Technology in Cancer Research & Treatment最新文献

{"title":"Predictive Effect of Prognostic Nutritional Index on Lymph Node Regression Rate in Patients with Locally Advanced Nasopharyngeal Carcinoma Undergoing Concurrent Chemoradiotherapy.","authors":"JunMei Song, Ting Liu, YaJing Wen, YuQing Lv, Qiulin Huang, RenSheng Wang, Jun Bie","doi":"10.1177/15330338251356541","DOIUrl":"10.1177/15330338251356541","url":null,"abstract":"<p><p>ObjectiveDetermining reliable predictive indicators of therapeutic efficacy for patients with nasopharyngeal carcinoma (NPC) can help select those who will benefit the most from treatment. This research assessed the predictive significance of the prognostic nutritional index (PNI) in patients with locally advanced nasopharyngeal carcinoma (LANPC) receiving concurrent chemoradiotherapy (CCRT).MethodsA retrospective analysis was performed on 128 patients with LANPC who underwent CCRT. The PNI was calculated using peripheral blood values, the optimal cut-off value of the PNI was determined using the receiver operating characteristic (ROC) curve, and the patients were categorized into low- and high-PNI groups. The Mann-Whitney U test and Pearson's chi-square test were employed to test the differences between groups. Univariate and multivariate logistic regression analyses were used to determine the predictors of a good response to CCRT.ResultsThe optimal cut-off value for PNI was 51.95. The regression rates of the cervical lymph nodes (CLNs) and total lymph nodes (TLNs) were higher in the high-PNI group compared to the low-PNI group (CLNs 78.67% and 65.91%; TLNs 78.56% and 67.60% respectively). Multivariate logistic regression showed that the PNI served as an independent predictor of CCRT efficacy in patients with LANPC.ConclusionThe PNI is a non-invasive, low-cost, and easy-to-use indicator in clinical practice for patients with LANPC undergoing CCRT. Patients with LANPC and low PNI require attention to ensure early diagnosis of residual disease and timely rescue treatment. These findings may help develop treatment strategies and clinical risk stratification.</p>","PeriodicalId":22203,"journal":{"name":"Technology in Cancer Research & Treatment","volume":"24 ","pages":"15330338251356541"},"PeriodicalIF":2.7,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12231972/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144544961","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":"Incorporating Percutaneous Laser Ablation for Early Breast Cancer Treatment: A Systematic Review.","authors":"Danielle Ramos Martin Matsumoto, Gil Facina","doi":"10.1177/15330338241300743","DOIUrl":"10.1177/15330338241300743","url":null,"abstract":"<p><p><b>Objectives:</b> We conducted a systematic review to compile the findings of all published studies on the use of percutaneous laser ablation (PLA) in the treatment of early-stage breast cancer. We aimed to identify appropriate methodology as well as parameters for the selection of suitable patients to optimize outcomes with the use of PLA. Additionally, we aimed to analyze whether this method is a viable alternative to current surgical treatments employed. <b>Methods:</b> The PRISMA 2020 method was applied. The terms \"laser ablation\" AND \"breast cancer\" were used to select all articles published up to January 2024 on the PubMed and Embase platforms. Articles in English were included. Only original articles were considered for this systematic review. Review articles, editorials, letters, and studies ex-vivo or not performed in humans were excluded. <b>Results:</b> Seventeen articles, including 308 patients were analyzed. Among the studies describing the complete response rate to assess treatment success, there was no residual tumor after ablation in 74.4% of the patients. MRI was the best exam to evaluate the effectiveness of the ablative procedure with a NPV of 92% to 100%. Skin burn was the most commonly observed complication, occurring in 6% of patients. Other less frequent complications were hematoma/bleeding, pain, nodulation, erythema, seroma, and fat necrosis. <b>Conclusions:</b> The use of PLA remains restricted to cases with specific indications or within the context of research protocols. However, future studies may validate this promising technique for the local treatment of early-stage breast cancer. This study was registered at INPLASY (registration number: INPLASY2024100045).</p>","PeriodicalId":22203,"journal":{"name":"Technology in Cancer Research & Treatment","volume":"24 ","pages":"15330338241300743"},"PeriodicalIF":2.8,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11898239/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142971968","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":"Ultrasound Video-Based Radiomics Analysis for Differentiating Benign and Malignant Breast Lesions.","authors":"Jiangfeng Wu, Lijing Ge, Yun Jin, Xiaoyun Wang","doi":"10.1177/15330338251377374","DOIUrl":"10.1177/15330338251377374","url":null,"abstract":"<p><p>ObjectiveTo evaluate the diagnostic performance of a combined model incorporating ultrasound video-based radiomics features and clinical variables for distinguishing between benign and malignant breast lesions.MethodsA total of 346 patients (173 benign and 173 malignant) were retrospectively enrolled. Breast ultrasound videos were acquired and processed using semi-automatic segmentation