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Breast cancer (BC) is the most frequently diagnosed type of cancer, and the leading cause of cancer-associated mortality in females worldwide. The aim of the present study was to investigate the prognostic and therapeutic potential of NUF2 in BC. The expression levels of NUF2 in BC tissues and cell lines were evaluated via bioinformatics, reverse transcription-quantitative PCR, western blot analysis and immunohistochemistry (IHC). In addition, the effect of NUF2 knockdown on BC cell proliferation and apoptosis was investigated using small interfering RNA (siRNA) technology. Bioinformatics and IHC analysis showed that NUF2 was overexpressed in BC tissues. Furthermore, western blot and RT-qPCR analyses demonstrated that NUF2 was upregulated in BC cells. In addition, BC cells transfected with NUF2 siRNA exhibited significantly decreased proliferation and colony formation, and increased apoptosis, compared with the control. Additionally, cell cycle analysis revealed that NUF2 induced G0/G1 cell cycle arrest by inhibiting cyclin B1 expression. Collectively, the present study suggested that NUF2 may represent a promising prognostic biomarker and a potential therapeutic target for BC.

Multiple new subtypes of breast cancer (BRCA) are identified in women each year, rendering BRCA the most common and rapidly expanding form of cancer in females globally. NUF2 has been identified as a prognostic factor in various human cancers, regulating cell apoptosis and proliferation. However, its role in BRCA prognosis has not been clarified. This study explored the role of NUF2 in breast cancer development and prognosis using informatic analysis combined with in vivo intracellular studies. Through the online website TIMER, we evaluated the transcription profile of NUF2 across a variety of different cancer types and found that NUF2 mRNA was highly expressed in BRCA patients. Its transcription level was found to be related to the subtype, pathological stage, and prognosis of BRCA. The R program analysis showed a correlation of NUF2 with cell proliferation and tumor stemness in the BRCA patient samples. Subsequently, the association between the NUF2 expression level and immune cell infiltration was analyzed using the XIANTAO and TIMER tools. The results revealed that NUF2 expression was correlated with the responses of multiple immune cells. Furthermore, we observed the effect of NUF2 expression on tumor stemness in BRCA cell lines in vivo. The experimental results illuminated that the overexpression of NUF2 statistically upregulated the proliferation and tumor stemness ability of the BRCA cell lines MCF-7 and Hs-578T. Meanwhile, the knockdown of NUF2 inhibited the abilities of both cell lines, a finding which was verified by analyzing the subcutaneous tumorigenic ability in nude mice. In summary, this study suggests that NUF2 may play a key role in the development and progression of BRCA by affecting tumor stemness. As a stemness indicator, it has the potential to be one of the markers for the diagnosis of BRCA.

Cholangiocarcinoma (CCA) is the second most common primary hepatic malignancy and associated with poor prognosis. Lack of therapeutic methods for CCA and insensitivity of targeted therapy and immunotherapy make its treatment challenging. NUF2, a component of Ndc80 kinetochore complex, is implicated in the initiation and development of multiple cancers. However, the role and mechanism of NUF2 in CCA is still unclear. In this research, we investigated the biological processes and underlying mechanisms of NUF2 in CCA. We discovered that the expression of NUF2 was upregulated in CCA and negatively correlated with prognosis. Changes in NUF2 levels had an impact on cell proliferation and migration. Moreover, NUF2 functioned as an oncogene to promote the progression of CCA through p38/MAPK signaling by inhibiting p62 binding of TFR1 and affecting its autophagic degradation. In addition, TFR1 promoted CCA progression and Kaplan-Meier analyses uncovered patients with high expression of TFR1 was associated with the poor survival. In conclusion, our study demonstrated that NUF2 promoted CCA progression by regulating TFR1 protein degradation, and the NUF2/TFR1/MAPK axis could be an excellent therapeutic target for CCA.

