Translational cancer research最新文献

{"title":"Overexpression of miR-1283 inhibits cell proliferation and migration of colorectal cancer cells by targeting PDZD8.","authors":"Zhen Wang, Xiang Li, Huan Zhou, Enda Yu, Xiaohong Yang","doi":"10.21037/tcr-2025-291","DOIUrl":"10.21037/tcr-2025-291","url":null,"abstract":"<p><strong>Background: </strong>PDZ domain-containing protein 8 (PDZD8) has been implicated in the progression of colorectal cancer. However, its regulatory mechanisms and functional impact remain to be fully elucidated. We assessed PDZD8 expression in colorectal cancer cell lines and normal colorectal mucosa using Real-time quantitative reverse transcription-polymerase chain reaction (qRT-PCR).</p><p><strong>Methods: </strong>The role of PDZD8 in colorectal cancer was further investigated through the generation of PDZD8-depleted HCT 116 and RKO cell models via short hairpin RNA (shRNA) interference. The influence of PDZD8 knockdown on cellular phenotypes was examined through proliferation, migration, apoptosis, and cell cycle assays. Additionally, the regulatory effect of miR-1283 on PDZD8 was explored both <i>in vitro</i> and <i>in vivo</i>.</p><p><strong>Results: </strong>PDZD8 messenger RNA (mRNA) expression was significantly upregulated in colorectal cancer cell lines compared to normal mucosa, with the highest expression in RKO and HCT 116 cells. PDZD8 knockdown impeded cell proliferation and migration while promoting apoptosis and cell cycle arrest <i>in vitro</i>. Bioinformatics analysis and dual-luciferase assays confirmed miR-1283 as a negative regulator of PDZD8. <i>In vitro</i> and <i>in vivo</i>, PDZD8 overexpression modulated cell viability and migration, increased tumor volume and weight in nude mice, and miR-1283 overexpression counteracted the pro-oncogenic effects of PDZD8.</p><p><strong>Conclusions: </strong>Our findings revealed that PDZD8 was a critical promoter of malignant phenotypes in colorectal cancer, and its expression was negatively regulated by miR-1283. Targeting the PDZD8/miR-1283 axis may offer a therapeutic strategy for colorectal cancer.</p>","PeriodicalId":23216,"journal":{"name":"Translational cancer research","volume":"14 8","pages":"4549-4560"},"PeriodicalIF":1.7,"publicationDate":"2025-08-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12432640/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145065584","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":"Comparisons of the efficacy of different Chinese medicine injections on immune function in patients with nasopharyngeal carcinoma during combined therapy: a systematic review and network meta-analysis.","authors":"Zhaohui Gu, Tian Zhang, Xinyue Chen","doi":"10.21037/tcr-2025-1479","DOIUrl":"10.21037/tcr-2025-1479","url":null,"abstract":"&lt;p&gt;&lt;strong&gt;Background: &lt;/strong&gt;Studies have demonstrated the safety and efficacy of traditional Chinese medicine (TCM) injections combined with concurrent chemoradiotherapy (CCRT) in patients with nasopharyngeal carcinoma (NPC). Although studies have examined the impact on immune function, direct comparisons of the effects of various TCM injections on immune function remain limited. Thus, a Bayesian network meta-analysis (NMA) was conducted to assess the beneficial effects of different TCM injections on immune function in patients with NPC during CCRT.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Methods: &lt;/strong&gt;The PubMed, Embase, Cochrane Library, Web of Science, China National Knowledge Infrastructure (CNKI), Wanfang, Weipu, and China Biology Medicine disc (CBM) databases were searched up to February 2025. The key inclusion criteria incorporated-(I) study subjects: individuals with clinically and pathologically confirmed NPC; (II) the control group received CCRT, and the study group received TCM injections combined with CCRT. The TCM injections of interest were Aidi (AD), Fufangkushen (FFKS), Kushensu (KSS), Shenqifuzheng (SQFZ), Lanxiangxi (LXX), etc.; (III) study type: a randomized controlled trial (RCT); (IV) outcome indicators: CD3&lt;sup&gt;+&lt;/sup&gt;, CD4&lt;sup&gt;+&lt;/sup&gt;, CD8&lt;sup&gt;+&lt;/sup&gt;, CD4&lt;sup&gt;+&lt;/sup&gt;/CD8&lt;sup&gt;+&lt;/sup&gt;. Two researchers independently screened and extracted the data according to the eligibility criteria. The quality of studies was assessed via the Cochrane Risk of Bias Assessment Tool 2.0 (ROB 2.0). Bayesian NMA was conducted with R version 4.3.3 and Stata 15.1.