Translational cancer research最新文献

{"title":"Development and validation of a Hypoxia and Lactate Metabolism Prognostic Score (HLMPS) for breast cancer using machine learning.","authors":"Zhou Fang, Shichong Liao, Zhong Wang, Juanjuan Li, Lijun Wang, Yimin Zhang, Yueyue Guo, Feng Yao","doi":"10.21037/tcr-2025-1115","DOIUrl":"10.21037/tcr-2025-1115","url":null,"abstract":"<p><strong>Background: </strong>Previous studies often overlooked the roles of hypoxia and lactate metabolism in the breast cancer (BRCA) microenvironment. This study developed and validated a novel prognostic model for BRCA based on hypoxia-related genes (HRGs) and lactate metabolism-related genes (LMRGs) using machine learning approaches. The aim was to identify molecular subtypes capable of predicting patient prognosis and treatment response, thereby facilitating precision medicine strategies for BRCA.</p><p><strong>Methods: </strong>This study utilized bulk RNA-sequencing data from The Cancer Genome Atlas (TCGA) BRCA cohort (1,079 tumor samples; 99 normal samples) as the training set, with five independent validation cohorts (GSE19615, GSE20685, GSE20711, GSE42568, GSE58812) retrieved from the Gene Expression Omnibus (GEO) database. HRGs and LMRGs were identified from the Molecular Signatures Database (MSigDB). A machine learning-based integrative approach was employed to construct the Hypoxia and Lactate Metabolism Prognostic Score (HLMPS) via 10-fold cross-validation and multiple algorithm combinations. Model robustness was rigorously assessed through Kaplan-Meier survival analysis, time-dependent receiver operating characteristic (ROC) curves, and calibration plots with Brier score quantification.</p><p><strong>Results: </strong>The HLMPS model demonstrated robust prognostic discrimination, with high-risk patients exhibiting significantly inferior overall survival compared to low-risk counterparts [training set areas under the curve (AUCs): 0.76, 0.77, 0.74 at 1/3/5 years; validation sets AUCs: 0.61, 0.65, 0.67 at 1/3/5 years]. Functional enrichment analysis revealed that patients with a high HLMPS tended to have dysregulation of cell cycle and neurodevelopmental pathways, while those with a low HLMPS exhibited activation of immune pathways, including T-cell receptor (TCR) signaling and antigen presentation. An Immune infiltration analysis showed that patients with a low HLMPS had higher levels of immune cell infiltration and better responsiveness to immunotherapy. Meanwhile, patients with a low HLMPS showed greater sensitivity to drugs such as irinotecan and palbociclib, while patients with a high HLMPS were more sensitive to drugs such as lapatinib and sorafenib.</p><p><strong>Conclusions: </strong>The HLMPS model represents a novel and clinically actionable tool for prognosticating outcomes and therapeutic responses in BRCA patients. This study highlights the potential of precision medicine strategies that integrate HRGs and LMRGs based on tumor microenvironment (TME) features. Future work should focus on validating the HLMPS model in larger, multicenter cohorts and determining its clinical applicability in guiding personalized treatment decisions for patients with BRCA.</p>","PeriodicalId":23216,"journal":{"name":"Translational cancer research","volume":"14 7","pages":"4399-4415"},"PeriodicalIF":1.7,"publicationDate":"2025-07-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12335689/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144822692","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Women's hormonal health research and care: the times, they are a-changin'.","authors":"Jennifer D Merrill, Lawrence M Nelson","doi":"10.21037/tcr-2025-331","DOIUrl":"10.21037/tcr-2025-331","url":null,"abstract":"","PeriodicalId":23216,"journal":{"name":"Translational cancer research","volume":"14 7","pages":"3899-3904"},"PeriodicalIF":1.7,"publicationDate":"2025-07-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12335676/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144822716","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"TC2N promotes the proliferation and invasion of head and neck cancer cells with the p53-R175H.","authors":"Qian Zhang, Xiaogang Zhou, Xianglin Hao, Qi Sun, Gang Zhang, Shuai Xu","doi":"10.21037/tcr-24-2130","DOIUrl":"10.21037/tcr-24-2130","url":null,"abstract":"<p><strong>Background: </strong>Tandem C2 domains, nuclear (TC2N) is a recently identified tumor-associated gene that has been confirmed to play important roles in various malignancies, including lung cancer, breast cancer, gastric cancer, glioma, and liver cancer. However, its biological functions and mechanisms in head and neck squamous cell carcinoma (HNSCC) remain unclear. In this study, we aimed to analyze the expression and methylation status of TC2N using public databases and preliminarily investigate the effects of TC2N on the malignant phenotypes of HNSCC cells and its potential mechanisms.