Technology in Cancer Research & Treatment最新文献

{"title":"Multidisciplinary Collaboration and Novel Technological Advances in Hadron Therapy.","authors":"Manjit Dosanjh, Alberto Degiovanni, Maria Monica Necchi, Elena Benedetto","doi":"10.1177/15330338241311859","DOIUrl":"10.1177/15330338241311859","url":null,"abstract":"<p><p>The battle against cancer remains a top priority for society, with an urgent need to develop therapies capable of targeting challenging tumours while preserving patient's quality of life. Hadron Therapy (HT), which employs accelerated beams of protons, carbon ions, and other charged particles, represents a significant frontier in cancer treatment. This modality offers superior precision and efficacy compared to conventional methods, delivering therapeutic the dose directly to tumours while sparing healthy tissue. Even though 350,000 patients have already been treated worldwide with protons and 50,000 with carbon ions, HT is still a relatively young field and more research as well as novel, cost-effective and compact accelerator technologies are needed to make this treatment more readily available globally. Interestingly the very first patient was irradiated with protons in September 1954, the same month and year CERN was founded. Both of these endeavours are embedded in cutting edge technologies and multidisciplinary collaboration. HT is finally gaining ground and, even after 70 years, the particle therapy field continues innovating and improving for the benefits of patients globally. Developing technologies that are both affordable and easy to use is key and would allow access to more patients. Advances in accelerator-driven Boron Neutron Capture Therapy (BNCT), image-guided hadron beams delivery, clinical trials and immunotherapy, together with the recent interest and advances in FLASH therapy, which is currently an experimental treatment modality that involves ultrahigh-dose rate delivery, are just a few examples of innovation that may eventually help to provide access to a larger number of patients.</p>","PeriodicalId":22203,"journal":{"name":"Technology in Cancer Research & Treatment","volume":"24 ","pages":"15330338241311859"},"PeriodicalIF":2.7,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11789126/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143081023","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":"Clinical Significance and Pathogenic Mechanisms of Long Non-Coding RNA TRPM2-AS in Cancers.","authors":"Shichen Huang, Bowen Li, Huanyu Chen, Cheng Rong, Zheng Yang, Xianqin Zhang","doi":"10.1177/15330338251315625","DOIUrl":"10.1177/15330338251315625","url":null,"abstract":"<p><p>Long non-coding RNAs (lncRNAs) are known to play vital roles in human cancers. LncRNA TRPM2-AS has been found to be upregulated in various types of cancers. The elevated levels of TRPM2-AS are associated with important clinicopathological parameters such as tumor size, tumor stage, and lymph node metastasis, revealing that TRPM2-AS could be a potential target for cancer diagnosis, prognosis and treatment. Moreover, TRPM2-AS is involved in regulating the cell proliferation, migration, invasion, apoptosis, drug or radio resistance by serving as a competing endogenous RNA, directly bounding to proteins and regulating multiple signaling pathways. In this review, we comprehensively summarize the latest knowledge on the aberrant expression of TRPM2-AS, the relationship between TRPM2-AS and clinical features, and the detailed mechanisms of potential functions of TRPM2-AS in various cancer types. The current study highlights the potential of TRPM2-AS as a prognostic and therapeutic target in cancers.</p>","PeriodicalId":22203,"journal":{"name":"Technology in Cancer Research & Treatment","volume":"24 ","pages":"15330338251315625"},"PeriodicalIF":2.7,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11770775/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143047972","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":"Combining Immunotherapy with Anlotinib in Extensive-Stage Small Cell Lung Cancer: A Multicenter Analysis of Efficacy and Safety.","authors":"Guogang Gao, Meiling Sun, Zhongfei Yang, Jingyi Li, Huaijun Ji, Ge Yu","doi":"10.1177/15330338251329248","DOIUrl":"10.1177/15330338251329248","url":null,"abstract":"<p><p>BackgroundExtensive-stage small cell lung cancer (ES-SCLC) is a highly aggressive malignancy with poor prognosis. This study aimed to assess the efficacy of combining immunotherapy (IT) with Anlotinib in ES-SCLC patients.MethodsThis study was a multicenter retrospective cohort analysis. Survival outcomes were evaluated using Kaplan-Meier curves and Cox proportional hazards regression models.ResultsA total of 147 patients were included in the analysis. The median overall survival (mOS) for the cohort was 15.5 months (95% CI: 13.9-17.1). Patients in the chemotherapy(CT) plus IT group had an mOS of 17.8 months, compared to 12.6 months in the CT-alone group (p = 0.055). When stratified into CT + IT + Anlotinib, CT + IT, and CT-alone groups, the mOS were 18.5, 16.3, and 