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Results: &lt;/strong&gt;This NMA encompassed 11 eligible articles involving 983 patients (496 in the CCRT + TCM injection group and 487 in the CCRT group). Seven TCM injections and four outcome indicators were considered. Due to the inability to implement blinding, all included articles presented a low risk of bias. The results demonstrated that AD injection was the most effective in improving CD3&lt;sup&gt;+&lt;/sup&gt; [surface under the cumulative ranking curve (SUCRA) 96.50%] and CD4&lt;sup&gt;+&lt;/sup&gt; (SUCRA 96.51%). KSS injection was the most effective in improving CD8&lt;sup&gt;+&lt;/sup&gt; (SUCRA 83.51%) and improving the CD4&lt;sup&gt;+&lt;/sup&gt;:CD8&lt;sup&gt;+&lt;/sup&gt; ratio (SUCRA 82.80%). Sensitivity analysis indicated stable results.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Conclusions: &lt;/strong&gt;This NMA demonstrated that TCM injections significantly increased the levels of peripheral blood CD3&lt;sup&gt;+&lt;/sup&gt; and CD4&lt;sup&gt;+&lt;/sup&gt; T-lymphocyte subpopulations during CCRT in patients with NPC. This may reduce the risk of patient infection. Furthermore, TCM injections improved CD8&lt;sup&gt;+&lt;/sup&gt; levels and the CD4&lt;sup&gt;+&lt;/sup&gt;:CD8&lt;sup&gt;+&lt;/sup&gt; ratio to some extent. These results suggest enhanced tumor immunosurveillance, potentially leading to improved patient survival. Among the injections, AD and KSS injections exhibited the most significant immune benefits for patients. However, due to the limited number and quality of included articles, further high-quality RCTs are","PeriodicalId":23216,"journal":{"name":"Translational cancer research","volume":"14 8","pages":"5059-5076"},"PeriodicalIF":1.7,"publicationDate":"2025-08-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12432771/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145065603","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":"Machine learning-based prognosis prediction for serous ovarian cancer using the SEER database and data from a single center in China.","authors":"Huan Chen, Yuexing Zhao, Qian Sun, Pei Jiao","doi":"10.21037/tcr-2025-540","DOIUrl":"10.21037/tcr-2025-540","url":null,"abstract":"<p><strong>Background: </strong>Ovarian cancer, particularly serous ovarian cancer, is the leading cause of death among gynecological malignancies. Despite advances in treatment, prognosis remains poor due to the tumor's heterogeneity and the frequent late-stage diagnosis, making survival a critical concern for patients. However, there is a lack of accurate clinical prognostic models to guide treatment decisions. Therefore, this study aimed to develop and validate a robust prognostic model for serous ovarian cancer using machine learning.</p><p><strong>Methods: </strong>Data for this study were obtained from the Surveillance, Epidemiology, and End Results (SEER) database (2010-2021) and Yancheng Dafeng People's Hospital (2012-2020). We used univariate and multivariate Cox regression analyses to identify independent risk factors and constructed a Light Gradient Boosting Machine (LightGBM) model with 10-fold cross-validation and hyperparameter tuning. The model's performance was evaluated using area under the receiver operating characteristic curve (ROC-AUC), feature importance rankings, and confusion matrices.