Glioblastoma multiforme (GBM) is a lethal brain tumor with limited therapies. NUF2, a kinetochore protein involved in cell cycle regulation, shows oncogenic potential in various cancers; however, its role in GBM pathogenesis remains unclear. In this study, we investigated NUF2’s function and mechanisms in GBM and developed an MRI-based machine learning model to predict its expression non-invasively, and evaluated its potential as a therapeutic target and prognostic biomarker. Functional assays (proliferation, colony formation, migration, and invasion) and cell cycle analysis were conducted using NUF2-knockdown U87/U251 cells. Western blotting was performed to assess the expression levels of β-catenin and MMP-9. Bioinformatic analyses included pathway enrichment, immune infiltration, and single-cell subtype characterization. Using preoperative T1CE Magnetic Resonance Imaging sequences from 61 patients, we extracted 1037 radiomic features and developed a predictive model using Least Absolute Shrinkage and Selection Operator regression for feature selection and random forest algorithms for classification with rigorous cross-validation. NUF2 overexpression in GBM tissues and cells was correlated with poor survival ( p  < 0.01). Knockdown of NUF2 significantly suppressed malignant phenotypes ( p  < 0.05), induced G0/G1 arrest ( p  < 0.01), and increased sensitivity to TMZ treatment via the β-catenin/MMP9 pathway. The radiomic model achieved superior NUF2 prediction (AUC = 0.897) using six optimized features. Key features demonstrated associations with MGMT methylation and 1p/19q co-deletion, serving as independent prognostic markers. NUF2 drives GBM progression through β-catenin/MMP9 activation, establishing its dual role as a therapeutic target and a prognostic biomarker. The developed radiogenomic model enables precise non-invasive NUF2 evaluation, thereby advancing personalized GBM management. This study highlights the translational value of integrating molecular biology with artificial intelligence in neuro-oncology.

Background Hepatocellular carcinoma (HCC) one of the most common digestive system tumors, threatens the tens of thousands of people with high morbidity and mortality world widely. The purpose of our study was to investigate the related genes of HCC and discover their potential abilities to predict the prognosis of the patients. Methods We obtained RNA sequencing data of HCC from The Cancer Genome Atlas (TCGA) database and performed analysis on protein coding genes. Differentially expressed genes (DEGs) were selected. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment were conducted to discover biological functions of DEGs. Protein and protein interaction (PPI) was performed to investigate hub genes. In addition, a method of supervised machine learning, recursive feature elimination (RFE) based on random forest (RF) classifier, was used to screen for significant biomarkers. And the basic experiment was conducted by lab, we constructe a clinical patients’ database, and obtained the data and results of immunohistochemistry. Results We identified five biomarkers with significantly high expression to predict survival risk of the HCC patients. These prognostic biomarkers included SPC25, NUF2, MCM2, BLM and AURKA. We also defined a risk score model with these biomarkers to identify the patients who is in high risk. In our single-center experiment, 95 pairs of clinical samples were used to explore the expression levels of NUF2 and BLM in HCC. Immunohistochemical staining results showed that NUF2 and BLM were significantly up-regulated in immunohistochemical staining. High expression levels of NUF2 and BLM indicated poor prognosis. Conclusion Our investigation provided novel prognostic biomarkers and model in HCC and aimed to improve the understanding of HCC. In the results obtained, we also conducted a part of experiments to verify the theory described earlier, The experimental results did verify our theory.

