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PubMed2026

FZD5 drives macrophage-mediated immunomodulation and predicts prognosis in glioma: evidence from single-cell sequencing.

BACKGROUND: Gliomas are highly malignant brain tumors characterized by an immunosuppressive microenvironment, which limits therapeutic efficacy and contributes to poor clinical outcomes. The WNT/β-catenin signaling pathway is critically involved in tumor progression, and FZD5, a key receptor within this pathway, may participate in immune regulation. However, its specific role and underlying mechanisms in glioma remain unclear. METHODS: RNA-seq and microarray datasets from the Chinese Glioma Genome Atlas (CGGA) and The Cancer Genome Atlas (TCGA), together with single-cell RNA sequencing (scRNA-seq) datasets from GEO, were comprehensively analyzed. The Seurat package was used to identify macrophage-related clusters and mitophagy-associated pathways. Cox and LASSO regression analyses, along with a prognostic nomogram, were applied to evaluate the prognostic significance of FZD5. Immune infiltration, functional enrichment, and immunotherapy response analyses were conducted, followed by validation using spatial transcriptomics, immunohistochemistry, and in vitro assays. RESULTS: In bulk glioma transcriptomes, FZD5 emerged as an independent predictor of poor prognosis. Crucially, single-cell and spatial analyses revealed that the biologically significant FZD5 signal originated predominantly within tumor-associated macrophages (TAMs), where it colocalized with the M2 marker CD163. Consistently, elevated FZD5 levels correlated with increased myeloid infiltration and an immunosuppressive tumor microenvironment. Functionally, macrophage-expressed FZD5 was associated with mitophagy-related programs and promoted an M2-skewed phenotype, thereby enhancing glioma cell proliferation, migration, and invasion via macrophage-glioma crosstalk. CONCLUSION: FZD5 is a TAM-enriched marker in glioma tissues and a potential regulator of macrophage-associated immunosuppressive programs, supporting its utility as a prognostic biomarker and a candidate target for microenvironment-oriented interventions in glioma.

Humans↗

PubMed2025

Lactate dehydrogenase a is a crucial biomarker that affects the prognosis, chemotherapy effect, and immune infiltration of breast cancer.

PURPOSE: Lactate dehydrogenase A (LDHA) is a key node in tumor growth, metabolism, and invasion and is upregulated across multiple cancers. However, the molecular mechanisms by which LDHA influences breast cancer (BC) remain unclear. We analyzed public datasets and an institutional cohort to clarify the relationship between LDHA and BC, with the aim of informing future therapeutic strategies. PATIENTS AND METHODS: Using The Cancer Genome Atlas (TCGA), we assessed LDHA expression in BC and examined its associations with tumor mutational burden (TMB), immune cell infiltration, immune checkpoint molecules, and drug sensitivity. We integrated multiple databases and used Kaplan-Meier analyses to evaluate prognostic value. To explore biological functions of LDHA, we performed Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), and Gene Set Enrichment Analysis (GSEA). We then analyzed BC patients receiving neoadjuvant chemotherapy (NAC) at Harbin Medical University Cancer Hospital to test the relationship between serum lactate dehydrogenase (LDH) and pathological complete response (pCR). Finally, we used National Health and Nutrition Examination Survey (NHANES) data to examine the association between serum LDH and mortality. RESULTS: LDHA was upregulated in BC tissues, and higher expression was significantly associated with worse overall survival (OS), recurrence-free survival (RFS), and distant metastasis-free survival (DMFS). Functional analyses indicated enrichment of metabolic pathways, such as glycolysis. LDHA expression correlated with multiple immune cell populations, suggesting involvement in the tumor immune microenvironment. Lower LDHA expression was associated with greater sensitivity to several chemotherapeutic agents. In our institutional cohort, patients with lower serum LDH were more likely to achieve pCR, and LDH was an independent predictor of pCR. In NHANES, elevated serum LDH was linked to increased mortality risk. CONCLUSION: Our findings suggest that LDHA expression and serum LDH levels are promising prognostic biomarkers for survival and may predict chemotherapy response in BC patients. These results highlight the clinical relevance of LDHA-mediated metabolic pathways. However, as a correlational study, our findings warrant further validation through functional experiments to confirm LDHA's role as a potential therapeutic target.

Humans↗

PubMed2026

The use of 3-dimensional (3D) printing in teaching musculoskeletal oncology for medical undergraduates.