</p><p><strong>Methods: </strong>Data from The Cancer Genome Atlas (TCGA) and multiple Gene Expression Omnibus (GEO) databases were analyzed to assess the expression levels of TC2N in HNSCC. Functional and signaling pathway analyses were conducted both <i>in vitro</i> and <i>in vivo</i> to evaluate the impact of TC2N on cell growth, invasion, and apoptosis. The role of TC2N in promoting cancer through mutant p53-mediated signaling was also explored.</p><p><strong>Results: </strong>The study found that TC2N was downregulated in HNSCC and its expression was correlated with the degree of promoter methylation. Both <i>in vitro</i> and <i>in vivo</i> experiments demonstrated that TC2N can stimulate cell growth and invasion, and inhibit apoptosis via mutant p53-R175-mediated pro-cancer signals.</p><p><strong>Conclusions: </strong>This study reports the expression pattern of TC2N in HNSCC and provides preliminary insights into the biological functions and mechanisms of this gene in this type of cancer, laying the experimental foundation for investigating the role and mechanism of TC2N in HNSCC.</p>","PeriodicalId":23216,"journal":{"name":"Translational cancer research","volume":"14 7","pages":"3905-3919"},"PeriodicalIF":1.7,"publicationDate":"2025-07-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12335704/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144822684","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Development and validation of machine learning models for classifying cancer-related sarcopenia using Kinect-based mixed-reality exercises in breast cancer survivors.","authors":"Byunggul Lim, Wook Song","doi":"10.21037/tcr-2024-2337","DOIUrl":"10.21037/tcr-2024-2337","url":null,"abstract":"<p><strong>Background: </strong>Sarcopenia in cancer survivors is often underdiagnosed due to limited access to imaging-based diagnostic tools such as computed tomography (CT) or dual-energy X-ray absorptiometry (DXA). Indirect classification using movement data may offer a practical, scalable alternative. This study aimed to develop and validate machine learning (ML)-based classification models for cancer-related sarcopenia using joint angle data obtained from Kinect-based mixed-reality (KMR) devices, aiming to improve classification accuracy and identify key movement-related predictors.</p><p><strong>Methods: </strong>Overall, 77 breast cancer survivors (mean age, 48.9±5.4 years) were included based on stage I-III diagnosis, treatment completion ≥6 months prior, no metastasis, low physical activity, and no major comorbidities. Sarcopenia was diagnosed using skeletal muscle index (SMI) (<5.7 kg/m²) and handgrip strength (HGS) (<18 kg). KMR device data were collected during 8 weeks of exercise. After preprocessing, the dataset was randomly split (8:2) for training and testing. Four ML models-support vector machine (SVM), K-nearest neighbor (KNN), random forest (RF), and XGBoost (XGB)-were trained. Five-fold cross-validation was used for tuning, and feature importance was analyzed.</p><p><strong>Results: </strong>Of the 38 participants in the exercise group included in the final analysis, 12 (31.5%) were initially diagnosed with sarcopenia. After the 8-week KMR device exercise intervention, 3 participants showed recovery from sarcopenia, resulting in 9 (23.6%) remaining classified with the condition. In the test set, the XGB model demonstrated the highest performance, achieving 94.7% accuracy, 91.2% recall, 95.8% precision, 93.4% F1 score, and 96.2% area under the curve (AUC). Feature importance analysis using RF and XGB consistently identified right \"knee flexion (right)\" as the most influential predictor.</p><p><strong>Conclusions: </strong>Among ML classification models trained on KMR device joint data, XGB demonstrated the best performance. Right knee flexion emerged as the most influential feature in sarcopenia classification. These findings suggest that KMR device movement analysis may serve as a practical, non-invasive screening tool for sarcopenia, enabling early detection and personalized intervention strategies for breast cancer survivors in both clinical and remote settings.