12.6 months, respectively, with the CT + IT + Anlotinib group demonstrating significantly improved OS compared to CT-alone (p = 0.044). The ORR and DCR for the entire cohort were 71.4% and 85.7%, respectively. Subgroup analysis revealed ORRs of 74.1% (CT + IT + Anlotinib), 73.9% (CT + IT), and 70.1% (CT-alone), with corresponding DCRs of 92.6%, 91.3%, and 82.5%. Multivariate analysis revealed that radiotherapy (RT, p = 0.003) and IT (p = 0.021) were independent prognostic factors for OS, while liver metastasis (p = 0.023) and RT (p = 0.018) were associated with PFS. Patients receiving RT in combination with CT showed markedly improved OS (17.5 vs 12.5 months; p = 0.002) and PFS (7.3 vs 6.3 months; p = 0.004). The incidence of adverse events was comparable across all groups (p = 0.721).ConclusionThe combined application of Anlotinib with IT and the combination of CT with RT both significantly improved survival outcomes in patients with ES-SCLC while maintaining a favorable safety profile. These findings warrant further investigation in future studies.</p>","PeriodicalId":22203,"journal":{"name":"Technology in Cancer Research & Treatment","volume":"24 ","pages":"15330338251329248"},"PeriodicalIF":2.7,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11926841/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143671103","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":"Evaluating T1/T2 Relaxometry with OCRA Tabletop MRI System in Fresh Clinical Samples: Preliminary Insights into ZEB1-Associated Tissue Characteristics.","authors":"Ahmed Y Sanin, Marcus Prier, Thomas Wartmann, Christian Siba, Katrin Hippe, Maciej Pech, Roland S Croner, Oliver Speck, Ulf D Kahlert, Georg Rose","doi":"10.1177/15330338251366371","DOIUrl":"https://doi.org/10.1177/15330338251366371","url":null,"abstract":"<p><p>IntroductionThe OCRA Tabletop MRI System is a compact, low-field (0.24T) magnetic resonance platform originally developed as an educational device to teach MR physics using chemical test tube-sized samples. Given its capabilities, we explored its diagnostic potential by performing relaxometric analysis on freshly resected human tissue specimens.MethodsMatched pairs of histologically confirmed tumor and non-tumor samples were analyzed with the OCRA MRI system to determine T1 and T2 relaxation times via NMR spectroscopy. In parallel, mRNA expression levels of ZEB1, a key transcription factor involved in WNT signaling, stem cell maintenance and tumor-stroma interactions were quantified for each sample.ResultsThe measured T1 and T2 relaxation times showed distinct profiles between tumor and non-tumor tissues. These biophysical properties were correlated with ZEB1 mRNA expression, revealing preliminary associations between tissue relaxation behavior and molecular signatures relevant to tumor microenvironment dynamics.ConclusionAlthough this pilot study does not yet confirm clinical diagnostic utility, it offers initial biophysical insights into tumor-associated tissue alterations and provides a foundation for future validation studies in larger patient cohorts.</p>","PeriodicalId":22203,"journal":{"name":"Technology in Cancer Research & Treatment","volume":"24 ","pages":"15330338251366371"},"PeriodicalIF":2.8,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12381451/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144970010","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 Role of Radiotherapy in Relapsed or Refractory Diffuse Large B-Cell Lymphoma Post-CAR-T Therapy: A Systematic Literature Review.","authors":"Andrea Emanuele Guerini, Eneida Mataj, Paolo Borghetti, Luca Triggiani, Mario Levis, Fabio Matrone, Gabriele Simontacchi, Stefania Nici, Stefano Riga, Mirsada Katica, Marco Lorenzo Bonù, Alessandra Tucci, Luigi Spiazzi, Stefano Maria Magrini, Michela Buglione di Monale","doi":"10.1177/15330338251351065","DOIUrl":"10.1177/15330338251351065","url":null,"abstract":"<p><p>IntroductionHistorically, the management of relapsed or refractory diffuse large B-cell lymphoma (r/r-DLBCL) involved chemotherapy and autologous stem cell transplant, though outcomes were often suboptimal. Chimeric antigen receptor T-cell (CAR-T) therapy has transformed the therapeutic landscape for r/r-DLBCL, achieving high response rates and improving progression-free and overall survival. However, a significant proportion of patients relapse after CAR-T, and optimal treatment strategies for post-CAR-T relapse remain unclear. Radiotherapy (RT), a highly effective treatment for lymphoma, is increasingly recognized for its potential role as both a bridging therapy and a salvage option following CAR-T relapse.MethodsA comprehensive literature review was conducted using databases including PubMed, Scopus, EMBASE, and Cochrane Library, with search terms combining \"radiotherapy,\" \"radiation therapy,\" \"lymphoma,\" and \"CAR T-cell.