INTRODUCTION: The approach to integrating relevant anatomy in the medical curriculum has been debated for many years. Current literature has explored the broad impact of 3D printing in medical education. However, there is little evidence on 3D printing for the teaching of musculoskeletal oncology (MSO). This is a self-controlled case series (SCCS) study that aims to analyse the effectiveness of 3D printed models in MSO in enhancing the learning experience, engagement and understanding of clinical and surgical anatomy for medical students. METHOD: A cross-sectional cohort study involving 75 clinical year medical students across 3 years from 2 medical schools that rotated through a single teaching hospital's orthopaedic department. Participants first viewed a set of computed-tomography (CT) images of a large pelvic osteosarcoma from a free open-source database, the Cancer Genome Atlas Sarcoma Collection (TCGA-SARC). A standardised 10-minute pre-intervention questionnaire which comprised 15 questions categorised by: 4 questions in 'anatomical knowledge', 7 questions in 'spatial awareness', 4 questions in 'surgical planning and complications', was administered to assess the baseline knowledge in their interpretation of the pathology via CT images only. Next, a 3D-printed model of the pelvic osteosarcoma, which included colour-coded adjacent structures, was provided as an adjunct to answer the same questionnaire. This concluded with a 5-point Likert scale feedback survey to gauge their perspectives and experience. RESULTS: The mean scores comparing their pre- and post-intervention assessment questionnaire increased by +1.34 from 8.15 (SD = 1.85) to 9.49 (SD = 1.7) (p < 0.001). The final year students had the greatest improvement of +1.54 from 8.00 (SD = 1.89) to 9.54 (SD = 1.59) (p = 0.004). There was no significant difference between the scores amongst the 2 medical schools. 91% of students agreed that the 3D model had helped them further their understanding of the anatomy of the sarcoma and 87% would want 3D printing models to augment their learning in anatomy. Baseline weaker students demonstrated significantly greater improvement in scores compared with baseline stronger students (mean difference +2.04 vs +0.30, p < 0.001). CONCLUSION: 3D printing is an effective teaching adjunct for musculoskeletal oncology surgical anatomy for medical undergraduates and could be used to enhance their understanding and learning experience. 3D models could be integrated in the teaching curriculum of surgical anatomy for undergraduate students.

Humans↗

PubMed2024

Stemness related lncRNAs signature for the prognosis and tumor immune microenvironment of ccRCC patients.

Long non-coding RNAs (lncRNAs) and cancer stem cells (CSCs) are crucial for the growth, migration, recurrence, and medication resistance of tumors. However, the impact of lncRNAs related to stemness on the outcome and tumor immune microenvironment (TIME) in clear cell renal cell carcinoma (ccRCC) is still unclear. In this study, we aimed to predict the outcome and TIME of ccRCC by constructing a stem related lncRNAs (SRlncRNAs) signature. We firstly downloaded ccRCC patients' clinical data and RNA sequencing data from UCSC and TCGA databases, and abtained the differentially expressed lncRNAs highly correlated with stem index in ccRCC through gene expression differential analysis and Pearson correlation analysis. Then, we selected suitable SRlncRNAs for constructing a prognostic signature of ccRCC patients by LASSO Cox regression. Further, we used nomogram and Kaplan Meier curves to evaluate the SRlncRNA signature for the prognose in ccRCC. At last, we used ssGSEA and GSVA to evaluate the correlation between the SRlncRNAs signature and TIME in ccRCC. Finally, We obtained a signtaure based on six SRlncRNAs, which are correlated with TIME and can effectively predict the ccRCC patients' prognosis. The SRlncRNAs signature may be a noval prognostic indicator in ccRCC.

Humans↗

PubMed2024

Exploring the prognostic landscape of oral squamous cell carcinoma through mitochondrial damage-related genes.

Oral squamous cell carcinoma (OSCC), the most prevalent form of oral cancer, poses significant challenges to the medical community due to its high recurrence rate and low survival rate. Mitochondrial Damage-Related Genes (MDGs) have been closely associated with the occurrence, metastasis, and progression of OSCC. Consequently, we constructed a prognostic model for OSCC based on MDGs and identified potential mitochondrial damage-related biomarkers. Gene expression profiles and relevant clinical information were obtained from The Cancer Genome Atlas (TCGA) database. Differential analysis was conducted to identify MDGs associated with OSCC. COX analysis was employed to screen seven prognosis-related MDGs and build a prognostic prediction model for OSCC. Cases were categorized into low-risk or high-risk groups based on the optimal risk score threshold. Kaplan-Meier (KM) analysis revealed significant survival differences (P < 0.05). Additionally, the area under the ROC curve (AUC) for patient survival at 1 year, 3 years, and 5 years were 0.687, 0.704, and 0.70, respectively, indicating a high long-term predictive accuracy of the prognostic model. To enhance predictive accuracy, age, gender, risk score, and TN staging were incorporated into a nomogram and verified using calibration curves. Risk scoring based on MDGs was identified as a potential independent prognostic biomarker. Furthermore, BID and SLC25A20 were identified as two potential independent mitochondrial damage-related prognostic biomarkers, offering new therapeutic targets for OSCC.

