Journal of Cancer最新文献

Background: Cuproptosis, a form of copper-mediated programmed cell death, has recently garnered significant attention. However, the mechanisms by which CRGs affect the progression of CRC remain unclear. Methods: Bioinformatics approaches were employed to analyze transcriptomic datasets and clinical data from 630 CRC patients, focusing on copy number variations, prognostic implications, and immune infiltration characteristics associated with CRGs. Key CRG-related genes impacting prognosis were identified using LASSO and Cox regression methods. A prognostic model incorporating various molecular markers and clinical parameters was constructed with a training cohort and validated with a separate validation cohort. This model was used to explore clinical indicators, immune infiltration, and tumor microenvironment characteristics in CRC patients. Additionally, single-cell analysis was performed to investigate the biological roles of critical genes, and expression patterns of these genes were assessed via qRT-PCR and WB. Results: A prognostic scoring model was established based on three pivotal genes associated with CRC prognosis. This model, an independent prognostic indicator, outperformed traditional clinicopathological features in predicting patient outcomes. Kaplan-Meier survival curves demonstrated superior prognostic outcomes for individuals in the low-risk group compared to those in the high-risk group. Model stability and reliability were confirmed through ROC analysis and univariate and multivariate Cox regression analyses. Further analysis revealed significant correlations between prognostic scores and the presence of M0 macrophages and memory CD4⁺ T cells. Differences in the expression of CDKN2A, PLCB4, and NXPE4 across various CRC tissues and cells were characterized using WB, IHC and qRT-PCR. Conclusion: This study not only highlights the diverse omics profiles of CRGs in CRC but also introduces a novel model for accurate prognostic forecasting.

Objective: To investigate the role of HOXC9 in the transformation of oral leukoplakia (OLK) to oral squamous cell carcinoma (OSCC) and its effectiveness as a new molecular marker for oral leukoplakia carcinogenesis. Materials and Methods: We assessed HOXC9 in OLK and OSCC using immunohistochemistry (IHC). Colony formation and transwell experiment were employed to appraise the function of HOXC9 in the malignant transformation of OLK. ChIP-qPCR, CO-IP, RIP-qPCR, RNA pull down and mass spectrometry were using to evaluate the molecular mechanism of HOXC9. Results: HOXC9 expression was higher in patients with OSCC than in those with OLK, which is associated with increased malignant transformation of OLK. Functional experiments suggested that HOXC9 induces the acquisition of cancer stem cells (CSCs) and epithelial-to-mesenchymal transition (EMT). Subsequently, we found that the HOXC9-mediated malignant phenotype was reversed by HOXC-AS1 depletion. Mechanistically, HOXC-AS1 regulates H3K27me3 methylation and EZH2 as a potential HOXC-AS1-HOXC9 interacting protein. Finally, we found that the 251-619nt nucleotide of HOXC-AS1 competitively binds to EZH2. Conclusion: HOXC-AS1 competitively binds to EZH2, inhibiting its binding to H3 in the HOXC9 promoter region, resulting in a decrease in H3K27me3 and enhanced expression of HOXC9, thereby promoting CSCs and EMT in oral leukoplakia, ultimately leading to malignant transformation into oral squamous cell carcinoma.

Background: Implantable port catheters (IPCs) and peripherally inserted central catheters (PICCs) are commonly used venous access methods for chemotherapy in cancer patients. However, the question of which is superior remains controversial. This meta-analysis, based on randomized controlled trials (RCTs), systematically compares the safety, cost, and impact on quality of life between these two methods. Methods: Eligible RCTs comparing IPC and PICC were identified through searches in seven databases. Complications were the primary endpoint, while secondary endpoints included cost, impact on chemotherapy, and quality of life assessments. Results: Six studies based on five RCTs, including a total of 1,127 patients, were analyzed. Patient data indicated that the PICC group experienced a higher incidence of total complications, thrombosis, deep vein thrombosis, implantation failure, unplanned catheter removal, and local reactions. Conversely, the IPC group had a higher incidence of pocket infection/exit-site infection without septicemia and pain. When considering catheter days, the PICC group again showed a higher incidence of total complications, thrombosis, deep vein thrombosis, implantation failure, unplanned catheter removal, edema, and local reactions. Complication-free survival was better in the IPC group. Although the impact on chemotherapy tended to favor the IPC group, this difference was not statistically significant. The total cost was higher in the IPC group, while the cost per catheter day was similar between the two groups. Quality of life assessments (using EORTC QLQ-C30) revealed similar global health status between the two groups during the post-implantation, mid-treatment, and end-treatment periods. However, the IPC group experienced a smaller decline in global health status post-implantation compared to the PICC group. Conclusions: Compared to PICC, IPC appears to be a safer and more comfortable intravenous catheterization option for cancer patients undergoing chemotherapy.

Background: KANK2, a gene crucial for cell migration and movement, is implicated in neoplastic and non-neoplastic diseases. This study aimed to analyze KANK2's expression and its diagnostic and prognostic significance across 33 cancers using multiple online databases.