in 3D Slicer. Radiomics features were extracted from volumetric tumor regions and refined using feature selection methods. Models were constructed using clinical variables, radiomics features, and their combination. Model performance was evaluated using receiver operating characteristic (ROC) analysis and area under the curve (AUC) values.ResultsThe clinical model incorporating age, tumor size, and Breast Imaging Reporting and Data System (BI-RADS) classification achieved an AUC of 0.873. The radiomics model, utilizing 14 selected features, attained an AUC of 0.836. The combined model, integrating radiomics and clinical data, demonstrated significantly improved predictive performance with an AUC of 0.926, surpassing the BI-RADS-based model (AUC = 0.737). Internal validation using bootstrap resampling confirmed the robustness of the combined model (AUC = 0.901-0.954).ConclusionThe integration of ultrasound video-based radiomics with clinical characteristics significantly improves the differentiation of benign and malignant breast tumors compared to conventional BI-RADS evaluation. This approach may enhance diagnostic accuracy and facilitate more precise clinical decision-making.</p>","PeriodicalId":22203,"journal":{"name":"Technology in Cancer Research & Treatment","volume":"24 ","pages":"15330338251377374"},"PeriodicalIF":2.8,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12417664/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145016149","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":"Stereotactic Body Radiotherapy for Extracranial Oligometastatic Renal Cell Carcinoma: State of the Art and Future Perspectives.","authors":"Sander Vandaele, Maarten Albersen, Benoit Beuselinck, Karolien Goffin, Vincent Vandecaveye, Henri Vandermeulen, Charlien Berghen","doi":"10.1177/15330338251357344","DOIUrl":"10.1177/15330338251357344","url":null,"abstract":"<p><p>Traditionally, radiotherapy in metastatic renal cell carcinoma (RCC) was applied for the palliation of symptoms and the control of critical sites such as bone lesions and brain metastases. However, technological advances in radiotherapy (RT) planning and delivery made it possible to precisely deliver high dose radiotherapy at a confined target volume. One such approach is stereotactic body radiotherapy (SBRT). In patients presenting with limited metastatic burden, known as oligometastatic RCC (omRCC), SBRT can be of interest to maintain local control, in order to defer the onset of either a first or a subsequent line of systemic treatment. In this narrative review, we summarize the prospective and retrospective evidence on SBRT as a treatment option for omRCC, and give insight into the future perspectives.</p>","PeriodicalId":22203,"journal":{"name":"Technology in Cancer Research & Treatment","volume":"24 ","pages":"15330338251357344"},"PeriodicalIF":2.7,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12276489/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144650545","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":"MR-Guided Adaptive Radiotherapy in Localized Prostate Cancer.","authors":"Andrea Gaetano Allegra, Luca Nicosia, Michele Rigo, Nicola Bianchi, Riccardo Filippo Borgese, Antonio De Simone, Niccolò Giaj-Levra, Davide Gurrera, Stefania Naccarato, Edoardo Pastorello, Francesco Ricchetti, Gianluisa Sicignano, Ruggero Ruggieri, Filippo Alongi","doi":"10.1177/15330338241297231","DOIUrl":"10.1177/15330338241297231","url":null,"abstract":"<p><p>MR-guided radiotherapy (MRgRT) is novel treatment modality in Radiation Oncology that could allow a higher precision and tolerability of Radiation Treatments. This modality is possible due to dedicated systems consisting of a MR scanner mounted on a conventional linac and software that permit daily online treatment plan adaptation. Prostate cancer (PC) is one of the most common malignancies in RO clinical practice and currently under investigation with this new technology. The focus of this review is to describe the current state of the art and clinical results of MRgRT in the treatment of PC. The available technology are briefly described, as well as the published literature and possible future applications.</p>","PeriodicalId":22203,"journal":{"name":"Technology in Cancer Research & Treatment","volume":"24 ","pages":"15330338241297231"},"PeriodicalIF":2.7,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11770696/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143047974","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 Early Thyroid Screening Model Based on Transformer and Secondary Transfer Learning for Chest and Thyroid CT Images.","authors":"Na Han, Rui Miao, Dongwei Chen, Jinrui Fan, Lin Chen, Siyao Yue, Tao Tan, Bowen Yang, Yapeng Wang","doi":"10.1177/15330338251323168","DOIUrl":"10.1177/15330338251323168","url":null,"abstract":"<p><p>IntroductionThyroid cancer is a common malignant tumor, and early diagnosis and timely treatment are crucial to improve patient prognosis. With the increasing use of enhanced CT scans, a new opportunity for early thyroid cancer screening has emerged. However, existing CT-based models face challenges due to limited datasets, small sample sizes, and high noise.MethodsTo address these challenges, we collected enhanced CT scan image data from 240 patients in Guangdong and Xinjiang, China, and established a CT dataset for early