Humans↗

PubMed2024

Construction of an immunogenic cell death-related LncRNA signature to predict the prognosis of patients with lung adenocarcinoma.

BACKGROUND: Lung adenocarcinoma (LUAD) is one of the most common malignant diseases worldwide. This study aimed to construct an immunogenic cell death (ICD)-related long non-coding RNA (lncRNA) signature to effectively predict the prognosis of LUAD. METHODS: The RNA-sequencing and clinical data of LUAD were downloaded from The Cancer Genome Atlas (TCGA). Least absolute shrinkage and selection operator (LASSO) and stepwise multivariate Cox proportional hazard regression analysis were utilized to construct lncRNA signature. Then, the reliability of the signature was evaluated in the training, validation and whole cohorts. The differences in the immune landscape and drug sensitivity between the low- and high-risk groups were analyzed. Finally, the expression level of the selected ICD-related lncRNAs in LUAD cell lines via reverse transcription quantitative PCR (RT-qPCR). CCK-8 and transwell assays were performed to study biological function of AC245014.3. RESULTS: A signature consisting of 5 ICD-related lncRNAs was constructed. Kaplan Meier (K-M) survival analysis showed shorter overall survival (OS) in high-risk group. The receiver operating characteristic (ROC) curves and Multivariate Cox regression analysis showed the signature was good predictive and independent prognostic factor in LUAD. Moreover, the high-risk group had a lower level of antitumor immunity and was less sensitive to some chemotherapeutics and targeted drugs. Finally, the expression level of selected ICD-related lncRNAs was validated in LUAD cell lines by RT-qPCR. Knockdown of AC245014.3 significantly suppressed LUAD proliferation, migration and invasion. CONCLUSIONS: In this study, an ICD-related lncRNA signature was constructed, which could accurately predict the prognosis of LUAD patients and guide clinical treatment.

Humans↗

PubMed2025

Construction of a prognostic model for gastric cancer based on immune infiltration and microenvironment, and exploration of MEF2C gene function.

BACKGROUND: Advanced gastric cancer (GC) exhibits a high recurrence rate and a dismal prognosis. Myocyte enhancer factor 2c (MEF2C) was found to contribute to the development of various types of cancer. Therefore, our aim is to develop a prognostic model that predicts the prognosis of GC patients and initially explore the role of MEF2C in immunotherapy for GC. METHODS: Transcriptome sequence data of GC was obtained from The Cancer Genome Atlas (TCGA), the Gene Expression Omnibus (GEO) and PRJEB25780 cohort for subsequent immune infiltration analysis, immune microenvironment analysis, consensus clustering analysis and feature selection for definition and classification of gene M and N. Principal component analysis (PCA) modeling was performed based on gene M and N for the calculation of immune checkpoint inhibitor (ICI) Score. Then, a Nomogram was constructed and evaluated for predicting the prognosis of GC patients, based on univariate and multivariate Cox regression. Functional enrichment analysis was performed to initially investigate the potential biological mechanisms. Through Genomics of Drug Sensitivity in Cancer (GDSC) dataset, the estimated IC50 values of several chemotherapeutic drugs were calculated. Tumor-related transcription factors (TFs) were retrieved from the Cistrome Cancer database and utilized our model to screen these TFs, and weighted correlation network analysis (WGCNA) was performed to identify transcription factors strongly associated with immunotherapy in GC. Finally, 10 patients with advanced GC were enrolled from Sun Yat-sen University Cancer Center, including paired tumor tissues, paracancerous tissues and peritoneal metastases, for preparing sequencing library, in order to perform external validation. RESULTS: Lower ICI Score was correlated with improved prognosis in both the training and validation cohorts. First, lower mutant-allele tumor heterogeneity (MATH) was associated with lower ICI Score, and those GC patients with lower MATH and lower ICI Score had the best prognosis. Second, regardless of the T or N staging, the low ICI Score group had significantly higher overall survival (OS) compared to the high ICI Score group. For its mechanisms, consistently, for Camptothecin, Doxorubicin, Mitomycin, Docetaxel, Cisplatin, Vinblastine, Sorafenib and Paclitaxel, all of the IC50 values were significantly lower in the low ICI Score group compared to the high ICI Score group. As a result, based on univariate and multivariate Cox regression, ICI Score was considered to be an independent prognostic factor for GC. And our Nomogram showed good agreement between predicted and actual probabilities. Based on CIBERSORT deconvolution analysis, there was difference of immune cell composition found between high and low ICI Score groups, probably affecting the efficacy of immunotherapy. Then, MEF2C, a tumor-related transcription factor, was screened out by WGCNA analysis. Higher MEF2C expression is significantly correlated with a worse OS. Moreover, its higher expression is also negatively correlated with tumor mutation burden (TMB) and microsatellite instability (MSI), but positively correlated with several immunosuppressive molecules, indicating MEF2C may exert its influence on tumor development by upregulating immunosuppressive molecules. Finally, based on transcriptome sequencing data on 10 paired tumor tissues from Sun Yat-sen University Cancer Center, MEF2C expression was significantly lower in paracancerous tissues compared to tumor tissues and peritoneal metastases, and it was also lower in tumor tissues compared to peritoneal metastases, indicating a potential positive association between MEF2C expression and tumor invasiveness. CONCLUSIONS: Our prognostic model can effectively predict outcomes and facilitate stratification GC patients, offering valuable insights for clinical decision-making. The identified transcription factor MEF2C can serve as a biomarker for assessing the efficacy of immunotherapy for GC.