Methods: This study aimed to comprehensively analyze KANK2 in 33 cancers using The Cancer Genome Atlas (TCGA) and Genotype-Tissue Expression (GTEx) database. Multiple web platforms and software were used for data analysis, including R, Cytoscape, HPA, TISIDB, UALCAN, GEO, cBioPortal, STRING, GSCALite, and CancerSEA. WB and qPCR experiments were used to verify the results.

Results: KANK2 is widely expressed in various tissues and has significant diagnostic value in multiple cancers, with AUC values exceeding 0.75 in 13 cancer types. Survival analysis indicated that KANK2 expression is significantly associated with overall survival (OS) and disease-specific survival (DSS) in several cancers. KANK2 expression varied significantly across different molecular and immune subtypes and was associated with specific genetic mutations and DNA methylation patterns. Functional state analysis highlighted correlations with processes such as EMT, angiogenesis, and apoptosis. GSEA identified pathways related to proliferation, migration, and extracellular matrix remodeling. The key interacting proteins were identified by PPI network analysis, and the sensitive drug molecules were found by GSCA database. The results were also confirmed by two GEO datasets and WB and qPCR results.

Conclusion: KANK2 serves as a valuable biomarker for diagnosis and prognosis in various cancers, and its expression is intricately linked to multiple molecular and cellular processes, offering potential therapeutic targets for future research.

Anoikis resistance and improper activation of epithelial‒mesenchymal transition (EMT) are critical factors in tumor metastasis and progression. Despite their interaction, the combined impact of anoikis and EMT on prognosis and immunotherapy in gastric cancer remains underexplored. In this study, we identified 354 anoikis- and EMT-related genes (AERGs) through Venn analysis and performed unsupervised clustering to classify gastric cancer patients into two molecular clusters: A and B. Molecular cluster A showed poor prognosis and an immunosuppressive tumor microenvironment, suggesting a "cold tumor" phenotype. Then, a novel AERG-related prognostic model comprising CD24, CRYAB, MMP11, MUC4, PRKAA2, SERPINE1, SKP2, and TP53 was constructed and validated, accurately predicting the 1-, 3-, and 5-year survival rates of gastric cancer patients. Multivariate analysis revealed that the AERG-related risk score was an independent prognostic factor (hazard ratio = 1.651, 95% confidence interval = 1.429-1.907, P<0.001). Further studies demonstrated that, compared to the high-risk group, the low-risk group exhibited higher CD8⁺ T cell infiltration, tumor mutational burden, immunophenoscores, and lower tumor immune dysfunction and exclusion scores, indicating potential sensitivity to immunotherapy. RT‒qPCR and immunohistochemical staining validated the expression levels of the model's molecular markers. Overall, our AERG-related model shows promise for predicting outcomes and guiding the selection of tailored and precise therapies for gastric cancer patients.

Gamma-delta (γδ) T cells are a crucial component of the tumor immune microenvironment which are considered a promising potential therapeutic strategy and target. Increasing evidence suggests that these unique immune cells play significant roles across various cancers. However, γδ T cells are often regarded as having dual roles in tumors, and their influence on lung adenocarcinoma (LUAD) remains controversial. In this research, we employed a wild-ranging approach using multi-omics data to investigate the function of γδ T cells in LUAD. The abundance of γδ T cell infiltration is linked to a positive prognosis in lung adenocarcinoma. The tumor-inhibiting role of γδ T cells was played through intrinsic lineage evolution, acquiring cytotoxic functions and engaging in signal transduction with antigen-presenting cells. Furthermore, patients with higher γδ T cells infiltration abundance might be more favorable for immunotherapy. Lastly, we established a predictive model using CT images based on radiomics, providing a non-invasive strategy to assess γδ T cells infiltration in LUAD patients. These findings offer new insights and perspectives the personalized therapies of γδ T cells.

Glioblastoma multiforme (GBM), whose pathogenesis involves proneural-to-mesenchymal transition (PMT), is the most malignant type of glioma and is associated with a bleak prognosis. Lactate dehydrogenase (LDH) comprises two major subunits, LDHA and LDHB, which can assemble into five different isoenzymes (LDH1-5). However, the role of LDH isoenzyme and its subunits in different GBM subtypes is largely unknown. Our findings reveal that LDHA and LDHB subunits correlated with mesenchymal and proneural subtype classification, and have prognostic and clinical significance in GBM patients. Moreover, it is demonstrated that LDH5, characterized by high LDHA and low LDHB levels, is highly expressed in mesenchymal subtype GBM cells and promotes proliferation, migration, and PMT. Conversely, proneural subtype GBM cells exhibited LDH1 dominance, and low LDHA and high LDHB levels. Notably, LDH1 played a pivotal role in the proliferation, migration, and PMT of proneural glioma cells. For treatment of proneural subtype GBM, gossypol-acetic acid (GAA)-bovine serum albumin (BSA) nanoparticles (GAA-BSA NPs) were developed to ameliorate PMT by targeting LDH1. These nanoparticles effectively suppress proneural subtype tumor growth both in vitro and in vivo, surpassing their efficacy against the mesenchymal subtype. The results offer several novel insights into the role of LDH isoenzyme in subtype classification between mesenchymal and proneural GBM and provide a promising therapeutic approach for proneural subtype GBM.

