Translational cancer research最新文献

{"title":"Development and validation of a prediction model based on two-dimensional dose distribution maps fused with computed tomography images for noninvasive prediction of radiochemotherapy resistance in non-small cell lung cancer.","authors":"Min Zhang, Ya Li, Yong Hu, Bo Du, Youlong Mo, Tianchu He, Yang Yang, Benlan Li, Ji Xia, Zhongjun Huang, Fangyang Lu, Bing Lu, Jie Peng","doi":"10.21037/tcr-24-1897","DOIUrl":"https://doi.org/10.21037/tcr-24-1897","url":null,"abstract":"<p><strong>Background: </strong>There are individualized differences in the prognosis of radiochemotherapy for non-small cell lung cancer (NSCLC), and accurate prediction of prognosis is essential for individualized treatment. This study proposes to explore the potential of multiregional two-dimensional (2D) dosiomics combined with radiomics as a new imaging marker for prognostic risk stratification of NSCLC patients receiving radiochemotherapy.</p><p><strong>Methods: </strong>In this study, 365 patients with histologically confirmed NSCLC, who had computed tomography (CT) scans before treatment, received standard radiochemotherapy, and had Karnofsky Performance Scale (KPS) scores ≥70 were included in three medical institutions, and 145 cases were excluded due to surgery, data accuracy, poor image quality, and the presence of other tumors. Finally, 220 patients were included in the study. Efficacy evaluation criteria for solid tumors are used to evaluate efficacy. Complete and partial remission indicate the radiochemotherapy-sensitive group, and disease stability and progression indicate the radiochemotherapy-resistant group. We combined all the data and then randomised them into a training cohort (154 cases) and a validation cohort (66 cases) in a 7:3 ratio. Radiomics and dosiomics features were extracted for gross tumor volume (GTV), GTV-heat, and 50 Gy-heat and screened. 2D dosiomics model (DM<sub>GTV</sub> and DM<sub>50Gy</sub>), radiomics model (RM<sub>GTV</sub>), 2D radiomics-dosiomics model (RDM), and combined models were constructed, and the predictive performances for radiochemotherapy resistance were compared. Subsequently, the predictive performance of various models for radiochemotherapy resistance was compared by receiver operating characteristic (ROC) curves and calculating accuracy, sensitivity and specificity. The multi-omics and clinical models were integrated for patient risk stratification.</p><p><strong>Results: </strong>DM<sub>50Gy</sub> had better predictive performance than RM<sub>GTV</sub> and DM<sub>GTV</sub>, with the area under the curve (AUC) of the ROC in the training and validation cohorts for DM<sub>50Gy</sub> were 0.764 [95% confidence interval (CI): 0.687-0.841] and 0.729 (95% CI: 0.568-0.889). And the RDM performed significantly better than the single radiomics and dosiomics models, with AUC of 0.836 (95% CI: 0.773-0.899) and 0.748 (95% CI: 0.617-0.879), respectively. Hemoglobin level and T stage were independent predictors in the clinical model. The combined model containing independent predictors further improved the predictive performance in both the training and validation cohorts, with AUC of 0.844 (95% CI: 0.781-0.907) and 0.753 (95% CI: 0.618-0.887). Grouping of patients according to the critical value of the combined model revealed significant differences in progression-free survival (PFS) and overall survival (OS) between the high-risk and low-risk groups (P<0.05).</p><p><strong>Conclusions: </strong>Com","PeriodicalId":23216,"journal":{"name":"Translational cancer research","volume":"14 3","pages":"1516-1530"},"PeriodicalIF":1.5,"publicationDate":"2025-03-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11985215/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144016204","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":"Scoparone suppresses proliferation and cell cycle of hepatocellular carcinoma cells via inhibiting AKT/GSK-3β/cyclin D1 signaling pathway.","authors":"Mei Hong, Hao Zhu, Weikang Liu, Pengyu Zhang, Song Yu, Quangen Gao, Genhai Shen, Bin Li, Gang Wang","doi":"10.21037/tcr-24-1771","DOIUrl":"https://doi.org/10.21037/tcr-24-1771","url":null,"abstract":"<p><strong>Background: </strong>Hepatocellular carcinoma (HCC) ranks as the sixth most prevalent cancer and the fourth leading cause of cancer-related mortality globally. Scoparone, a natural coumarin derivative primarily derived from Artemisia Capillaris Thunb, has demonstrated antitumor properties across various cancer types. However, its functions in HCC have not been clearly elucidated. This study aimed to investigate the antitumor effects of scoparone on the MHCC-97L and HCCC-9810 HCC cell lines.