Humans↗

PubMed2025

Comprehensive pan-cancer analysis of HSPG2 as a marker for prognosis.

BACKGROUND: In recent years, several studies have shown that HSPG2 is associated with the prognosis of specific cancers. The aim of this study was to investigate the prognostic value of HSPG2 in pan-cancer and to analyze its possible mechanisms. METHODS: We used The Cancer Genome Atlas (TCGA) and Genotype-Tissue Expression (GTEx) to explore the expression of HSPG2 in 33 tumors and corresponding controls. Univariate Cox regression and Kaplan-Meier survival analysis were applied to detect the effects of HSPG2 on overall survival (OS), disease-specific survival (DSS), and progression-free interval (PFI) in patients with these tumors, and to analyze the relationship between HSPG2 and clinical characteristics. And we further analyzed the relationship between HSPG2 and immune infiltration, DNA methylation and single cell function. And GO and KEGG enrichment analyses were performed using HSPG2 co-expressed genes. Finally, we explored the diagnostic efficacy of HSPG2 for diseases of interest and validated it using qPCR experiment. RESULTS: HSPG2 was lowly expressed in 17 cancers and highly expressed in 11 cancers, and was correlated with patient's clinical characteristics in many cancers. Multivariate regression analysis showed that HSPG2 was an independent prognostic factor for DSS, OS, and PFI in bladder urothelial carcinoma (BLCA) and Mesothelioma (MESO). HSPG2 was correlated with DNA methylation, single-cell function, and immune infiltration in a variety of cancers. HSPG2 exhibited a good diagnostic efficacy for BLCA and MESO. qPCR and western blot results showed that HSPG2 expression was increased in mesothelioma compared to normal controls. CONCLUSION: These findings suggest that HSPG2 could be considered as a potential diagnostic and prognostic marker for BLCA and MESO.

Humans↗

PubMed2025

Putative function and prognostic molecular marker of mast cells in colorectal cancer.

BACKGROUND: The increased demand for markers for colorectal cancer (CRC) highlights the importance of investigating immune cells involved in CRC progression. This study aims to dissect the mast cells in CRC, characterize the role of mast cells in CRC development, coordinate molecular communication between mast cells and malignant cells, and construct and validate a prognostic classification model based on mast cell markers. METHODS: Single-cell transcriptome data of CRC patients were extracted from GSE146771 for cell classification and annotation. The malignant cells were identified by copykat and the communication between mast cells and malignant cells was analyzed by CellChat. Least absolute shrinkage and selection operator (LASSO) regression analysis and Cox regression analysis of mast cell markers were performed in the TCGA-COAD cohort to construct a prognostic classification model. qRT-PCR was performed to detect the mRNA expression of the molecules in the classification model in P815 and MC-9 cells. The co-culture experiment of MC38 and P815 cells were performed in 12-well transwell dish. Wound healing assay and Transwell assay were performed to detect cell migration and invasion. RESULTS: 10,186 high-quality cells in GSE146771 were annotated to 9 cell types. Six markers in mast cells (HDC, GATA2, ASAH1, BTBD19, TIMP1, FAM110A) were selected to construct a classification model. The high-risk score defined showed high infiltration of immunosuppressive cells, including endothelial cells, CAFs, Tregs and high angiogenesis and epithelial-mesenchymal transition (EMT) activities. In the model, HDC were abnormally low expressed in P815 cells, while BTBD19, FAM110A, GATA2, ASAH1 and TIMP1 showed excessive expression in P815 cells. Knockdown of GATA2 in the co-culture system of P815 and MC38 cells blocked cell migration and invasion. CONCLUSION: This study identified the cell types within CRC, elaborated the cellular functions of mast cells in CRC development and their molecular communication to coordinate malignant cells, and highlighted the molecular components and biological features that constitute promising prognostic classification model.

