Technology in Cancer Research & Treatment最新文献

{"title":"SMC3 Is Highly Expressed in Gliomas and Is Associated With Favorable Prognosis and B Cell-Related Immune Features.","authors":"Wei Han, Lei Tian, Haonan Li, Yadong Liu, Xuetao Han, Liubing Hou, Zhiqing Xiao, Xiaoying Xue, Huandi Zhou","doi":"10.1177/15330338261454517","DOIUrl":"10.1177/15330338261454517","url":null,"abstract":"<p><p>IntroductionSMC3, a core component of the cohesin complex, plays diverse roles in tumorigenesis across different cancer types. However, its expression pattern, prognostic significance, and potential association with the immune microenvironment in gliomas remain largely unexplored.MethodsIn this retrospective study, we systematically analyzed SMC3 expression using multiple transcriptomic datasets, including CGGA (CGGA-325, CGGA-301), TCGA, and GEO (GSE4290, GSE50161), and validated protein-level expression in 44 clinical glioma specimens via immunohistochemistry. Associations with overall survival (OS) were assessed using Kaplan-Meier and Cox regression analyses. Immune microenvironment features were evaluated using ESTIMATE and TIMER2.0, and pathway enrichment was analyzed through GSEA. Core B cell-related genes and signaling pathways associated with SMC3 were further identified by intersecting SMC3-correlated genes with MSigDB C7 and KEGG B cell receptor signaling gene sets.ResultsSMC3 was significantly overexpressed in glioma tissues compared with normal brain, with higher expression in lower-grade gliomas (LGG) than glioblastoma (GBM). High SMC3 expression was associated with prolonged OS across CGGA-325, CGGA-301, and the Validation Cohort, and remained prognostically favorable in specific clinical subgroups, including MGMT-unmethylated and 1p/19q non-codeleted tumors. SMC3 high-expression tumors exhibited lower overall immune and stromal scores but showed significant positive correlations with B cell and plasma cell infiltration. GSEA revealed enrichment of PI3K-AKT-MYC- and MTORC1-related pathways in high SMC3 tumors. Intersection analyses identified four core B cell-related genes (AKT3, CHUK, GSK3B, PIK3CA) within the PI3K-Akt signaling pathway, suggesting SMC3 expression may be associated with B cell-related immune features.ConclusionsSMC3 is highly expressed in gliomas and is associated with favorable prognosis. Its expression correlates with B cell-related immune infiltration and activation of PI3K-Akt-MYC signaling, highlighting a potential role in shaping local immune microenvironments. These findings provide novel evidence for SMC3 as a prognostic biomarker and suggest a potential association with B cell-mediated immune features in gliomas.</p>","PeriodicalId":22203,"journal":{"name":"Technology in Cancer Research & Treatment","volume":"25 ","pages":"15330338261454517"},"PeriodicalIF":2.7,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13219900/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148043965","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 New Perspective in Tumor Therapy: Targeting M2-Type Tumor-Associated Macrophages.","authors":"Qiang Zhang, Yungang Sun, Yu Zhuang, Mengxu Yao, Siyang Jiao, Qi Wang, Xiaoying Zhang, Feng Shao","doi":"10.1177/15330338261448345","DOIUrl":"10.1177/15330338261448345","url":null,"abstract":"<p><p>Uncontrolled proliferation is not the only factor driving tumor growth; the tumor microenvironment (TME) has a significant impact. Tissue homeostasis and pathogen removal depend on macrophages, which are important innate immune effector cells. Nevertheless, there is growing evidence that tumor-associated macrophages (TAMs) do not consistently suppress cancer and are functionally diverse. Specifically, M2-polarized TAMs (M2-TAMs) build up in multiple solid tumors, where they promote angiogenesis, metastasis, and immunosuppression, hastening the course of the disease. Here, we critically assess the clinical translatability of TAM-targeted treatment approaches, outline the molecular circuits underpinning M2-TAMs-tumor cell interaction, and extensively explore the phenotypic spectrum and functional diversity of macrophages in cancer. Our objective is to offer a theoretical foundation for upcoming immunotherapeutic interventions.