\" A total of 690 records were screened, and 14 studies were included in the analysis after applying inclusion and exclusion criteria.ResultsRT demonstrates high response rates in CAR-T relapsed DLBCL, with overall response rates (ORR) ranging from 35% to 82.4% and complete response rates (CRR) from 17% to 59%. One-year local control rates ranged between 62% and 84%. Salvage RT showed comparable or superior outcomes to systemic therapies in multiple studies, particularly in patients with localized relapses. The toxicity profile of RT was favorable, particularly when modern techniques such as IMRT were employed. Case reports and retrospective series highlighted its effectiveness in achieving durable responses and controlling localized disease progression.ConclusionsRadiotherapy is a safe and effective treatment option for patients with DLBCL relapsed or refractory after CAR-T therapy. It achieves high local control rates and favorable outcomes, particularly in patients with localized relapse. Incorporating RT into the therapeutic workflow may enhance the management of this challenging population. Further prospective studies are needed to define its role and optimize treatment sequencing.</p>","PeriodicalId":22203,"journal":{"name":"Technology in Cancer Research & Treatment","volume":"24 ","pages":"15330338251351065"},"PeriodicalIF":2.8,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12177245/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144317897","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Efficacy and Safety of Poly (ADP-Ribose) Polymerase Inhibitors in Combination with Chemotherapy for Advanced Breast Cancer: A Systematic Review and Meta-Analysis.","authors":"Qiuhua Duan, Yue Feng, Lichen Cao, Lijun Hu, Jianlin Wang, Fei Sun, Qinghong Meng, Mengyun Zhou, Jingping Yu, Haiyan Gao","doi":"10.1177/15330338251350630","DOIUrl":"10.1177/15330338251350630","url":null,"abstract":"<p><p>PurposeTo comprehensively evaluate the efficacy and safety of combining poly (ADP-ribose) polymerase (PARP) inhibitors with chemotherapy in patients with advanced breast cancer.MethodsA systematic literature search was conducted in PubMed, Embase, Cochrane Library, Web of Science, and ClinicalTrials.gov to identify randomized controlled trials (RCTs) evaluating PARP inhibitor-chemotherapy combinations. Studies reporting progression-free survival (PFS), overall survival (OS), overall response rate (ORR), and safety outcomes were included. Data extraction and quality assessment were performed independently by two reviewers, and a meta-analysis was conducted using random-effects models.ResultsOf 970 studies retrieved, four RCTs involving 1064 patients met the inclusion criteria. PARP inhibitors combined with chemotherapy significantly improved PFS (hazard ratio [HR] 0.73, 95% confidence interval [CI] 0.63-0.84, <i>P</i> < .0001) and showed a trend towards improved OS (HR 0.93, 95% CI 0.79-1.09, <i>P</i> = .36), though this was not statistically significant. There was no significant improvement in ORR (RR 1.08, 95% CI 0.98-1.20, <i>P</i> = .13). Regarding safety, no significant difference was observed in all grades or grade 3-4 adverse events (AEs) overall, but the combination therapy was associated with an increased risk of anemia, nausea, and diarrhea (RRs ranging from 1.14 to 1.29, all <i>P</i> < .01).ConclusionPARP inhibitor combined with chemotherapy is an effective option for the treatment of patients with advanced breast cancer, but its potential increased risks of specific AEs need to be weighed. Clinicians should make individualized treatment plans according to the specific conditions of patients, comprehensive consideration of efficacy and safety.</p>","PeriodicalId":22203,"journal":{"name":"Technology in Cancer Research & Treatment","volume":"24 ","pages":"15330338251350630"},"PeriodicalIF":2.7,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12174678/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144310466","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":"Retraction: microRNA-195 Promotes Small Cell Lung Cancer Cell Apoptosis via Inhibiting Rap2C Protein-Dependent MAPK Signal Transduction.","authors":"","doi":"10.1177/15330338251363321","DOIUrl":"10.1177/15330338251363321","url":null,"abstract":"","PeriodicalId":22203,"journal":{"name":"Technology in Cancer Research & Treatment","volume":"24 ","pages":"15330338251363321"},"PeriodicalIF":2.8,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12351068/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144837783","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":"Retraction: \"Mir-452-3p: A Potential Tumor Promoter That Targets the CPEB3/EGFR Axis in Human Hepatocellular Carcinoma\".","authors":"","doi":"10.1177/15330338251377135","DOIUrl":"10.1177/15330338251377135","url":null,"abstract":"","PeriodicalId":22203,"journal":{"name":"Technology in Cancer Research & Treatment","volume":"24 ","pages":"15330338251377135"},"PeriodicalIF":2.8,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12420964/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145030526","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":"Integrating Peritumoral and Intratumoral Radiomics with Deep Learning for Preoperative Prediction of Lymphovascular Invasion in