Mast Cells↗

PubMed2025

CCT8 drives colorectal cancer progression via the RPL4-MDM2-p53 axis and immune modulation.

PURPOSE: Colorectal cancer (CRC) ranks high in global mortality, emphasizing the need for effective interventions. The aim of the research is to elucidate the oncogenic role of CCT8 in CRC and its interaction with RPL4 in the RPL4-MDM2-p53 axis. METHODS: TIMER 2.0, TCGA, and GTEx databases were used to analyze CCT8 expression patterns in CRC. Immunohistochemistry was performed to examine CCT8 distribution in CRC tissues and adjacent non-tumor tissues. Functional assays, including CCK-8, transwell, wound-healing, and flow cytometry, were conducted using DLD-1 and HCT116 cell lines to assess the effects of CCT8 on cell proliferation, migration, invasion, and apoptosis. Gene set enrichment analysis, protein-protein interaction network analysis, and co-immunoprecipitation were performed to explore the interaction between CCT8 and RPL4 and their role in the RPL4-MDM2-p53 pathway. Additionally, gene set variation analysis was applied to investigate the relationship between CCT8/RPL4 expression and immune infiltration patterns in CRC. RESULTS: CCT8 was significantly upregulated in CRC and associated with tumor progression. Mechanistically, CCT8 potentially synergizes with RPL4 concluded from their positive correlation and similar immune infiltration patterns, influencing the RPL4-MDM2-p53 axis and contributing to p53 ubiquitination and degradation. CONCLUSION: These findings underscore the oncogenic significance of CCT8 in CRC and shed light on its molecular mechanisms, paving the way for potential therapeutic applications.

Humans↗

PubMed2025

Transcriptomics-based exploration of ubiquitination-related biomarkers and potential molecular mechanisms in laryngeal squamous cell carcinoma.

BACKGROUND: One of the most common and prevalent cancers is laryngeal squamous cell carcinoma (LSCC), which poses a great threat to the life and health of the patient. Nonetheless, it has been demonstrated that ubiquitination is crucial for the development and course of LSCC. Therefore, it is particularly important to identify biomarkers for ubiquitination-related genes (UbRGs) in LSCC. METHODS: Differentially expressed genes (DEGs) in the LSCC versus controls were obtained by differential expression analysis. Also, key modular genes associated with LSCC were obtained using weighted gene co-expression network analysis (WGCNA). Next, DEGs, key module genes, and UbRGs were taken to intersect to obtain candidate genes. And then machine algorithms were to screen potential biomarkers, further their diagnostic value were analyzed and validated. Then, therapeutic agents for biomarkers were predict. In addition, the regulatory networks of the biomarkers were mapped. The expression levels of biomarkers were detected in clinical samples using reverse transcription-quantitative PCR (RT-qPCR). RESULTS: A total of eight candidate genes were acquired by the overlap 1,911 DEGs, the key modular genes of WGCNA, and 1,393 UbRGs. A sum of four biomarkers (WDR54, KAT2B, NBEAL2 and LNX1) were identified by two machine learning, then these four biomarkers were validated in GSE127165 and the expression trend was consistent with TCGA-LSCC, they were recorded as biomarkers. Moreover, the accuracy of the biomarkers in predicting clinical aspects of LSCC was confirmed by the receiver operating characteristic (ROC) curves. Subsequently, cancers such as malignant neoplasms, colorectal cancers, tumors, and primary malignant neoplasms were significantly associated with the biomarkers, which further suggests that these four biomarkers were strongly associated with cancer. Meanwhile, the drugs garcinol, cocaine, and triazolam, among others, used for LSCC treatment were predicted. Finally, transcription factors (TFs) (BRD4, MYC, AR, and CTCF) were predicted to regulate the biomarkers. RT-qPCR assays illustrated that the expression trends of KAT2B, LNX1 and NBEAL2 remained consistent with the dataset. CONCLUSION: The identification of four biomarkers (WDR54, KAT2B, NBEAL2 and LNX1) associated with UbRGs could ultimately serve as a predictive clinical diagnosis of LSCC and provide insight into the molecular mechanisms of LSCC.