</p><p><strong>Methods: </strong>Cell proliferation was assessed through viability and colony formation assays. Migration and invasion capabilities of the cells were evaluated by wound healing assays and Transwell assays. Additionally, transcriptome sequencing and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis were conducted to uncover pathways linked to gene enrichment in the artemisinin treatment group. Western blotting and flow cytometry were utilized to analyze the expression of mechanistic proteins associated with artemisinin treatment in HCC.</p><p><strong>Results: </strong>Our findings revealed that scoparone effectively inhibited the proliferation, migration, and invasion of HCC cells. The genes affected by scoparone treatment were predominantly enriched in pathways related to the cell cycle. Specifically, scoparone reduced the expression of genes such as <i>CDK2, CDK3, CDK4, CDC25A, CCND1</i>, and <i>CCNE1</i>, while it increased the expression of <i>CDKN1A</i> (<i>p21</i>). Furthermore, scoparone suppressed the levels of cell cycle-related proteins CDK2, CDK4, and cyclin D1, along with the signaling pathways involving p-AKT and p-GSK-3β. Notably, the inhibitory effects of scoparone on HCC cell proliferation were partially reversed by the AKT activator, SC79.</p><p><strong>Conclusions: </strong>Scoparone inhibited HCC cell viability by targeting the AKT/GSK-3β/cyclin D1 pathway.</p>","PeriodicalId":23216,"journal":{"name":"Translational cancer research","volume":"14 3","pages":"1638-1650"},"PeriodicalIF":1.5,"publicationDate":"2025-03-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11985190/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144045052","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":"Radiomics-clinical nomogram for preoperative tumor-node-metastasis staging prediction in breast cancer patients using dynamic enhanced magnetic resonance imaging.","authors":"Zhe Yang, Shouen Wang, Wei Yin, Ying Wang, Fanghua Liu, Jianshu Xu, Long Han, Chenglong Liu","doi":"10.21037/tcr-24-1559","DOIUrl":"https://doi.org/10.21037/tcr-24-1559","url":null,"abstract":"<p><strong>Background: </strong>Breast cancer is one of the most commonly diagnosed malignancies in women worldwide, and the disease burden continues to aggravate. The tumor-node-metastasis (TNM) staging information is crucial for oncology physicians to develop appropriate clinical strategies. This study aimed to investigate the value of a radiomics-clinical model for predicting TNM stage in breast cancer patients using dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI).</p><p><strong>Methods: </strong>DCE-MRI images from 166 patients with pathologically confirmed breast cancer were retrospectively collected, including early stage (TNM0-TNM2) and locally advanced or advanced stage (TNM3-TNM4). Included patients were divided into a training cohort (n=116) and a test cohort (n=50). The radiomics, clinical and integrated models were constructed and a nomogram was established to distinguish the TNM0-TNM2 stage from the TNM3-TNM4 stage. Receiver operating characteristic (ROC) curves, calibration curves and decision curve analysis (DCA) were employed to assess the predictability of the models.</p><p><strong>Results: </strong>Eighty-five patients were at the early stages, while 81 patients were at the other stages. In the training and test cohorts, the area under the curve (AUC) values for distinguishing early and advanced breast cancer were 0.870 and 0.818 for the nomogram, respectively. The nomogram calibration curves showed good agreement between the predicted and observed TNM stages in the training and test cohorts. The Hosmer-Lemeshow test showed that the nomogram fit perfectly in the two cohorts. DCA indicated that the nomogram displayed clear superiority in forecasting TNM staging over clinical and radiomic signatures.