</p>","PeriodicalId":22203,"journal":{"name":"Technology in Cancer Research & Treatment","volume":"25 ","pages":"15330338261448345"},"PeriodicalIF":2.7,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13161641/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147843205","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 Preliminary Study on the Auto-Segmentation of Targets and Organs at Risk in Pediatric Total Marrow and Lymphoid Irradiation.","authors":"Zhihua Xie, Jinfeng Liu, Lixia Hou, Haoran Feng, Fuli Zhang, Na Lu","doi":"10.1177/15330338261426261","DOIUrl":"10.1177/15330338261426261","url":null,"abstract":"<p><p>IntroductionLeukemia is one of the most prevalent cancers in children. The use of total marrow and lymphoid irradiation (TMLI) via helical tomotherapy (TOMO) as a conditioning regimen prior to bone marrow transplant (BMT) has been widely adopted in clinical practice. Accurate and efficient segmentation of target volumes and organs at risk (OARs) is a prerequisite for precise TMLI. The purpose of this study was to investigate the feasibility of deep learning-based auto-segmentation technology (using 2D U-net and 3D V-net models) for target volumes (bone marrow and lymphatic drainage regions) and organs at risk (OARs) in pediatric total marrow and lymphoid irradiation (TMLI).MethodsThis study was designed as a retrospective study. Thirty-six pediatric patients treated with TMLI between 2018 and 2024 were included. Target volumes and OARs were manually segmented and refined. The CT images and corresponding contours were imported into the AccuLearning workstation (Manteia Company, Xiamen, China) to train, validate, and test based on 2D U-net and 3D V-net deep learning models. The auto-segmentation performance was evaluated on 6 test cases using the Dice Similarity Coefficient (DSC), Hausdorff Distance (HD), and Average Surface Distance (ASD).ResultsFinally, analysis revealed DSC values >0.7 for all OARs except lenses segmented by the 3D V-net model. For target volumes, bone structures achieved high segmentation accuracy.ConclusionThe 3D V-net model demonstrated superior performance compared to the 2D U-net model. Auto-segmented contours generated by the 2D U-net and 3D V-net models, with minor manual adjustments, are clinically applicable for TMLI radiotherapy planning.</p>","PeriodicalId":22203,"journal":{"name":"Technology in Cancer Research & Treatment","volume":"25 ","pages":"15330338261426261"},"PeriodicalIF":2.7,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13150095/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147781759","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":"METTL3-Mediated m6A Modification of COL5A2 Inhibits Ferroptosis Through an IGF2BP3-dependent Mechanism in Gastric Cancer.","authors":"Guo Xin, Li Shuang, Guo Yuying, Ji Lina","doi":"10.1177/15330338261481298","DOIUrl":"10.1177/15330338261481298","url":null,"abstract":"<p><p>IntroductionMETTL3, the core enzyme of m6A methylation, influences gastric cancer (GC) progression, but its role in ferroptosis remains unclear. This study investigated the regulatory role of METTL3 in GC ferroptosis and its underlying mechanism via the downstream target gene collagen type V alpha 2 chain(COL5A2).MethodGC cell lines (AGS, MKN-45) and normal GES-1 cells were used. Ferroptosis was induced by erastin and RSL-3. METTL3 overexpression/knockdown models were constructed to assess ferroptosis indicators, including lipid reactive oxygen species(ROS), malondialdehyde(MDA), Fe²⁺, glutathione(GSH) and malignant phenotypes. m6A sites were predicted and validated by MeRIP-qPCR. m6A readers were knocked down to identify effectors, and mRNA stability was evaluated via RIP and actinomycin D assays. The focal adhesion kinase(FAK)/mitogen-activated protein kinase(MAPK)/extracellular signal-regulated kinase(ERK)pathway and ferroptosis-related proteins were detected by Western blot, with pathway involvement confirmed using the FAK inhibitor PF-573228. To validate