</p>","PeriodicalId":23216,"journal":{"name":"Translational cancer research","volume":"14 7","pages":"4208-4218"},"PeriodicalIF":1.7,"publicationDate":"2025-07-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12335685/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144822701","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Development of a prognostic model based on m6A reader <i>HNRNPA2B1</i> upregulation and immune infiltration in multiple malignant tumors.","authors":"Yang Han, Wei Xia, Zhong-Na Ma, Zhong-Chao Mai, Yu-Shui Ma, Da Fu, Juhua Zhuang","doi":"10.21037/tcr-2024-2616","DOIUrl":"10.21037/tcr-2024-2616","url":null,"abstract":"<p><strong>Background: </strong>High <i>HNRNPA2B1</i> expression has been previously observed in diverse tumor types. On this basis, the present work focused on exploring the effects of <i>HNRNPA2B1</i> on pan-cancer occurrence and progression, as well as its potential functions and molecular regulatory mechanisms.</p><p><strong>Methods: </strong><i>HNRNPA2B1</i> gene expression, protein expression, Tumor Node Metastasis (TNM) stage, and survival prognosis in thirty-three different tumors across thirty-three tumors were analyzed via The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases, which included 9,664 cancer tissues and 711 normal tissues, with R software (version 3.6.3). A series of bioinformatics analyses were performed to determine the relationships between the expression of <i>HNRNPA2B1</i>-associated genes and prognosis, DNA promoter methylation, phosphorylation status and immune cell infiltration. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses were performed to elucidate gene functions. Cancer and corresponding para-cancerous samples were confirmed via immunohistochemistry.</p><p><strong>Results: </strong>This study confirmed that <i>HNRNPA2B1</i> overexpression was associated with cancer development and a dismal prognosis in multiple types of cancer. Mutation and amplification were the main types of alterations in bladder urothelial carcinoma and esophageal adenocarcinoma, respectively. The phosphorylation and methylation levels of <i>HNRNPA2B1</i> were linked to multiple tumor types. Furthermore, the <i>HNRNPA2B1</i> expression level was positively correlated with infiltration degree in CESC, LIHC, HNSC-HPV⁺, and MESO-associated fibroblasts in TCGA. In addition, nine Chinese herbal medicines and ten Chinese medicinal plant components targeting <i>HNRNPA2B1</i> were identified.</p><p><strong>Conclusions: </strong><i>HNRNPA2B1</i> affects tumor occurrence and progression. The expression of <i>HNRNPA2B1</i> may serve as a reliable prognostic marker as well as a potential therapeutic target.</p>","PeriodicalId":23216,"journal":{"name":"Translational cancer research","volume":"14 7","pages":"4219-4242"},"PeriodicalIF":1.7,"publicationDate":"2025-07-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12335694/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144822702","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A comparison of hepatitis B virus- and hepatitis C virus-related hepatocellular carcinoma: a bioinformatics analysis.","authors":"Yiwen Huang, Guangpeng Chen, Hong Fan, Shangzi Wang, Huangbo Yuan, Zhengqiu Liu, Tiejun Zhang","doi":"10.21037/tcr-2024-2607","DOIUrl":"10.21037/tcr-2024-2607","url":null,"abstract":"<p><strong>Background: </strong>The genetic and epigenetic differences between hepatitis B virus-related hepatocellular carcinoma (HBV-HCC) and hepatitis C virus-related hepatocellular carcinoma (HCV-HCC) remain underexplored. This study aimed to elucidate DNA methylation patterns and features of HBV-HCC and HCV-HCC through use of an innovative method from a comparative perspective.</p><p><strong>Methods: </strong>We conducted gene expression and methylation analyses to identify differentially expressed genes (DEGs) and differentially methylated probes (DMPs) based on The Cancer Genome Atlas (TCGA) database. Cox survival analysis was employed to identify prognosis-related DEGs (Pro-DEGs). A novel sequential least absolute shrinkage and selection operator (Seq-Lasso) technique was used to integrate gene expression and DNA methylation data, subsequently generating gene-level DNA methylation summaries. These summaries were used to select methylation-expression quantitative trait loci (methyl-eQTLs) from Pro-DEGs for HBV-HCC and HCV-HCC, respectively.