Humans↗

PubMed2025

MicroRNA-486: a dual-function biomarker for diagnosis and tumor immune microenvironment characterization in non-small cell lung cancer.

BACKGROUND: This investigation evaluates the clinical significance and molecular mechanisms of microRNA-486 (miR-486) as a potential biomarker in non-small cell lung cancer (NSCLC) through an integrative analytical approach. METHODS: We conducted systematic search and meta-analysis of diagnostic studies from major biomedical databases from inception through April 04, 2025, followed by comprehensive bioinformatics interrogation. Protein-protein interaction (PPI) networks were constructed using STRING to identify key hub genes regulated by miR-486. Validation of hub genes employed TCGA datasets, while immune infiltration analysis utilized TIMER2.0 platform. RESULTS: The meta-analysis indicated that miR-486, both individually and in combination, could be effective biomarkers for NSCLC detection. Afterwards, functional enrichment analyses of miR-486 target genes highlighted significant ontology terms and pathways crucial to the initiation and progression of NSCLC. PPI networks revealed key proteins and modules that participate in multiple essential pathways associated with NSCLC pathogenesis. Furthermore, the identified hub genes were validated for differential expression in cancerous versus normal tissues, suggesting their potential diagnostic utility, while subsequent survival analyses confirmed their prognostic value through significant associations with overall survival. Notably, these hub genes were found to be significantly associated with immune infiltration levels, immune microenvironment scores, and immune-related proteins in NSCLC. CONCLUSIONS: This dual-modality investigation establishes miR-486 as a multi-functional biomarker in NSCLC, demonstrating both diagnostic utility and immunoregulatory potential through tumor microenvironment modulation.

Humans↗

PubMed2025

NR2F6 regulates Temozolomide resistance in glioma via the E2F2-PARP1 pathway.

BACKGROUND: Glioma is the most common primary malignant brain tumor in adults. Temozolomide (TMZ) represents a standard-of-care chemotherapeutic agent in glioblastoma (GBM). However, the development of drug resistance constitutes a significant hurdle in the treatment of malignant glioma. Elucidating the mechanisms of temozolomide (TMZ) resistance in glioma is of critical clinical importance for improving patient prognosis and developing novel therapeutic strategies. METHODS: We obtained RNA sequencing (RNA-seq) data of 648 glioma samples from The Cancer Genome Atlas (TCGA) and 325 samples from the Chinese Glioma Genome Atlas (CGGA) as study cohorts. Additionally, we validated the expression characteristics of the NR2F6 gene in our in-house cohort of glioma patients. Furthermore, we investigated the potential mechanism of NR2F6 in TMZ resistance in glioma by constructing TMZ-resistant cell lines in vitro. Statistical analyses and graphical work were primarily performed using R language and GraphPad Prism software. RESULTS: We observed a significant upregulation of NR2F6 expression in high-grade gliomas, which is associated with an unfavorable prognosis in patients. Concurrently, our findings revealed a significant upregulation of NR2F6 in drug-resistant cells, which induced TMZ resistance in glioma cells via the E2F2-PARP1 axis. CONCLUSION: In brief, NR2F6, as a nuclear transcription factor, enhances the transcription of E2F2.The increased expression of E2F2 enhances PARP1 expression, which in turn facilitates TMZ-mediated DNA damage repair, thereby diminishing glioma sensitivity to TMZ.

Journal Article↗

PubMed2025

Centromere protein I facilitates breast cancer tumorigenesis and disease progression through modulation of Wnt/β-Catenin signaling.