the in vitro findings, a nude mouse xenograft tumor model was established.ResultsMETTL3 was highly expressed in GC cells and suppressed by ferroptosis inducers. METTL3 overexpression inhibited ferroptosis (reducing ROS, MDA, Fe²⁺, increasing GSH) and promoted proliferation and migration. COL5A2 was positively correlated with METTL3. MeRIP-qPCR confirmed that METTL3 mediates m6A modification of COL5A2's 3'-UTR. RIP and ActD assays demonstrated that the m6A reader insulin-like growth factor 2 mRNA-binding protein 3(IGF2BP3) maintains COL5A2 mRNA stability. IGF2BP3 knockdown promoted ferroptosis and apoptosis, which were reversed by COL5A2 overexpression. Furthermore, COL5A2 overexpression activated the FAK/MAPK/ERK pathway, upregulated GPX4, and inhibited ferroptosis; these effects were counteracted by the FAK inhibitor. In vivo, METTL3 overexpression promoted tumor growth, reduced 4-HNE levels, and regulated ferroptosis and FAK/MAPK/ERK pathway proteins, all of which were reversed by COL5A2 knockdown.ConclusionMETTL3 upregulates COL5A2 expression through m6A modification, with IGF2BP3 maintaining COL5A2 mRNA stability. This subsequently activates the FAK/MAPK/ERK signaling pathway, inhibits ferroptosis, and promotes GC progression. The METTL3/IGF2BP3/COL5A2 axis represents a promising therapeutic target for GC treatment.</p>","PeriodicalId":22203,"journal":{"name":"Technology in Cancer Research & Treatment","volume":"25 ","pages":"15330338261481298"},"PeriodicalIF":2.7,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13527347/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148841304","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":"Influence of Interfractional Variations of Bladder and Rectal Filling on Vaginal Cuff Movement and the Role of Rectal Balloons in Gynecological Pelvic Proton Beam Therapy.","authors":"Lars Wessel, Friderike K Longarino, Natalia Sycheva, Jan-Hendrik Bolten, Hanna Waldsperger, Katharina Kozyra, Philipp Schroeter, Julia Bauer, Fabian Weykamp, Eva Meixner, Kristin Lang, Laila König, Jürgen Debus, Nathalie Arians","doi":"10.1177/15330338261438327","DOIUrl":"10.1177/15330338261438327","url":null,"abstract":"<p><p>IntroductionPostoperative active raster-scanning intensity modulated proton beam therapy (IMPT) for gynecological cancers requires precise target coverage, yet interfractional motion of the vaginal cuff and adjacent pelvic organs may compromise dosimetric robustness. This study retrospectively assessed interfractional organ movement and evaluated the clinical need for rectal balloon (RB) use to ensure adequate target coverage.Methods23 patients, 17/6 with/without RB, received postoperative IMPT between 2017 and 2020 at Heidelberg Ion-beam Therapy Center (HIT). Positioning verification computed tomography (pv-CT) and treatment planning CT (tp-CT) images were retrieved and rectum, bladder and the vaginal cuff (VC) were contoured. The clinical target volume (CTV) and planning target volume (PTV) were mapped from tp-CT to the pv-CT images and forward dose calculation was performed. To assess the volume of the VC not covered by the CTV or PTV, the region of interest (ROI), VC outside of CTV (VC-CTV) and outside of PTV (VC-PTV) were created. Volume differences (Δ) to the tp-CT images and dose parameters for each ROI were evaluated.Results139 pv-CTs were analysed. The use of RB significantly reduced VC displacements, resulting in fewer pv-CTs with the VC located outside the CTV (40% vs. 91%, p = 0.0252) and PTV (28% vs. 68%, p = 0.0362). CTV/PTV coverage and ROI doses remained stable across all fractions and there was no significant difference between groups. The applied PTV margins ensured robust dose coverage despite interfractional anatomical variations.ConclusionRB application effectively reduced interfractional VC motion and there was no significant Δ in target coverage or ROI doses. Using tp-CT images with full and empty bladder for definition of the CTV and standardized PTV margins contributed to stable dosimetry outcomes, confirming the robustness of the used IMPT treatment protocol. However, the use of RB may be beneficial, especially in patients with known gastrointestinal comorbidities or trapped air in the rectum.