</p><p><strong>Results: </strong>Hypomethylation was more prevalent in HBV-HCC than in HCV-HCC in regardless of the genome region. Notably, open sea regions of the HBV-HCC patient group contained the most functionally significant methylation sites, whereas in the HCV-HCC patient group, the most functionally important cytosine-phosphate-guanine (CpG) sites were typically located in shelf regions when positively associated with gene expression within genes. We further constructed and validated a prognostic index (PI) based on six methyl-eQTLs associated with HCC prognosis.</p><p><strong>Conclusions: </strong>Our study found that CpG island sites had the least functional importance in both HBV-HCC and HCV-HCC. And, we also constructed and validated a PI based on six methyl-eQTLs that may be related to HCC prognosis via RFC3.</p>","PeriodicalId":23216,"journal":{"name":"Translational cancer research","volume":"14 7","pages":"4243-4259"},"PeriodicalIF":1.7,"publicationDate":"2025-07-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12335692/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144822672","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A novel fumaric acid metabolism-related prognostic signature associated with prognosis and immune infiltration landscape in laryngeal squamous cell carcinoma.","authors":"Zhang Feng, Yuhang Yang, Jinqing Li, Long Zuo, Meijiao Duan, Bingmin Xu, Zhenlian Xie, Dongzhi Zuo, Xiaosong He, Fangxian Liu, Feng He","doi":"10.21037/tcr-2025-29","DOIUrl":"10.21037/tcr-2025-29","url":null,"abstract":"<p><strong>Background: </strong>Laryngeal squamous cell carcinoma (LSCC) is an aggressive malignant tumor, characterized by high incidence and mortality. Metabolic pathways within cancer cells are frequently dysregulated; thus, exploring fumaric acid metabolism-related genes (FAMRGs) appears interesting. We aimed to identify a signature prognostic genetic profile to develop tailored management strategies for patients with LSCC.</p><p><strong>Methods: </strong>Data from The Cancer Genome Atlas (TCGA), Gene Expression Omnibus (GEO), and GeneCards databases were used to identify differentially expressed genes related to fumaric acid (FA) metabolism in LSCC. To explore the underlying mechanisms, we conducted analyses using the Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG). Additionally, we employed Cox regression and the least absolute shrinkage and selection operator (LASSO) to develop a risk signature based on FAMRGs. This signature was validated in TCGA and GEO cohorts. The association of the risk score with clinical characteristics, microenvironmental characteristics, and drug sensitivity was explored by correlation analyses. Finally, expression of FAMRGs was validated using datasets from the Gene Expression Profiling Interactive Analysis (GEPIA) and the Human Protein Atlas (HPA) databases. Moreover, the robustness of our findings was further confirmed through molecular docking and single-cell sequencing.</p><p><strong>Results: </strong>A FA metabolism-associated model for laryngeal cancer was constructed using seven genes (<i>ABCC2</i>, <i>ADH7</i>, <i>AQP9</i>, <i>CXCL11</i>, <i>GPT</i>, <i>PAEP</i>, and <i>PLCG1</i>). Functional analysis suggested that FAMRGs were strongly associated with the chemotaxis and cytokine-cytokine receptor interaction. High-risk score subgroups, as indicated by the Kaplan-Meier curves, demonstrated poorer outcomes in both TCGA and GEO cohorts. A predictive nomogram was developed for LSCC survival probability; FAMRGs were significantly associated with the immune checkpoints. Additionally, six small molecule drugs that appeared promising as therapeutic agents in combating LSCC were identified. Besides, CXCL11 and AQP9 exhibited significantly high expression in tumor tissues, while GPT showed low expression, as confirmed by the HPA and GEPIA databases. Molecular docking confirmed the interaction between the seven core genes and FA. This finding was corroborated by single-cell sequencing, which revealed significant expression differences across various cell clusters in LSCC.</p><p><strong>Conclusions: </strong>A prognostic model associated with FA metabolism was established for LSCC based on seven genes. This model can effectively predict LSCC prognosis. Additionally, six small molecule drugs with potential therapeutic value for LSCC were identified.