BACKGROUND: Breast cancer (BCa) is a major contributor to female mortality worldwide. Treatment resistance and tumor heterogeneity contribute to the lack of effective therapeutic targets, posing a significant challenge in BCa management. CENPI, a core centromere protein involved in chromosome segregation, has emerging evidence implicating it in oncogenesis across diverse malignancies. However, its functional and molecular mechanisms in BCa remain unclear. METHODS: We analyzed CENPI expression and its clinical significance by using the BCa dataset from the Cancer Genome Atlas (TCGA) and immunohistochemical staining of 3 human BCa tissue samples. Cellular functional assays and mice xenograft models were utilized to assess the effects of CENPI on BCa growth. RNA sequencing combined with bioinformatics analysis was conducted to elucidate the molecular mechanisms underlying CENPI function, with further validation through Western blotting, immunofluorescence, and TOP/FOP flash assays. RESULTS: CENPI was aberrantly overexpressed in BCa, with elevated expression levels strongly associated with disease progression and poor prognosis. Functional assays demonstrated that CENPI significantly promoted breast carcinogenesis in both cellular and animal models. Mechanistically, CENPI increased BCa progression and malignant phenotypes by modulating the Wnt/β-catenin axis. CONCLUSIONS: CENPI is a critical oncogene in BCa, driving tumorigenesis and disease progression via the Wnt/β-catenin axis, which represents a promising biomarker and therapeutic target for BCa.

Breast cancer↗

PubMed2026

TMEM33 regulates the proliferation and migration of lung adenocarcinoma by promoting the PI3K/AKT/mTOR signaling pathway.

Lung adenocarcinoma is a common type of lung cancer with high incidence and mortality rates. TMEM33, a tumor-associated protein, has not been fully elucidated in lung adenocarcinoma. To explore the expression of TMEM33 in lung adenocarcinoma, its impact on tumor progression, and its role in the PI3K/AKT/mTOR signaling pathway. Key genes associated with lung adenocarcinoma were screened using the Gene Expression Omnibus (GEO) dataset GSE140797 in combination with a weighted correlation network analysis (WGCNA). Gene Ontology (GO) functional enrichment and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses were performed on these key genes. TMEM33 expression in Lung adenocarcinoma patients was validated using data from the TCGA database. The directly interactive molecules were screened through a bioinformatics method. Cellular assays (Western Blot, CCK8, colony formation, scratch assay, Trans well assay) and a nude mouse model were used to investigate the effects of TMEM33 on cell proliferation, migration, and tumor growth. TMEM33 is highly expressed in lung adenocarcinoma tissues (P < 0.05) and associated with poor prognosis. Overexpression of TMEM33 promotes cell proliferation and migration, and activates the PI3K/AKT/mTOR signaling pathway (P < 0.01). In the nude mouse model, TMEM33 overexpression increases tumor volume (P < 0.001), and PI3K/AKT pathway inhibition suppresses these effects (P < 0.05, P < 0.01). TMEM33 acts as an oncogene in lung adenocarcinoma by activating the PI3K/AKT/mTOR pathway, providing new therapeutic targets.

Cell migration↗

PubMed2026

LLPS-based classification and a novel prognostic signature reveal NRF1 as a therapeutic target in pancreatic cancer.

BACKGROUND: Aberrant liquid-liquid phase separation (LLPS) can alter biomolecular condensate functions and may influence pancreatic tumorigenesis and progression, but the specific role of LLPS regulators in prognosis and the tumor immune microenvironment (TIME) in pancreatic ductal adenocarcinoma (PDAC) remains unclear. METHODS: We integrated transcriptome data of LLPS regulator-related differentially expressed genes (DEGs; n = 298) in a cohort of 176 PDAC patients from TCGA. Three LLPS regulator subtypes (LS1-LS3) were identified through multi-omics analyses, and a prognostic LLPS subtype-related risk model (LRRPC) was developed and validated. Chromatin immunoprecipitation confirmed NRF1 binding to promoters of key risk genes, and in vitro and in vivo experiments assessed the effects of NRF1 targeting on tumor growth. RESULTS: The three LLPS regulator subtypes exhibited significant differences in prognosis, clinical features, genomic alterations, TIME patterns and predicted immunotherapy response. The LRRPC signature predicted prognosis and immunotherapy efficacy across cohorts and was associated with tumor biomarkers and immune infiltration. Nuclear Respiratory Factor 1 (NRF1) directly regulated hub genes such as FAM83A, RHOV and ITGB6, promoting PDAC cell proliferation, while its inhibition induced apoptosis and reduced tumor growth. CONCLUSIONS: This study proposes an LLPS-based stratification framework for PDAC, and the LRRPC model provides an LLPS subtype-related risk score that may assist personalized prognostic assessment and immunotherapy stratification. NRF1 emerges as a promising therapeutic candidate whose targeting can inhibit tumor progression in PDAC experimental models and warrants further evaluation.