</p><p><strong>Conclusions: </strong>Compared to traditional imaging methods, the clinical-radiomics nomogram acquired by DCE-MRI could potentially be utilized to preoperatively evaluate the TNM stage of breast cancer with relatively high accuracy. It can be an effective method to guide clinical decisions.</p>","PeriodicalId":23216,"journal":{"name":"Translational cancer research","volume":"14 3","pages":"1836-1848"},"PeriodicalIF":1.5,"publicationDate":"2025-03-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11985186/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144049663","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":"Triage of women with positive HPV: comparing DNA ploidy analysis with HPV 16/18 genotyping and cervical cytology.","authors":"Wei Song, Lan Zhu, Min Zheng, Hua Liu","doi":"10.21037/tcr-24-1455","DOIUrl":"https://doi.org/10.21037/tcr-24-1455","url":null,"abstract":"<p><strong>Background: </strong>Cervical cancer screening primarily uses the human papillomavirus (HPV) test with partial genotyping (HPV 16/18) and liquid-based cytology using ThinPrep cytology test (TCT) to triage women with a positive HPV test. Although quantitative DNA ploidy analysis has shown reliability, its integration into screening guidelines as a triage test, compared to partial genotyping and TCT, has not been fully established. The objective of the study is to evaluate the clinical utility of DNA ploidy analysis as a triage test for women with a positive HPV test in primary screening, comparing it to HPV 16/18 genotyping and TCT.</p><p><strong>Methods: </strong>We retrospectively analyzed data from 335 women aged ≥18 years who participated in a cervical cancer screening program at Shanghai Ruijin Hospital and underwent triage using HPV 16/18, TCT, and DNA ploidy testing. The sensitivities and specificities of these methods, both individually and combined, were evaluated.</p><p><strong>Results: </strong>The test showed sensitivities and specificities of 35.4% and 76.1% for HPV 16/18, 29.2% and 88.2% for TCT, and 93.8% and 92.7% for DNA ploidy, respectively. Combining these tests improved outcomes, with DNA ploidy plus HPV 16/18 genotyping showing enhanced sensitivity and high specificity. Notably, DNA ploidy alone identified high-grade squamous intraepithelial lesions (HSIL) and cervical cancer with a higher detection rate and lower positivity rate in triage than HPV 16/18 and TCT.</p><p><strong>Conclusions: </strong>DNA ploidy analysis demonstrated superior specificity and sensitivity in the triage of women with positive HPV test results, offering a more effective alternative for detecting high-grade lesions and cervical cancer. These findings support the potential of integrating DNA ploidy into current cervical cancer screening protocols to enhance triage effectiveness and reduce unnecessary colposcopy referrals.</p>","PeriodicalId":23216,"journal":{"name":"Translational cancer research","volume":"14 3","pages":"1664-1674"},"PeriodicalIF":1.5,"publicationDate":"2025-03-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11985189/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144042801","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":"Prediction of the prognosis of intrahepatic cholangiocarcinoma patients after hepatectomy via propensity score matching: a competitive risk model analysis.","authors":"Shu-Sen Jiang, Zhi-Yu Wang, Li-Jun Tan, Li-Xia Zhou, Xue-Yao Wang, Xin-Meng Han, Shun-Gang Li, Ji-Meng Luo, Hong-Bing Yao","doi":"10.21037/tcr-24-1819","DOIUrl":"https://doi.org/10.21037/tcr-24-1819","url":null,"abstract":"<p><strong>Background: </strong>Hepatectomy represents the cornerstone therapeutic approach for intrahepatic cholangiocarcinoma (ICCA); however, research pertaining to the prognosis of ICCA patients utilizing competing risk models remains scarce. This study aimed to construct a prognostic model utilizing competing risk analysis to predict cancer-specific survival (CSS) among ICCA patients posthepatectomy.