</p>","PeriodicalId":23216,"journal":{"name":"Translational cancer research","volume":"14 7","pages":"3991-4008"},"PeriodicalIF":1.7,"publicationDate":"2025-07-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12335682/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144822674","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Identification and validation of anoikis-related differentially expressed genes in nasopharyngeal carcinoma.","authors":"Chaobin Huang, Ying Peng, Xueping Zheng, Siqian Cai, Zhongmei Lin, Yahan Zheng, Wei Zheng, Fengying Peng, Yuanji Xu","doi":"10.21037/tcr-2025-1263","DOIUrl":"10.21037/tcr-2025-1263","url":null,"abstract":"<p><strong>Background: </strong>Anoikis resistance is a critical feature enabling cancer cells to survive during detachment from the extracellular matrix. This study aimed to identify and validate anoikis-related differentially expressed genes (ARDEGs) in nasopharyngeal carcinoma (NPC), providing new insights into the molecular mechanisms underlying NPC progression and potential therapeutic targets.</p><p><strong>Methods: </strong>Four gene expression datasets from the Gene Expression Omnibus (GEO) database were integrated to form the GEO-Combined dataset. NPC and adjacent normal nasopharyngeal tissues comprising the Test_Data were subjected to RNA sequencing. The differentially expressed genes (DEGs) from the GEO-Combined and Test_Data datasets were screened. DEGs associated with anoikis were identified and termed as ARDEGs. The key genes were validated by quantitative real-time polymerase chain reaction (qRT-PCR).</p><p><strong>Results: </strong>A total of 104 ARDEGs were identified in our study. Five key genes (i.e., <i>PLAUR</i>, <i>PTGS2</i>, <i>SERPINE1</i>, <i>CHI3L1</i>, and <i>ITGAV</i>) were identified using the random forest (RF) and least absolute shrinkage and selection operator (LASSO) algorithms. A nomogram based on these five key genes showed robust diagnostic performance, with the area under the curve (AUC) underscoring its utility as a prognostic tool. Further, the functional enrichment analysis indicated that the risk model was associated with the biological pathways involved in tumor migration and invasion. Based on the model constructed from the five key genes, our study found 152 pairs of messenger RNA (mRNA)-transcription factor (TF) interaction relationships, which may provide insights into the mechanisms of metastasis and recurrence of NPC.</p><p><strong>Conclusions: </strong>The identification and validation of ARDEGs in NPC highlighted critical molecular players in anoikis resistance, offering potential targets for therapeutic interventions. Our study provides a comprehensive understanding of the role of ARDEGs in NPC, paving the way for further research into targeted therapies for NPC.</p>","PeriodicalId":23216,"journal":{"name":"Translational cancer research","volume":"14 7","pages":"4429-4446"},"PeriodicalIF":1.7,"publicationDate":"2025-07-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12335718/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144822694","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Integrative single-cell and bulk transcriptomic analyses identify a robust four-gene signature for risk stratification in neuroblastoma.","authors":"Zhanbo Wu, Ningning Sun, Yinan Dong, Li Zhang, Jifeng Sun, Xin Li, Runmei Li","doi":"10.21037/tcr-2025-569","DOIUrl":"10.21037/tcr-2025-569","url":null,"abstract":"&lt;p&gt;&lt;strong&gt;Background: &lt;/strong&gt;Neuroblastoma (NB) is a heterogeneous pediatric malignancy with highly variable outcomes. Traditional clinical factors, such as stage, MYCN status, and patient age, often fail to fully capture disease complexity. Recent advances in single-cell sequencing and integrative transcriptomic analyses provide an opportunity to identify more precise prognostic biomarkers and guide individualized therapies. This study aimed to develop and validate a robust prognostic model for NB by integrating single-cell and bulk transcriptomic data.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Methods: &lt;/strong&gt;We integrated seven publicly available single-cell RNA sequencing (scRNA-seq) datasets to form the Neuroblastoma Atlas and stratified tumor cells into high-risk and intermediate/low-risk groups. Differentially expressed genes (DEGs) were identified using defined fold-change and expression thresholds. Candidate genes were further validated using bulk RNA-sequencing data (HRA002064) and intersected with essential genes defined by DepMap Computational estimation of gene dependency using Clustered Regularly Interspaced Short Palindromic Repeats (CRISPR) screening (CERES) scores. From the resulting set, we constructed a multivariate Cox regression-based prognostic model using the GSE49710 dataset. The model's performance was evaluated via Kaplan-Meier curves, time-dependent receiver operating characteristic analysis, and decision curve analysis. External validation was performed in the E-MTAB-8248 dataset, and comparisons with standard clinical indicators (International Neuroblastoma Staging System, MYCN status, age) were conducted.