</p><p><strong>Results: </strong>A total of 7,916 cases from the SEER database and 163 cases from Yancheng Dafeng People's Hospital were included in the analysis. The LightGBM model outperformed other machine learning models, with ROC-AUC values of 0.902 [95% confidence interval (CI): 0.881-0.923], 0.863 (95% CI: 0.841-0.886), 0.814 (95% CI: 0.794-0.835), and 0.816 (95% CI: 0.796-0.835) at 6, 12, 24, and 36 months, respectively, in the test set. Additionally, the model maintained robust performance in external validation, with ROC-AUC values of 0.821 (95% CI: 0.718-0.923), 0.785 (95% CI: 0.698-0.871), 0.745 (95% CI: 0.669-0.821), and 0.790 (95% CI: 0.722-0.858) at 6, 12, 24, and 36 months, respectively. We also identified surgery as the most significant predictor of survival, followed by chemotherapy, in ovarian cancer patients.</p><p><strong>Conclusions: </strong>We utilized the LightGBM model to predict survival in ovarian cancer patients, demonstrating excellent prognostic accuracy and high reproducibility. This model provides a valuable tool for guiding clinical decision-making and optimizing treatment strategies. Future research is needed to further validate its applicability across different populations.</p>","PeriodicalId":23216,"journal":{"name":"Translational cancer research","volume":"14 8","pages":"4703-4719"},"PeriodicalIF":1.7,"publicationDate":"2025-08-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12432648/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145065605","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":"Diagnostic value of circulating tumor cells in gastric cancer: a systematic review and meta-analysis.","authors":"Kang Yang, Peiwen Ouyang, Ke Gao, Zhaohui Duan","doi":"10.21037/tcr-2025-565","DOIUrl":"10.21037/tcr-2025-565","url":null,"abstract":"<p><strong>Background: </strong>In order to find new biomarkers related to gastric cancer diagnosis, in recent years, some researchers have confirmed that circulating tumor cells (CTCs) can be used in the diagnosis of gastric cancer, but the results are inconsistent among studies. In this study, we used meta-analysis to systematically evaluate the diagnostic value of CTCs for gastric cancer.</p><p><strong>Methods: </strong>A comprehensive search was carried out using the following databases: PubMed, Embase, Cochrane Library, Web of Science, Ovid MEDLINE, Scopus, China National Knowledge Infrastructure (CNKI), Wanfang, Weipu Chinese database, Chinese Biomedical Literature (CBM) database, and Duxiu database. The aim of this extensive search was to find published studies that investigated the role of CTCs in the diagnosis of gastric cancer, especially in patients with both gastric and non-gastric cancer. The search spanned from the inception of each database to January 30, 2025. Subsequently, eligible studies underwent a stringent screening process. They were evaluated according to a set of pre-determined literature inclusion and exclusion criteria. The quality of the included literature was appraised using the Quality Assessment of Diagnostic Accuracy Studies-2 (QUADAS-2) scale, a tool developed to assess the quality of studies in the area of cancer research. Relevant data were then extracted, and a meta-analysis of the included studies was conducted using MetaDiSc 1.4 and Stata 16.0 software.</p><p><strong>Results: </strong>A total of 18 papers were included in this study, encompassing 1,399 gastric cancer patients and 750 non-gastric cancer controls. Meta-analysis indicated that the heterogeneity of the included papers was due to a non-threshold effect. Meta-regression analysis revealed that the identification of the test method might be the main source of heterogeneity. The random-effects model analysis showed that the combined sensitivity of the cell-based CTC test for diagnosing gastric cancer was 0.78 [95% confidence interval (CI): 0.76-0.80], the combined specificity was 0.93 (95% CI: 0.91-0.94), the combined positive likelihood ratio (PLR) was 9.13 (95% CI: 6.36-13.12), the combined negative likelihood ratio (NLR) was 0.24 (95% CI: 0.18-0.33), and the diagnostic odds ratio (DOR) was 43.83 (95% CI: 27.12-70.84). The area under the summary receiver operating characteristic (sROC) curve (AUC) was 0.9274, and the Q* value was 0.8621. Regarding sensitivity analyses, the results of this study were relatively stable, and the diagnostic test Deeks funnel plot demonstrated that there was no publication bias in this study.