</p><p><strong>Methods: </strong>This study retrospectively analyzed ICCA patients from the Surveillance, Epidemiology, and End Results (SEER) database (2004-2015) who underwent hepatectomy. Patients were randomly allocated to the training (70%) and validation (30%) cohorts, with baselines balanced via propensity score matching (PSM). Prognostic factors were ascertained through both univariate and multivariate analyses of competing risks, facilitating the development of pertinent risk models and nomograms. The efficacy of the model was assessed via receiver operating characteristic (ROC) curves, area under the curve (AUC), and calibration plots, with clinical utility appraised through decision curve analysis (DCA). The X-tile program facilitated the categorization of participants into low-, intermediate-, and high-risk groups on the basis of their scores derived from the nomogram.</p><p><strong>Results: </strong>Among the 1,131 participants included in the analysis after PSM, 65.34% (n=739) died from ICCA, and 13.97% (n=158) died from other causes. The 1-, 2-, and 3-year overall survival (OS) rates for ICCA patients after hepatectomy were 79.4%, 59.8% and 46.4%, respectively; the corresponding CSS rates were 82.5%, 64.0%, and 51.3%, respectively. Multivariate analysis revealed that hypodifferentiation, advanced T stage, lymph node invasion, and distant metastasis were significant risk factors. The AUCs for predicting CSS in the training cohort were 0.668, 0.711, and 0.710 for 1, 2, and 3 years, respectively. similarly, the AUCs for the test cohort were 0.709, 0.718, and 0.721 for 1, 2, and 3 years, respectively. The AUC demonstrated that the developed nomogram model exhibited moderate discriminatory power. The calibration curve demonstrated that the predicted values closely matched the actual data. DCA demonstrated greater clinical utility for the nomogram than the tumor node metastasis (TNM) classification system. Patients were divided into three risk groups according to the nomogram, which revealed substantial differences in survival rates between the groups (P<0.001).</p><p><strong>Conclusions: </strong>The prognostic nomogram developed based on the competitive risk model demonstrates moderate predictive accuracy for the specific survival rate of ICCA patients after hepatectomy, offering a practical tool for individualized prognostication and treatment planning.</p>","PeriodicalId":23216,"journal":{"name":"Translational cancer research","volume":"14 3","pages":"1884-1901"},"PeriodicalIF":1.5,"publicationDate":"2025-03-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11985192/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144000870","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":"Analysis and assessment of ferroptosis-related gene signatures and prognostic risk models in skin cutaneous melanoma.","authors":"Jianchao Ma, Yang Cai, Youqi Lu, Xu Fang","doi":"10.21037/tcr-24-1506","DOIUrl":"https://doi.org/10.21037/tcr-24-1506","url":null,"abstract":"<p><strong>Background: </strong>The occurrence and development of skin cutaneous melanoma (SKCM) are significantly influenced by ferroptosis, a sort of regulated cell death characterized by iron deposition and lipid peroxidation. Although positive strides have been achieved in the present management of SKCM, it is still unknown exactly how ferroptosis occurs in this condition. We aimed to determine the role of prognostically relevant ferroptosis-related genes (PR-FRGs) in SKCM development and prognosis.</p><p><strong>Methods: </strong>The training group was created using combined transcriptomic RNA data acquired from The Cancer Genome Atlas (TCGA) and Genotype-Tissue Expression (GTEx) databases. The dataset GSE19234 was acquired from the Gene Expression Omnibus (GEO) database as a validation group. Differentially expressed ferroptosis-related genes (DE-FRGs) were obtained from the training group, of which 103 showed up-regulation and 77 showed down-regulation. Then, 12 PR-FRGs were identified by the protein-protein interaction (PPI) network and Cox regression analysis, and prognostic risk models and nomograms were constructed. The risk model was validated using a validation group, and the prognostic value of the risk model was analyzed. Finally, immunohistochemical data were obtained from the Human Protein Atlas (HPA) website to validate the PR-FRGs.