</p>","PeriodicalId":22203,"journal":{"name":"Technology in Cancer Research & Treatment","volume":"25 ","pages":"15330338261438327"},"PeriodicalIF":2.7,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13111882/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147781807","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":"Fully Automated Stain Quantification Framework for IHC Whole Slide Images in Breast Cancer.","authors":"Tuo Yin, Frédéric Lifrange, Zoë Denis, Alex de Caluwé, Laurence Buisseret, Xavier Catteau, Clara Legros, Nick Reynaert, Jennifer Dhont","doi":"10.1177/15330338251407734","DOIUrl":"10.1177/15330338251407734","url":null,"abstract":"<p><p>IntroductionImmunohistochemistry (IHC) plays a crucial role in breast cancer diagnosis, treatment selection, and research. However, manual scoring of IHC whole slide images (WSIs) is time-consuming and suffers from inter- and intra-observer variability.MethodsTo help address these challenges, we present and publicly release a fully automated, compartment-specific (ie, tumor and stroma) H-scoring framework for IHC analysis. The framework consists of three deep learning modules: tumor-stroma segmentation, nuclei segmentation, and H-score estimation for tumor and stroma. It processes WSIs in minutes, delivering consistent and reproducible H-scores with accuracy comparable to expert pathologists. The modular design also allows flexibility for use in other IHC tasks such as cellularity quantification, and supports configuration options to balance accuracy and computational efficiency.ResultsFine-tuned on 87 expert-annotated patches, the framework achieved a Spearman's rank correlation (<i>ρ</i>) in internal validation of 0.84 (95% confidence interval [CI]: 0.77-0.89) across 100 expert-annotated WSIs, outperforming state-of-the-art (<i>ρ</i> = 0.78, 95% CI: 0.68-0.85) and matching the inter-observer variability between two expert pathologists (<i>ρ</i> = 0.84, 95% CI: 0.63-0.94). In external validation, it achieved 86% accuracy in HER2 classification (0-3+) and a mean absolute error of 21 ± 10 (range: [5-46]) in CD73 scoring, where ground truth H-scores were all 0.ConclusionThe framework achieves agreement comparable to that of expert pathologists, underscoring its clinical utility in providing reproducible IHC scores that can reduce diagnostic variability and support consistent treatment decisions. The code is available at https://github.com/YinTuo/AutoIHC.</p>","PeriodicalId":22203,"journal":{"name":"Technology in Cancer Research & Treatment","volume":"25 ","pages":"15330338251407734"},"PeriodicalIF":2.7,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13051182/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147609752","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":"Salivary SIRT3 Levels in Gutka and Alcohol Consumers: A Cross-Sectional Study on Habit-Associated Molecular Changes.","authors":"Junaid Ahmed, Shubham Pawar, Nandita Shenoy, Neelam Pawar, Nanditha Sujir","doi":"10.1177/15330338251408546","DOIUrl":"10.1177/15330338251408546","url":null,"abstract":"<p><p>BackgroundSirtuin-3 (SIRT3) regulates the production of cellular reactive oxygen species (ROS). This study aims to elucidate the molecular mechanisms involved in oral lesion development by exploring the relationship between SIRT3 expression, gutka consumption, and oral disease progression, with the objective of identifying potential biomarkers for early detection and risk assessment.MethodsA cross-sectional study was conducted among individuals who regularly underwent oral health check-ups, excluding patients with premalignant and oral cancers from the study. Participants were categorized into three groups: Case 1 (gutka and alcohol consumers), Case 2 (gutka consumers without alcohol), and Control (non-consumers). Unstimulated saliva samples were collected and analysed using ELISA to measure SIRT3 levels. Statistical comparisons were performed using ANOVA followed by post hoc Tukey testsResultsThe mean SIRT3 levels were 7.57 ± 3.23 ng/mL (Case 1), 8.17 ± 2.87 ng/mL (Case 2), and 9.9 ± 2.78 ng/mL (control). The differences between the groups were statistically significant (p = .036), with the greatest difference observed between the case 1 group and the control group.ConclusionSIRT3 levels were lowest in individuals who consumed gutka and alcohol and were significantly lower than those in the control group. These findings suggest a potential negative impact of gutka and alcohol consumption on SIRT3 levels.