</p><p><strong>Conclusions: </strong>CTCs have relatively high sensitivity, specificity and accuracy in the diagnosis of gastric cancer patients, which has certain value for the clinical diagnosis of gastric cancer.</p>","PeriodicalId":23216,"journal":{"name":"Translational cancer research","volume":"14 8","pages":"4791-4803"},"PeriodicalIF":1.7,"publicationDate":"2025-08-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12432790/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145065098","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":"Diagnostic accuracy of SHOX-2 methylation for malignant pleural effusion: a systematic review and meta-analysis.","authors":"Hao-Jie Wang, Jian-Ying Cui, Wen-Jie Hou, Xu-Lei Hao, Wen-Qi Zheng, Zhi-De Hu, Xi-Shan Cao, Li Yan","doi":"10.21037/tcr-2025-686","DOIUrl":"10.21037/tcr-2025-686","url":null,"abstract":"<p><strong>Background: </strong>Some studies have assessed the diagnostic value of SHOX-2 methylation for malignant pleural effusion (MPE), but their findings were inconsistent. This study aimed to conduct a systematic review and meta-analysis to evaluate the diagnostic accuracy of SHOX-2 methylation for MPE.</p><p><strong>Methods: </strong>We searched the PubMed and Web of Science databases to identify studies involving SHOX-2 methylation in diagnosing MPE. The last search date was in December 2024. We evaluated the quality of the included studies using the revised Quality Assessment of Diagnostic Accuracy Studies tool-2 (QUADAS-2). A bivariate model was used to pool the sensitivity, specificity, and their 95% confidence intervals (CIs) of SHOX-2 methylation. The overall diagnostic accuracy of SHOX-2 methylation was assessed by a summary receiver operating characteristic (sROC) curve. The publication bias was analyzed using Deek's test.</p><p><strong>Results: </strong>Six studies with 613 MPE patients and 723 benign pleural effusion (BPE) patients were included. The pooled sensitivity (95% CI) and specificity (95% CI) of SHOX-2 methylation were 0.64 (0.36-0.85) and 0.96 (0.92-0.98), respectively. The area under the sROC curve was 0.96 (95% CI: 0.94-0.97). There was no publication bias across the eligible studies.</p><p><strong>Conclusions: </strong>SHOX-2 methylation has a moderate diagnostic value for MPE.</p>","PeriodicalId":23216,"journal":{"name":"Translational cancer research","volume":"14 8","pages":"4955-4964"},"PeriodicalIF":1.7,"publicationDate":"2025-08-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12432786/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145065101","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":"Unveiling prognostic factors and predictive modeling in lung adenocarcinoma with neuroendocrine differentiation.","authors":"Wei Li, Yuanming Pan, Siyu Cai, Shenglong Xie, Bin He","doi":"10.21037/tcr-2025-12","DOIUrl":"10.21037/tcr-2025-12","url":null,"abstract":"<p><strong>Background: </strong>Some lung cancer patients are pathologically confirmed to have lung adenocarcinoma with neuroendocrine differentiation (LUAD-ND). However, research on this subtype remains limited. This study aimed to systematically investigate the metastatic patterns and prognosis-related factors of LUAD-ND, and construct neural network-based prediction models for survival outcomes.</p><p><strong>Methods: </strong>By analyzing the Surveillance, Epidemiology, and End Results (SEER) database, we employed the Cox proportional hazards model to investigate prognostic factors for overall survival (OS) and cancer-specific survival (CSS) in patients with LUAD-ND. We calculated hazard ratios (HRs) and 95% confidence intervals (CIs) and detailed the median survival time and specific time survival probabilities for different features in the LUAD-ND population. Finally, using a neural network algorithm, we developed a predictive model for forecasting LUAD-ND's OS and CSS, evaluating its performance using the area under the receiver operating characteristic curve (AUC).