Immunotherapy↗

PubMed2026

Targeting RELA and STAT3 regulates TNFRSF10A-mediated apoptosis in a novel apoptosis-based prognostic model for clear cell renal cell carcinoma.

BACKGROUND: Clear cell renal cell carcinoma (ccRCC) is the most common subtype of renal malignancy and remains a major cause of cancer-related mortality worldwide. Although advances in surgery, targeted therapy, and immunotherapy have improved outcomes for patients, reliable biomarkers for predicting prognosis remain limited. Therefore, robust gene-based prognostic models are urgently needed to improve risk stratification and guide individualized treatment strategies. METHODS: We developed a novel prognostic model integrating apoptosis and immune - related genes (AIRGs) to predict overall survival (OS) in patients with ccRCC. RESULT: Using Gene Set Enrichment Analysis (GSEA) combined with least absolute shrinkage and selection operator (LASSO) Cox regression, we identified 7 key prognostic genes, namely, CCR4, TNFRSF10A, TEK, TGFA, CD14, IFITM1, and SEMA3G, that collectively demonstrated strong predictive performance in TCGA cohort with c-index = 0.711. Functional enrichment analyses revealed that apoptosis, immune regulation, and multiple oncogenic signaling pathways were significantly associated with the risk score, highlighting the critical role of the tumor microenvironment in ccRCC progression. Transcription factor binding analysis based on the JASPAR database suggested that RELA and STAT3 with scores of 0.829 and 0.951, respectively are potential upstream regulators within the prognostic network, particularly influencing TNFRSF10A expression. External validation using the International Cancer Genome Consortium (ICGC) dataset confirmed the robustness of the prognostic model with c-index = 0.612 Furthermore, in vitro experiments demonstrated that RELA and STAT3 regulate TNFRSF10A-mediated apoptotic signaling in ccRCC cells, providing mechanistic support for the bioinformatic findings. CONCLUSION: This study establishes a biologically informed and clinically relevant prognostic framework for ccRCC. Our findings highlight the therapeutic potential of targeting the RELA/STAT3-TNFRSF10A axis and contribute to the advancement of precision medicine in ccRCC.

Humans↗

PubMed2026

Oncogenic PIK3CA reprograms glutamine metabolism to drive bladder cancer progression.

BACKGROUND: Genomic analysis has revealed that approximately 40% of bladder cancer (BLCA) tumors harbor alterations in the PI3K/AKT pathway, with PIK3CA mutations occurring in 15-25% of cases. PIK3CA, which encodes the catalytic p110α subunit of PI3K, plays a critical role in regulating cell survival, proliferation, and metabolism. However, the metabolic and functional consequences of PIK3CA mutations in BLCA remain poorly defined. METHODS: To investigate the role of PIK3CA mutations in BLCA, we performed targeted sequencing on tumors from patients, identifying recurrent alterations. Using CRISPR/Cas9 knock-in models in SCaBER and UM-UC-3 cell lines, we introduced the PIK3CA E545K mutation to study its effects. We conducted transcriptomic profiling, targeted metabolomics, and stable isotope tracing to assess metabolic reprogramming. Functional assays measured proliferation, mitochondrial complex I activity, and glutaminolysis. Orthotopic xenografts in mice were used to evaluate in vivo tumor growth and metabolism. RESULTS: PIK3CA mutations were present in 20% of cases, consistent with TCGA data. The E545K and E545Q hotspots accounted for 70% of these mutations. PIK3CA E545K strongly activated PI3K/AKT signaling. Transcriptomic analysis revealed enrichment of OXPHOS, fatty acid metabolism, and mTORC1 signaling. Metabolomics indicated changes in TCA cycle metabolites and enhanced reductive carboxylation of glutamine to citrate, driving fatty acid synthesis. Mutant cells showed increased expression of GLS1 and FASN, higher proliferation rates, and elevated mitochondrial complex I activity. In vivo, PIK3CA-mutant xenografts displayed significantly increased tumor growth. CONCLUSION: PIK3CA mutations are frequent drivers of metabolic reprogramming in BLCA, leading to increased glutamine flux, elevated OXPHOS activity, and enhanced fatty acid synthesis, all of which contribute to tumor progression. These findings provide the first comprehensive evidence that PIK3CA-driven metabolic alterations are both biomarkers of aggressive disease and actionable therapeutic targets. The efficacy of PI3Kα inhibition in combination with metabolic targets may support its potential in precision medicine for PIK3CA-mutant BLCA and highlights the value of integrating metabolic biomarkers into treatment strategies for advanced BLCA.

Journal Article↗