</p>","PeriodicalId":22203,"journal":{"name":"Technology in Cancer Research & Treatment","volume":"25 ","pages":"15330338251408546"},"PeriodicalIF":2.7,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13176558/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147933788","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":"Magnetic-Field-Induced Secondary-Electron Effects in MR-Guided Radiotherapy: From Dosimetric Mechanisms to Workflow-Based Clinical Risk Management.","authors":"Aixin Wang, Jian Fang, Mingyu Tan, Yimin Li, Min Liu, Jinyi Lang","doi":"10.1177/15330338261488745","DOIUrl":"10.1177/15330338261488745","url":null,"abstract":"<p><p>MR-guided radiotherapy (MRgRT) combines high-contrast MRI, online adaptation, and radiation delivery in a single treatment workflow. The static magnetic field, however, changes the transport of secondary electrons generated by megavoltage photons and can produce dose perturbations that depend strongly on anatomy and beam geometry. This review examines the underlying physics, with emphasis on Lorentz-force deflection, the electron return effect (ERE) at density interfaces, and the electron streaming effect (ESE) in favorable geometries. It also considers where conventional DVH-based review may miss small, spatially confined hot or cold regions. We discuss magnetic-field-aware dose calculation, Monte Carlo and accelerated methods, independent verification, and delivered-dose reconstruction in adaptive workflows. Evidence is then considered by anatomical site, including the head and neck, thorax, and abdomen. Across these settings, clinical importance is determined mainly by the location and size of the perturbation and its relation to normal-tissue tolerance. Data from 0.35 T and 1.5 T systems show that relevant effects can persist after reoptimization, vary with motion, and respond differently to additional beam angles. In representative planning studies, a 1.5 T field increased skin D2% by about 1.4 Gy in simulated lung SBRT, whereas reoptimization in head-and-neck plans reduced the mean increase in skin Dmax from 5.43 to 1.68 Gy. We therefore treat magnetic-field-induced dose effects as geometry-specific risks that should be identified and controlled prospectively. The review concludes with practical guidance on where to inspect dose, when additional verification is justified, and which mitigation strategies are supported by current evidence.</p>","PeriodicalId":22203,"journal":{"name":"Technology in Cancer Research & Treatment","volume":"25 ","pages":"15330338261488745"},"PeriodicalIF":2.7,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13562860/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148930977","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":"The Prognostic Value of SERPINE1 in Clinical Outcomes in Head and Neck Squamous Cell Carcinoma: A Systematic Review and Meta-Analysis.","authors":"Shifeng Yan, Xinyu Li, Changyu Zhu, Wei Li","doi":"10.1177/15330338261435460","DOIUrl":"10.1177/15330338261435460","url":null,"abstract":"<p><p>BackgroundSERPINE1 has attracted considerable attention in tumor biology, but its clinical importance in head and neck squamous cell carcinoma (HNSCC) is not yet clear. We therefore examined whether SERPINE1 expression is related to survival in patients with HNSCC.MethodsWe searched three major databases (PubMed, EMBASE, and the Cochrane Library) and identified observational studies reporting survival outcomes in relation to SERPINE1 expression through November 11, 2024. From eligible reports we extracted data on progression-free survival (PFS), overall survival (OS), disease-specific survival (DSS) and disease-free survival (DFS), and calculated pooled hazard ratios (HRs) using random-effects models.ResultsEleven studies including 733 individuals with HNSCC met the inclusion criteria. Across these cohorts, higher SERPINE1 expression was consistently linked with shorter OS (HR 2.81, <i>P</i> = 0.003) and shorter DFS (HR 1.57, <i>P</i> = 0.004). In contrast, no clear associations were observed for PFS or DSS (<i>P</i> ≥ 0.05).ConclusionCurrent evidence suggests that increased SERPINE1 expression is associated with an unfavorable prognosis in HNSCC, particularly for OS and DFS. Larger prospective studies are needed to confirm these findings and to determine how SERPINE1 assessment might be incorporated into risk stratification and treatment planning for patients with HNSCC.</p>","PeriodicalId":22203,"journal":{"name":"Technology in Cancer Research & Treatment","volume":"25 ","pages":"15330338261435460"},"PeriodicalIF":2.7,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13507692/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147609757","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":"An MRI-Based Intratumoral and Peritumoral 2.5D Deep Learning Model for Predicting P53-Mutated Hepatocellular Carcinoma: A Two-Center Study.","authors":"Jingfei Weng, Pinxiong Li, Dinghua Yao, Yuqing He, Chun Yang, Bin Yang","doi":"10.1177/15330338261488956","DOIUrl":"10.1177/15330338261488956","url":null,"abstract":"<p><p>IntroductionHepatocellular carcinoma (HCC) is the most common primary liver cancer with high mortality. TP53 is the most frequently mutated tumor-suppressor gene in HCC, and P53 mutations are associated with poor differentiation, vascular invasion, and lower survival. Preoperative noninvasive detection of P53-mutated HCC is critical for treatment planning and prognostic assessment. This study aimed to develop and validate a deep learning (DL) model for predicting P53 mutation status in HCC.MethodsIn this retrospective two-center study, 373 patients with pathologically confirmed HCC were enrolled from two institutions (Center 1: n=320; Center 2: n=53). The Center 1 cohort was randomly partitioned into a training cohort (n=256) and an internal test cohort (n=64). Patients from Center 2 constituted an independent external test cohort (n=53). We employed a 2.5D ResNet34 architecture to process three-channel dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI). Separate deep learning models were constructed for intratumoral and peritumoral regions using both single-phase and multiphase (arterial, portal venous, and delayed) fusion sequences. Significant clinical variables were selected to build a Clinical model, which was subsequently integrated with the optimal deep learning model to create a Combined model. Model performance was assessed by the area under the curve (AUC), calibration curves, and decision curve analysis (DCA).ResultsMultiphase fusion models consistently outperformed their single-phase models. The peritumoral (5mm) fusion model (IntraPeri5mm_Fusion) outperformed the intratumoral fusion model, achieving AUCs of 0.881 (95% CI: 0.836-0.926), 0.772 (95% CI: 0.651-0.893), and 0.757 (95% CI: 0.624-0.891) on the training cohort, internal test cohort, and external test cohort, respectively. The Combined model yielded further incremental improvement, with AUCs reaching 0.886 (95% CI: 0.842-0.930), 0.805 (95% CI: 0.691-0.918), and 0.793 (95% CI: 0.668-0.918) across the respective cohorts.ConclusionsThe proposed 2.5D DL model based on DCE-MRI effectively predicts P53-mutated HCC. Integrating peritumoral features with clinical variables yields the best performance, offering a promising noninvasive tool for prognostic stratification and individualized therapeutic planning.</p>","PeriodicalId":22203,"journal":{"name":"Technology in Cancer Research & Treatment","volume":"25 ","pages":"15330338261488956"},"PeriodicalIF":2.7,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13558934/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148913541","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}