</p><p><strong>Results: </strong>Most patients with LUAD-ND were diagnosed at an advanced stage. The OS time of patients with LUAD-ND was 12 (95% CI: 10-14) months, and the CSS time was 14 (95% CI: 12-16) months. The most common distant metastatic sites were bone, followed by liver, brain, and lung. Surgery (HR =0.51; 95% CI: 0.31-0.82; P=0.006) and chemotherapy (HR =0.33; 95% CI: 0.21-0.50; P<0.001) were associated with improved OS. Similarly, surgery (HR =0.49; 95% CI: 0.28-0.84; P=0.01) and chemotherapy (HR =0.31; 95% CI: 0.19-0.49; P<0.001) were linked to better CSS. The neural network-based tool can effectively predict the prognosis of LUAD-ND, achieving an AUC of 0.852-0.864 for 6-month OS and 0.835-0.883 for 6-month CSS.</p><p><strong>Conclusions: </strong>Patients with LUAD-ND face a dismal prognosis, yet chemotherapy and surgical interventions can ameliorate their outcomes. The neural network tool developed in this study yields precise prognostic estimations.</p>","PeriodicalId":23216,"journal":{"name":"Translational cancer research","volume":"14 8","pages":"4649-4661"},"PeriodicalIF":1.7,"publicationDate":"2025-08-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12432600/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145065222","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":"Classification of chemoradiotherapy sensitivity in hypopharyngeal squamous cell carcinoma based on deep-learning and radiomics feature fusion.","authors":"Hengmin Tao, Xinbo Yang, Meihui Chen, Baosheng Li","doi":"10.21037/tcr-2025-1628","DOIUrl":"10.21037/tcr-2025-1628","url":null,"abstract":"<p><strong>Background: </strong>Analyzing apparent diffusion coefficient (ADC) images before chemoradiotherapy (CRT) can effectively predict the treatment response of patients with hypopharyngeal squamous cell carcinoma (HPSCC), thereby reducing the treatment risks. This study aimed to develop a predictive model by combining deep-learning features and radiomics features derived from ADC images to predict the CRT sensitivity of HPSCC patients, providing effective guidance for treatment strategy selection.</p><p><strong>Methods: </strong>This study retrospectively analyzed the data of 120 HPSCC patients. Deep-learning features were extracted from ADC images using a vision transformer (ViT)-based deep-learning model, while radiomics features were extracted using the PyRadiomics feature extractor. Among the 1,288 extracted radiomics features, the most significant ones were selected using the Spearman's correlation coefficient, intraclass correlation coefficient (ICC), and least absolute shrinkage and selection operator (LASSO) method. These features were fused through a concatenation approach, and a classification prediction was performed using a convolutional neural network with three fully connected layers.</p><p><strong>Results: </strong>The accuracy, sensitivity, specificity, and area under the curve (AUC) values of the feature fusion model were 0.99 <i>vs</i>. 0.875, 0.988 <i>vs</i>. 0.842, 1.000 <i>vs</i>. 1.000, and 1.000 <i>vs</i>. 0.947, for the training and validation datasets, respectively. The feature fusion model performed optimally in comparison to the other models. In the validation dataset, the accuracy of the feature fusion model improved by 16.7% and 4.2% compared to the clinical and radiomic models, respectively.</p><p><strong>Conclusions: </strong>The model developed in this study, which integrates deep-learning features with traditional radiomics features, can accurately predict the CRT sensitivity of HPSCC patients using pre-treatment ADC images. This model provides an effective reference for selecting optimal treatment strategies for patients.