</p><p><strong>Results: </strong>Twelve PR-FRGs were identified. A prognostic risk model was built using PR-FRGs, and patients in the training and validation groups were classified as high or low risk based on the risk model. The outcomes demonstrated that the prognosis was better for the low-risk group. Prognostic value analysis showed that the prognostic risk model could accurately predict the patients' overall survival (OS), was superior to clinical traits such as age, gender, and tumor stage in predicting ability, and could be used as an independent predictor. Meanwhile, the nomogram constructed based on PR-FRGs can effectively predict the prognosis of SKCM patients. Finally, PR-FRGs were validated in the HPA database.</p><p><strong>Conclusions: </strong>Ferroptosis affects the prognosis of SKCM patients. Prognostic risk model and nomogram constructed based on 12 PR-FRGs demonstrated significant advantages in predicting the prognosis of SKCM patients. This will help in the identification and prognostic prediction of SKCM and in the discovery of new individualized treatment modalities.</p>","PeriodicalId":23216,"journal":{"name":"Translational cancer research","volume":"14 3","pages":"1857-1873"},"PeriodicalIF":1.5,"publicationDate":"2025-03-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11985187/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143983104","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":"Causal associations between atrial fibrillation and esophageal cancer: a two-sample Mendelian randomization study.","authors":"Jinsong Lei, Longjun Yang, Gongming Wang, Qianwen Liu, Guangran Guo","doi":"10.21037/tcr-24-2107","DOIUrl":"https://doi.org/10.21037/tcr-24-2107","url":null,"abstract":"<p><strong>Background: </strong>Previous studies indicated that atrial fibrillation (AF) patients had a significantly higher esophageal cancer (EC) risk. However, influencing by confounding factors, the causal effect is uncertain. In this study, we aimed to validate the causal relationship between AF and EC by Mendelian randomization (MR) analysis.</p><p><strong>Methods: </strong>An observational analysis was conducted using the data from the National Health and Nutrition Examination Survey (NHANES) and UK Biobank. Then a two-sample MR method was employed to assess the causal effect of AF on EC. The exposure of AF was collected from publicly available genome-wide association studies (GWASs). Meanwhile, the EC outcome data were derived from the UK Biobank and the FinnGen consortium. A set of 108 single-nucleotide polymorphisms (SNPs) served as instrumental variables (IVs). The effect estimates were calculated using the inverse variance weighted (IVW) method.</p><p><strong>Results: </strong>Genetically predicted AF was associated with an increased risk of EC [odds ratio (OR), 1.73; 95% confidence interval (CI): 1.01-1.73; P=0.04]. The similar results could be found by sensitivity analyses and no any evidence of horizontal pleiotropy was observed.</p><p><strong>Conclusions: </strong>This two-sample MR analysis suggested that AF was causally associated with an increased risk of EC.</p>","PeriodicalId":23216,"journal":{"name":"Translational cancer research","volume":"14 3","pages":"1849-1856"},"PeriodicalIF":1.5,"publicationDate":"2025-03-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11985194/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144011805","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":"Targeting PAR-2-driven inflammatory pathways in colorectal cancer: mechanistic insights from atorvastatin and rosuvastatin treatment in cell line models.","authors":"Rajashree Patnaik, Riah Lee Varghese, Sara Khan, Bintul Huda, Farida Bhurka, Layla Amiri, Yajnavalka Banerjee","doi":"10.21037/tcr-24-1027","DOIUrl":"https://doi.org/10.21037/tcr-24-1027","url":null,"abstract":"<p><strong>Background: </strong>Colorectal cancer (CRC) is a growing health concern globally and in regions such as the United Arab Emirates, where risk factors like obesity and hyperlipidaemia are prevalent. Chronic inflammation, driven by pathways involving protease-activated receptor 2 (PAR-2), plays a pivotal role in CRC progression, creating a tumour-promoting microenvironment. The overexpression of PAR-2 has been associated with increased tumour aggressiveness and drug resistance. While previous studies have focused on broad inflammatory modulation, this study explores the selective targeting of PAR-2 by atorvastatin (ATV) and rosuvastatin (RSV), highlighting their specificity by assessing minimal impact on PAR-1 expression, which serves as a control.