luminal B, non-basal-like, non-triple negative breast cancer (TNBC), and luminal androgen receptor (LAR). Overexpression of ALDOA was related to the presence of lymph node metastasis (LNM), older age, high Ki67 expression, estrogen receptor (ER) and progesterone receptor (PR) positivity, and advanced Scarff-Bloom-Richardson (SBR) and Nottingham Prognostic Index (NPI) grades, while decreased ALDOA mRNA levels were observed in TNBC and basal-like BC. KM plotter showed that higher ALDOA mRNA levels predicted worse overall survival (OS), relapse-free survival (RFS), and distant metastasis-free survival (DMFS) overall. However, in BC patients with LNM, higher ALDOA levels correlated to better DMFS. ALDOA was a crucial prognostic factor required for BC advancement, indicating a possible target for BC treatment.