</p>","PeriodicalId":23216,"journal":{"name":"Translational cancer research","volume":"14 8","pages":"5142-5154"},"PeriodicalIF":1.7,"publicationDate":"2025-08-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12432764/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145065614","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":"<i>ISG20L2</i> as a driver in the proliferation and invasion of lung adenocarcinoma via <i>NKX2-1</i> regulation.","authors":"Xiaoming Fang, Xinyu Zhang, Ping Liu, Dan Yu, Andrzej Swierniak, Carl G Maki, Ruichen Gao, Ming Liu","doi":"10.21037/tcr-2025-1546","DOIUrl":"10.21037/tcr-2025-1546","url":null,"abstract":"<p><strong>Background: </strong>Interferon-stimulated 20-kDa exonuclease-like 2 (<i>ISG20L2</i>) is a gene that shows variable expression levels in lung adenocarcinoma (LUAD). Despite this, its role and expression in LUAD have not been well characterized. This study focused on analyzing the expression of <i>ISG20L2</i> in LUAD, its association with patient prognosis, and its potential regulatory influence on NK2 homeobox 1 (<i>NKX2-1</i>) in LUAD cells.</p><p><strong>Methods: </strong>We used The Cancer Genome Atlas (TCGA) database and immunohistochemistry to assess the expression of <i>ISG20L2</i>. Kaplan-Meier survival analysis was employed to determine the relationship between <i>ISG20L2</i> expression and prognosis in patients with LUAD. The diagnostic potential of <i>ISG20L2</i> in LUAD was evaluated through receiving operating characteristic curve analysis. The association between <i>ISG20L2</i> expression and clinicopathological features was analyzed with the Fisher exact test. Overexpression and depletion studies of <i>ISG20L2</i> were performed via transient transfection. The biological functions of <i>ISG20L2</i> in A549 cells, such as cell proliferation, apoptosis, migration, and invasion, were examined via Cell Counting Kit-8 (CCK-8), flow cytometry, and Transwell assays. Bioinformatics analysis suggested a link between <i>ISG20L2</i> and <i>NKX2-1</i>, which was subsequently confirmed through cytological experiments.</p><p><strong>Results: </strong>Our results demonstrated that <i>ISG20L2</i> was overexpressed in LUAD, and this overexpression was significantly correlated with poor prognosis. <i>In vitro</i> experiments further supported a positive association between <i>ISG20L2</i> expression and the proliferative, migratory, and invasive capabilities in A549 cells, with no notable effect on apoptosis. Functional assays confirmed that <i>ISG20L2</i> enhanced A549 cell proliferation and invasion by modulating <i>NKX2-1</i>.</p><p><strong>Conclusions: </strong><i>ISG20L2</i> promotes LUAD progression via <i>NKX2-1</i> regulation, implying the potential of the <i>ISG20L2/NKX2-1</i> axis as a candidate biomarker and therapeutic target in LUAD.</p>","PeriodicalId":23216,"journal":{"name":"Translational cancer research","volume":"14 8","pages":"5028-5044"},"PeriodicalIF":1.7,"publicationDate":"2025-08-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12432785/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145065558","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 of metabolic driver genes and targeted drug screening for lung adenocarcinoma metastasis at the single-cell resolution.","authors":"Liang Wu, Wenjuan Zhao, Xin Guo, Zuquan Hu, Sen Chen, Wenzhu Huang","doi":"10.21037/tcr-2025-484","DOIUrl":"10.21037/tcr-2025-484","url":null,"abstract":"<p><strong>Background: </strong>Lung adenocarcinoma (LUAD) is the predominant type of lung cancer, and metastasis is a major cause of poor prognosis and death. Metabolic activation is a crucial factor driving tumor metastasis; however, the metabolic heterogeneity at the single-cell level presents significant challenges in targeting metabolism-related genes for treatment. This study aimed to decode the metabolic drivers in tumor metastasis progression to optimize LUAD prognosis prediction and screen specific targeted drugs.