</p><p><strong>Methods: </strong>HT-29 and Caco-2 CRC cell lines were employed to investigate the anti-inflammatory effects of ATV and RSV. Inflammation was induced with lipopolysaccharide (LPS), followed by treatment with varying concentrations of ATV and RSV. Western blotting and real-time polymerase chain reaction for quantification (qPCR) were performed to quantify PAR-2 and TNF-α at both the protein and mRNA levels. Enzyme linked immunosorbent assay (ELISA) was used to measure the secretion of TNF-α. Calcium signalling, which plays a crucial role in inflammation, was analysed using Fluo-4 AM dye, with fluorescence imaging capturing the effects of statin treatment on intracellular calcium influx.</p><p><strong>Results: </strong>LPS treatment significantly upregulated PAR-2 and TNF-α expression in both cell lines, validating the inflammatory model. Co-treatment with ATV or RSV reduced PAR-2 and TNF-α expression in a dose-dependent manner. The higher concentrations of ATV (50 µg/mL) and RSV (20 µg/mL) produced the most significant reduction in these inflammatory markers at both the protein and mRNA levels. Importantly, the treatment did not substantially alter PAR-1 expression, underlining the specificity of ATV and RSV in modulating PAR-2-mediated pathways. Additionally, statin treatment attenuated LPS-induced calcium influx, with fluorescence intensity decreasing markedly at higher concentrations of both statins.</p><p><strong>Conclusions: </strong>This study provides novel insights into the selective targeting of PAR-2 by ATV and RSV, distinguishing their effects from PAR-1. The reduction in PAR-2 expression and TNF-α secretion, along with the suppression of calcium signalling, underscores the potential of these statins as targeted anti-inflammatory agents in CRC. The findings highlight the therapeutic value of ATV and RSV in modulating inflammation through PAR-2-specific pathways, which may contribute to reduced cancer progression. These results pave the way for further preclinical and clinical evaluations to explore statins as adjunctive therapies in the management of CRC.</p>","PeriodicalId":23216,"journal":{"name":"Translational cancer research","volume":"14 3","pages":"1531-1566"},"PeriodicalIF":1.5,"publicationDate":"2025-03-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11985218/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144033269","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":"Association between diffusion-weighted imaging and tumor matrix in liver cancer: a cross-sectional study.","authors":"Hans-Jonas Meyer, Johann Potratz, Dörthe Jechorek, Kai Ina Schramm, Jan Borggrefe, Alexey Surov","doi":"10.21037/tcr-24-1516","DOIUrl":"https://doi.org/10.21037/tcr-24-1516","url":null,"abstract":"<p><strong>Background: </strong>Imaging modalities can reflect the underlying histopathology of tumors. However, the precise interactions between histopathological microstructure and the resulting imaging phenotype remain elusive. Predicting histopathological features, including the extracellular matrix, in a non-invasive manner could improve clinical care of liver tumors. The present study used cross-sectional guided biopsy specimens to utilize accurate spatial biopsy localization to correlate magnetic resonance imaging (MRI) derived the apparent diffusion coefficient (ADC) values with collagen IV expression in various liver cancers.