Invasive Breast Cancer Using DCE-MRI.","authors":"Qiaomei Zhao, Hui Zhang, Wei Xing","doi":"10.1177/15330338251374945","DOIUrl":"10.1177/15330338251374945","url":null,"abstract":"<p><p>BackgroundLymphovascular invasion (LVI) is a critical factor in breast cancer (BC) prognosis and treatment planning, yet preoperative non-invasive assessment remains challenging. This research proposes the design and validation of a comprehensive artificial intelligence (AI) system that combines intratumoral and peritumoral radiomic analysis, deep learning (DL)-derived features, and clinical risk indicators extracted from dynamic contrast-enhanced MRI (DCE-MRI), with the goal of predicting LVI status in patients with BC.MethodsThis multi-institutional retrospective study included 496 IBC patients (training cohort: n = 344; validation cohort: n = 152). DCE-MRI scans were acquired preoperatively, and intratumoral/peritumoral (0-1, 1-3, 3-5 mm) radiomics features were extracted. A ResNet-50-based DL model was applied to 2.5D tumor slices, and clinical risk factors were identified via logistic regression. The least absolute shrinkage and selection operator (LASSO) method was employed to identify the most relevant features. The ensemble model was created by combining the Intra- Peri Fusion model with the clinically independent risk factors. Model performance was evaluated by sensitivity, specificity, AUC, and decision curve analysis (DCA).ResultsLVI was present in 33.8% and 32.7% of the training and validation cohorts. The SVM (Support Vector Machine) Intra-Peri Fusion model reached AUCs of 0.921 and 0.906, showing enhanced discriminative performance over single-region approaches. The ensemble model, derived from integrating a fusion model with clinical risk factors, demonstrated superior performance with AUCs of 0.951 (training) and 0.929 (validation) and high net benefit in DCA. Calibration curves confirmed excellent agreement between predicted and observed outcomes.ConclusionThe AI-driven ensemble model combining radiomics, DL, and clinical features enables accurate preoperative prediction of LVI in IBC, which holds potential for optimizing surgical planning and adjuvant therapy strategies.</p>","PeriodicalId":22203,"journal":{"name":"Technology in Cancer Research & Treatment","volume":"24 ","pages":"15330338251374945"},"PeriodicalIF":2.8,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12409024/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144969958","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":"Enhancing Specificity in Predicting Axillary Lymph Node Metastasis in Breast Cancer through an Interpretable Machine Learning Model with CEM and Ultrasound Integration.","authors":"Weimin Xu, Bowen Zheng, Chanjuan Wen, Hui Zeng, Sina Wang, Zilong He, Xin Liao, Weiguo Chen, Yingjia Li, Genggeng Qin","doi":"10.1177/15330338251334735","DOIUrl":"https://doi.org/10.1177/15330338251334735","url":null,"abstract":"<p><p>IntroductionThe study aims to evaluate the performance of an interpretable machine learning model in predicting preoperative axillary lymph node metastasis using primary breast cancer and lymph node features derived from contrast-enhanced mammography (CEM) and ultrasound (US) breast imaging reporting and data systems (BI-RADS).MethodsThis retrospective study included patients diagnosed with primary breast cancer. Two experienced radiologists extracted the BI-RADS features from the largest cross-section of the lesions and axillary lymph nodes based on CEM and US images, creating three datasets. Each dataset will train six base models to predict axillary lymph nodes, with pathological results serving as the gold standard. The top three models were used to train the five ensemble models. Additionally, SHapley Additive exPlanations (SHAP) was used to interpret the optimal model. The receiver-operating characteristic curve (ROC) and AUC were used to evaluate model performance.ResultsThis study involved 292 female patients, of whom 99 had axillary lymph node metastasis and 193 did not. The combination of CEM and ultrasound BI-RADS demonstrated the best performance in predicting axillary lymph node metastasis. Among these, the LightGBM achieved the highest AUC (0.762) and specificity (86.67%, while the ensemble model using RF as the meta-model had an AUC (0.754) and specificity (83.33%. The most important variables identified by SHAP were the long diameters of the lymph nodes in the CEM recombined image, along with their complete morphology in the low-energy image.ConclusionThe machine learning model using CEM and US BI-RADS features accurately predicted axillary lymph node metastasis before surgery, thereby serving as a valuable tool for clinical decision-making in patients with breast cancer.</p>","PeriodicalId":22203,"journal":{"name":"Technology in Cancer Research & Treatment","volume":"24 ","pages":"15330338251334735"},"PeriodicalIF":2.7,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12035205/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143998798","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}