Purpose: Exploring the value of predicting the WHO/ISUP grade of clear cell renal cell carcinoma (ccRCC) using computed tomography urography (CTU) images, providing valuable recommendations for the treatment of ccRCC. Method: CTU images from the Renmin Hospital of Wuhan University (RHWU) cohort, including 328 patients with ccRCC, were retrospectively collected. The corticomedullary (CMP) phase features of ccRCC were extracted from the CTU images using the Pyradiomics package, and key features were selected through the Least Absolute Shrinkage and Selection Operator (LASSO) regression. The 328 patients were split into training and testing sets in a 7:3 ratio. 175 patients from the The Cancer Genome Atlas (TCGA) cohort were used for the external validation set. Various models, including Logistic Regression (LR), Multilayer Perceptron (MLP), Support Vector Machine (SVM), and eXtreme Gradient Boosting (XGBoost), were employed to predict the ISUP grade. SHAP analysis was then used to visualize the performance of the best model. Results: A total of 1,218 features were extracted using the Pyradiomics package, with 20 features selected for model training through LASSO analysis. In the training set, the AUC for the LR model was 0.88 (95% confidence interval [CI] 0.84-0.91), for MLP it was 0.89 (95% CI 0.86-0.93), for SVM it was 0.86 (95% CI 0.83-0.90), and for XGBoost it was 0.96 (95% CI 0.92-0.99). In the testing set, the AUC for LR was 0.79 (95% CI 0.73-0.85), for MLP it was 0.78 (95% CI 0.72-0.83), for SVM it was 0.78 (95% CI 0.73-0.82), and for XGBoost it was 0.80 (95% CI 0.75-0.85). In the validation set, the AUC for LR was 0.74 (95% CI 0.68-0.79), for MLP it was 0.68 (95% CI 0.63-0.73), for SVM it was 0.67 (95% CI 0.64-0.71), and for XGBoost it was 0.78 (95% CI 0.74-0.83). XGBoost demonstrated superior performance, with a sensitivity of 0.99 (95% CI 0.96-1.00) in the training set, 0.92 (95% CI 0.88-0.97) in the testing set and 0.91 (95% CI 0.86,0.95) in validation set. SHAP analysis revealed that the wavelet-LHL_glcm_Idn and wavelet-LHL_glrlm_LongRunEmphasis features played pivotal roles in the classification task. Conclusion: In this study, we employ an artificial intelligence model to conduct non-invasive ISUP grade prediction on preoperative CTU images of ccRCC, thereby aiding clinical decision-making. Additionally, we uncover that the radiomics features extracted from the CMP phase of CTU images hold promise as potential biomarkers for grading ccRCC.

Lung cancer remains the leading cause of cancer-related mortality worldwide, with non-small cell lung cancer (NSCLC) being the predominant subtype. Recent advances in transcriptome sequencing have highlighted the critical role of long non-coding RNAs (lncRNAs) in NSCLC, with lncRNAs influencing gene expression through epigenetic, transcriptional, and post-transcriptional mechanisms. Despite the growing understanding of lncRNAs, challenges such as delayed diagnosis and drug resistance continue to complicate NSCLC management. This review explores novel findings in the role of lncRNAs (e.g., MALAT1, HOTAIR, and GAS5) in NSCLC, with a particular focus on their encoded small peptides and N6-methyladenosine (m6A) modifications. We further discuss how the interplay between lncRNAs, their encoded peptides, and m6A modifications can provide new strategies for improving NSCLC diagnosis, treatment, and overcoming drug resistance. This review also highlights emerging research avenues that could lead to innovative clinical interventions in NSCLC.

We studied the prognostic value of SIGLEC1 in colorectal cancer (CRC) using bioinformatics. SIGLEC1 exhibited differential expression between the tumor and control samples, and improved survival was observed in patients with increased SIGLEC1 expression. The univariate and multivariate analyses confirmed SIGLEC1 as an independent prognostic factor for CRC, based on which a nomogram was constructed for predicting survival in patients with CRC. Additionally, higher SIGLEC1 expression was correlated with increased immunological/stromal/ESTIMATE scores as well as immune cell infiltration and was strongly and positively associated with T helper cells and macrophages. Furthermore, significant positive correlations were observed between SIGLEC1 expression and inhibitory/coinhibitory immunological genes. Additionally, the TIDE results of patients with CRC showed that increased SIGLEC1 expression was related to poorer immunotherapeutic responses. In clinical samples from patients with CRC, a decrease in SIGLEC1 expression was noted compared to para-cancerous tissues and samples from patients who received Yiqi Huayu Jiedu Decoction (YHJD) treatment. The in vivo results indicated the superior efficacy of YHJD against CRC in inhibiting tumor metastasis. Our study demonstrates that SIGLEC1 serves as a prognostic factor for CRC, strongly linked to immune response, and can be modulated by YHJD, suggesting novel avenues for CRC treatment.