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Results: &lt;/strong&gt;Integrating scRNA-seq and bulk RNA-seq data identified 123 overlapping DEGs, of which seven genes (&lt;i&gt;BIRC5&lt;/i&gt;, &lt;i&gt;CDC2&lt;/i&gt;, &lt;i&gt;GINS2&lt;/i&gt;, &lt;i&gt;MAD2L1&lt;/i&gt;, &lt;i&gt;ORC6L&lt;/i&gt;, &lt;i&gt;RRM2&lt;/i&gt;, &lt;i&gt;TOP2A&lt;/i&gt;) were further prioritized based on CERES dependency scores. Multivariate Cox regression and collinearity screening yielded a four-gene prognostic model (RiskScore) that significantly discriminated high- and low-risk patients in the GSE49710 cohort. Compared to traditional indicators, the four-gene model demonstrated superior time-dependent area under the curve (AUC) values and clinical decision-making benefits. External validation in E-MTAB-8248 confirmed the model's robust predictive performance, with high AUC values at 1-, 3-, and 5-year time points and consistent superiority over clinical parameters.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Conclusions: &lt;/strong&gt;This study presents a novel four-gene prognostic signature derived from integrative scRNA-seq and bulk RNA-seq analyses. The model outperforms established clinical factors in predicting NB outcomes and provides added clinical decision-making value. Further prospective validation and mechanistic investigations may facilitate the translation of this prognostic signature into routine clinical practice, enabling more refined risk stratification and personalized treatment strategies for","PeriodicalId":23216,"journal":{"name":"Translational cancer research","volume":"14 7","pages":"3920-3929"},"PeriodicalIF":1.7,"publicationDate":"2025-07-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12335703/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144822700","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Efficacy of transcatheter arterial chemoembolization-based multimodal treatment in patients with neuroendocrine tumors involving the liver.","authors":"Hu Xu, Li Zhang, Juan Zhang, Yi Chen, Ningling Ge, Yuhong Gan, Rongxin Chen, Maopei Chen","doi":"10.21037/tcr-2024-2482","DOIUrl":"10.21037/tcr-2024-2482","url":null,"abstract":"<p><strong>Background: </strong>Neuroendocrine tumors (NETs) are a group of heterogeneous diseases which have liver dominant involvement potency. The value of transcatheter arterial chemoembolization (TACE) treatment for NET patients in the era of somatostatin analogues (SSAs) and anti-proliferation agents needs further study. The study aimed to investigate the value of TACE-based treatment for NETs involving the liver.</p><p><strong>Methods: </strong>A group of 29 NET patients received TACE-based multimodal treatment in the Department of Hepatic Oncology of Zhongshan Hospital, Fudan University was retrospectively collected. Baseline characteristics of included patients were analyzed. Kaplan-Meier analysis and Cox proportional hazards regression were used to investigate clinical and pathological parameters on overall survival (OS) and progression free-survival (PFS) in NET patients.</p><p><strong>Results: </strong>The median OS and PFS were 20.0 [95% confidence interval (CI): 13.4-26.5] months and 11.0 (95% CI: 7.7-14.3) months, respectively. Tumor grade (P=0.001), number of TACE treatments (P=0.003), neutrophil to lymphocyte ratio (NLR) (P=0.005) and systemic treatment mode (P=0.007) were significantly associated with OS while tumor grade (P<0.001), number of TACE treatments (P=0.002), aspartate aminotransferase (AST) (P=0.01) and systemic treatment mode (P=0.001) were of significance to PFS in multivariate Cox regression analyses.</p><p><strong>Conclusions: </strong>TACE-based multimodal treatment is beneficial for NETs involving the liver. The sequence and timing of local treatment and systemic treatment allocation need further investigation.</p>","PeriodicalId":23216,"journal":{"name":"Translational cancer research","volume":"14 7","pages":"4321-4330"},"PeriodicalIF":1.7,"publicationDate":"2025-07-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12335680/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144822706","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}