</p><p><strong>Methods: </strong>A total of 127 patients (n=68 female; 45.6%) with a mean age of 65.3±12.3 years were included in the analysis. Inclusion criteria were an available cross-sectional biopsy, available biopsy specimens and a pre-interventional MRI with diffusion-weighed imaging (DWI) sequence. The tumors included 45 patients (35.4%) with hepatocellular carcinoma (HCC), 26 patients (20.5%) with cholangiocellular carcinoma and 56 patients (44.1%) with liver metastases of various primary tumors. Prebioptic liver MRI with diffusion-weighted imaging was used to correlate ADC values with collagen IV expression obtained from liver biopsy. The ADC values were measured in a co-registered way with cross-sectional biopsy imaging to ensure the spatial concordance between imaging and histopathology. The stained area and signal intensity of the immunohistochemical staining were examined.</p><p><strong>Results: </strong>The mean average stained area of collagen IV was 32.6%±27.4% and the mean staining intensity was 2.03±1.01. HCC showed statistically less stained area compared to the other tumor types (analysis of variance P<0.0001). In the overall patient sample, there was no correlation between ADCmean and average stained area (r=0.05, P=0.55) and staining intensity (r=-0.04, P=0.60). In a subgroup analysis of HCC patients, there was a significant correlation between ADCmin and the staining intensity (r=-0.33, P=0.02).</p><p><strong>Conclusions: </strong>ADC values are not associated with collagen IV expression in liver tumors. The complex extracellular matrix is not reflected by the DWI signal, which can be discussed as mainly be influenced by the cellularity of the tumors. Further research is needed to investigate the complex interactions between histopathology and the resulting imaging phenotype of MRI for clinical care.</p>","PeriodicalId":23216,"journal":{"name":"Translational cancer research","volume":"14 3","pages":"1764-1771"},"PeriodicalIF":1.5,"publicationDate":"2025-03-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11985173/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144055232","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 narrative review of papillary thyroid carcinoma-related long non-coding RNAs and their relevance to malignant tumors.","authors":"Yuanhao Su, Yi Jin","doi":"10.21037/tcr-24-1038","DOIUrl":"https://doi.org/10.21037/tcr-24-1038","url":null,"abstract":"<p><strong>Background and objective: </strong>In recent years, research on the relationship between papillary thyroid carcinoma (PTC) and long non-coding RNAs (lncRNAs) has been burgeoning. However, there has not been an analysis of the regulatory mechanisms of these lncRNAs in all tumors, nor a comprehensive categorization and comparison of these mechanisms. This review aims to uncover whether PTC-related lncRNAs also play an important role in other tumors and to identify a common pattern of action.</p><p><strong>Methods: </strong>We conducted a statistical analysis of lncRNAs related to PTC that have been reported during the period from Jan 2022 to May 2024 through searching in the Embase, Web of Science, and PubMed databases, focusing on those with greater research value. Using them as the focal points of our study, we compiled data on their different regulatory mechanisms across various malignant tumors, emphasizing key findings.</p><p><strong>Key content and findings: </strong>This comprehensive analysis not only provides valuable insights into potential regulatory mechanisms of these lncRNAs in PTC but also serves as a reference for exploring their broader regulatory networks within cancer. The principal discovery is that lncRNAs associated with PTC can competitively interact with microRNAs (miRNAs). This interaction influences miRNA-targeted messenger RNA (mRNA) and the expression of cancer-related proteins, ultimately facilitating the progression of PTC as well as other malignant tumors.</p><p><strong>Conclusions: </strong>The lncRNAs associated with PTC exert regulatory functions in other malignancies as well and possess similar regulatory mechanisms. This provides a molecular basis for the future development of relevant targeted therapies.</p>","PeriodicalId":23216,"journal":{"name":"Translational cancer research","volume":"14 3","pages":"2125-2149"},"PeriodicalIF":1.5,"publicationDate":"2025-03-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11985200/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144035893","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}