Abstract Background: Gastric cancer (GC), a malignant tumor with poor prognosis, is one of the leading causes of cancer-related deaths worldwide; consequently, identifying novel therapeutic targets is crucial for its corresponding treatment. NUF2, a component of the NDC80 kinetochore complex, promotes cancer progression in multiple malignancies. Therefore, this study aimed to explore the potential of NUF2 as a therapeutic target to inhibit GC progression. Methods: Clinical samples were obtained from patients who underwent radical resection of GC at Lanzhou University Second Hospital from 2016 to 2021. Cell count assays, colony formation assays, and cell-derived xenotransplantation (CDX) models were used to determine the effects of NUF2 on GC progression. Flow cytometry was used to detect the effect of NUF2 or quercetin on cell cycle progression and apoptosis. A live-cell time-lapse imaging assay was performed to determine the effect of NUF2 on the regulation of mitotic progression. Transcriptomics was used to investigate the NUF2-associated molecular mechanisms. Virtual docking and microscale thermophoresis were used to identify NUF2 inhibitors. Finally, CDX, organoid, and patient-derived xenograft (PDX) models were used to examine the efficacy of the NUF2 inhibitor in GC. Results: NUF2 expression was significantly increased in GC and was negatively correlated with prognosis. The deletion of NUF2 suppressed GC progression both in vivo and in vitro. NUF2 significantly regulated the mitogen-activated protein kinase (MAPK) pathway, promoted G2/M phase transition, and inhibited apoptosis in GC cells. Additionally, quercetin was identified as a selective NUF2 inhibitor with low toxicity that significantly suppressed tumor growth in GC cells, organoids, CDX, and PDX models. Conclusions: Collectively, NUF2-mediated G2/M phase transition and apoptosis inhibition promoted GC progression; additionally, NUF2 inhibitors exhibited potent anti-GC activity. This study provides a new strategy for targeting NUF2 to suppress GC progression in clinical settings.

The poor sensitivity of clear cell renal cell carcinoma (ccRCC) to conventional chemotherapy and radiotherapy makes its treatment challenging. The Ndc80 kinetochore complex component (NUF2) is involved in the development and progression of several cancers. However, its role in ccRCC remains unclear. In this study, we investigated the biological functions and underlying mechanism of NUF2 in ccRCC. We found that NUF2 expression was increased in ccRCC and associated with poor prognosis. Altering NUF2 level affected cell proliferation, migration, and invasion. Moreover, NUF2 acted as a potential oncogene to promote the progression of ccRCC through epigenetic activation of high-mobility group AT-hook 2 (HMGA2) transcription by suppressing lysine demethylase 2A expression and affecting its occupancy on the promoter region to regulate histone H3 lysine 36 di-methylation modification. In addition, Kaplan-Meier and multivariate analysis revealed that patients whose NUF2 and HMGA2 were both elevated showed the shortest survival; and the number of upregulated markers acted as an independent predictor to evaluate survival probability. Thus, our results demonstrate that NUF2 promotes ccRCC progression, at least partly by epigenetically regulating HMGA2 transcription, and that the NUF2-HMGA2 axis could be an ideal therapeutic target and a promising prognostic indicator for ccRCC.

The aims of the present study were to screen differentially expressed genes (DEGs) in breast cancer (BC) and investigate NDC80 kinetochore complex component (NUF2) as a prognostic marker of BC in detail. A total of four BC microarray datasets, downloaded from the Gene Expression Omnibus (GEO) and The Cancer Genome Atlas (TCGA) databases, were used to screen DEGs. A total of 190 DEGs with the same expression trends were identified in the 4 data-sets, including 65 upregulated and 125 downregulated DEGs. Functional and pathway enrichment analyses were performed using the Database for Annotation, Visualization and Integrated Discovery. The upregulated DEGs were enriched for 10 Gene Ontology (GO) terms and 7 pathways, and the downregulated DEGs were enriched for 10 GO terms and 10 pathways. A protein-protein interaction network containing 149 nodes and 930 edges was constructed using the Search Tool for the Retrieval of Interacting Genes, and 2 functional modules were identified using the MCODE plugin of Cytoscape. Based on an in-depth analysis of module 1 and literature mining, NUF2 was selected for further research. Oncomine database analysis and reverse transcription-quantitative PCR showed that NUF2 is significantly upregulated in BC tissues. In analyses of correlations between NUF2 and clinical pathological characteristics, NUF2 was significantly associated with the malignant features of BC. Using 5 additional datasets from GEO, it was demonstrated that NUF2 has a significant prognostic role in both ER-positive and ER-negative BC. A Gene Set Enrichment Analysis indicated that NUF2 may regulate breast carcinogenesis and progression via cell cycle-related pathways. The results of the present study demonstrated that NUF2 is overexpressed in BC and is significantly associated with its multiple pathological features and prognosis.