</p><p><strong>Methods: </strong>In this study, we determined that the metabolic activation of tumor and immune cells in the microenvironment is significantly altered during LUAD metastasis. Simultaneously, we identify pivotal metabolic driver genes (MDGs) based on single-cell RNA-sequencing (scRNA-seq) data, which could serve as targets for targeted therapy. We then constructed a novel prognostic risk model based on MDGs and validated its excellent predictive performance in independent datasets. Using the non-negative matrix factorization (NMF) algorithm, we classify LUAD molecular subtypes into three clusters according to MDGs and evaluate their association with prognosis and clinical characteristics.</p><p><strong>Results: </strong>We screened a panel of 307 drugs targeting MDGs and confirmed the efficacy of cholic acid, as a representative compound from the screened panel, in inhibiting the migration of LUAD cells.</p><p><strong>Conclusions: </strong>Our research provides potential targets and candidate drug for targeting metabolic-related genes in metastatic LUAD treatment.</p>","PeriodicalId":23216,"journal":{"name":"Translational cancer research","volume":"14 8","pages":"4774-4790"},"PeriodicalIF":1.7,"publicationDate":"2025-08-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12432774/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145065560","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":"Transarterial chemoembolization combined with tyrosine kinase inhibitors and programmed death receptor-1 inhibitors for unresectable hepatocellular carcinoma: a systematic review and meta-analysis.","authors":"Yonghong He, Yuexi Liu, Jie Xu, Yanan He","doi":"10.21037/tcr-2025-798","DOIUrl":"10.21037/tcr-2025-798","url":null,"abstract":"<p><strong>Background: </strong>More than 60% of patients with hepatocellular carcinoma (HCC) are diagnosed at the intermediate-advanced stages, which are not amenable to surgical resection and ablation. The optimal treatment plan for patients with unresectable HCC remains controversial. This study aimed to evaluate the efficacy and safety of transarterial chemoembolization (TACE) combined with tyrosine kinase inhibitors (TKI) plus programmed death receptor-1 (PD-1) inhibitors (TACE + TKI + PD-1) versus TACE combined with TKI (TACE + TKI) among patients with unresectable HCC.</p><p><strong>Methods: </strong>A comprehensive search of the PubMed, EMBASE and the Cochrane Library databases was performed, and all studies related to TACE + TKI + PD-1 and TACE + TKI for treatment of HCC were included. We calculated risk ratio (RR) and mean difference for dichotomous and continuous outcomes. Data were analyzed using RevMan5.4 and Stata 17.0. We conducted a subgroup analysis based on specific types of TKI.</p><p><strong>Results: </strong>A total of 12 retrospective studies were included in the analysis, involving 1,078 patients in the TACE + TKI + PD-1 group and 1,332 in the TACE + TKI group. Compared with the TACE + TKI group, the TACE + TKI + PD-1 group showed prolonged overall survival [RR =7.39, 95% confidence interval (CI): 5.69-9.08, P<0.001, I²=90%], progression-free survival (RR =3.89, 95% CI: 3.21-4.57, P<0.001, I²=81%)and higher objective response rate (RR =1.38, 95% CI: 1.26-1.51, P<0.001, I²=49%). Similarly, the 1-year survival rate improved (RR =5.92, 95% CI: 4.43-5.92, P<0.001, I²=11%) in the TACE + TKI + PD-1 group. No significant difference was found in adverse events between the two groups.</p><p><strong>Conclusions: </strong>TACE + TKI + PD-1 significantly improved survival outcomes and demonstrated superior efficacy and a manageable safety profile in the systemic treatment of patients with unresectable HCC.</p>","PeriodicalId":23216,"journal":{"name":"Translational cancer research","volume":"14 8","pages":"4976-4988"},"PeriodicalIF":1.7,"publicationDate":"2025-08-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12432782/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145064826","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}