thyroid cancer screening. We propose a deep learning model, the DVT model, which combines transformer DNN and transfer learning techniques to integrate time series data and address small sample sizes and high noise.ResultsThe experimental results show that the DVT model achieves a prediction accuracy of 0.96, AUROC of 0.97, specificity of 1, and sensitivity of 0.94. These results indicate that the DVT model is a highly effective tool for early thyroid cancer screening.ConclusionThe DVT model has the potential to assist clinicians in identifying potential thyroid cancer patients and reducing patient expenses. Our study provides a new approach to thyroid cancer screening using enhanced CT scans and demonstrates the effectiveness of deep learning techniques in addressing the challenges associated with CT-based models.</p>","PeriodicalId":22203,"journal":{"name":"Technology in Cancer Research & Treatment","volume":"24 ","pages":"15330338251323168"},"PeriodicalIF":2.7,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11960174/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143754597","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":"Molecular Mechanisms and Therapeutic Prospects of Immunotherapy and Targeted Therapy in Primary Central Nervous System Lymphoma.","authors":"Lin Zhong, Anqing Lu, Xiyue Lu, Xiaoyin Liu, Lujia Cao, Shihong Zhu, SiJun Diao, Xu Cheng, Hongwei Wu, Jing Chen","doi":"10.1177/15330338251319394","DOIUrl":"10.1177/15330338251319394","url":null,"abstract":"<p><p>Primary central nervous system lymphoma (PCNSL) is a very rare extranodal non-Hodgkin's lymphoma confined to the brain, eyes, spinal cord, and cerebrospinal fluid (CSF). This disease is highly aggressive. For decades, high-dose methotrexate-based induction regimens have been the standard treatment for PCNSL and have significantly improved patient overall survival (OS). However, some patients still experience disease recurrence or develop drug resistance. With a deeper understanding of the pathophysiology of PCNSL, various therapies, including CD20 monoclonal antibodies, Bruton's tyrosine kinase (BTK) inhibitors, immunomodulatory drugs, immune checkpoint inhibitors, phosphoinositide 3-kinase (PI3 K)/mammalian target of rapamycin(mTOR) inhibitors, and chimeric antigen receptor (CAR) -T cells are increasingly being applied and have demonstrated considerable efficacy. These therapies have paved the way for novel treatment strategies in PCNSL, representing a highly promising field. Investigating the mechanisms, specific targets, and signaling pathways, as well as interactions with the tumor microenvironment (TME), can provide a solid foundation for further exploration and potentially enhance the optimization of treatment approaches for PCNSL. This review seeks to explore the characteristics of the TME in PCNSL, elucidate the molecular mechanisms of various immunotherapies and targeted therapies, examine their interactions with the TME, and summarize the advancements in the research of PCNSL immunotherapy and targeted therapy.</p>","PeriodicalId":22203,"journal":{"name":"Technology in Cancer Research & Treatment","volume":"24 ","pages":"15330338251319394"},"PeriodicalIF":2.7,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11800258/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143256471","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":"Novel Anticancer Triple Formula Based on Aptamer-Conjugated PEGylated Nanoliposomes.","authors":"Ali Al-Samydai, Hamdi Nsairat, Moath Alqaraleh, Maha N Abu Hajleh, Areej Jaber, Lidia Al-Halaseh, Hanan Azzam, Qasim Khalid Alazzawi, Israa Al-Ani, Simone Carradori, Walhan Alshaer","doi":"10.1177/15330338251356548","DOIUrl":"10.1177/15330338251356548","url":null,"abstract":"<p><p>BackgroundCancer remains a leading cause of death worldwide, necessitating the development of affordable and innovative therapies to reduce its human and economic burden.ObjectivesIn this study, we aimed to develop a synergistic anticancer formula encapsulated in nanoliposomes to enhance efficacy and minimize side effects. Additionally, we explored the effect of aptamer conjugation on the efficacy and stability of the formula.MethodsThe Etoricoxib-β-cyclodextrin complex was prepared using the kneading method, and nanoliposomes were developed via thin film hydration. The AS1411 aptamer was conjugated to the nanoliposomes to target nucleolin, a protein overexpressed in cancer cells. The etoricoxib-β-cyclodextrin complex was characterized using proton nuclear magnetic resonance, and various liposome properties, including size, encapsulation efficiency, and stability, were optimized. The release profiles of the active compounds were evaluated using high-performance liquid chromatography, and their cytotoxicity was assessed in human cancer cell lines.ResultsThe nanoliposomes co-loaded with the three agents and their aptamer-conjugated counterpart showed optimal characteristics, with particle sizes of 133.3 ± 1.45 nm and 174.8 ± 4.78 nm, and zeta potentials of -15.26 ± 1.80 mV and -15.66 ± 2.57 mV, respectively. The encapsulation efficiencies were 88.63% (raloxifene), 41.73% (etoricoxib), and 39.26% (naringin) without the aptamer, and 81.99%, 36.66%, and 38.33%, respectively, with the aptamer. The IC₅₀ of the formula for the three co-loaded agents was 167.4 µg/mL for A549 cells and 2.6 µg/mL for MCF-7 cells. Cytotoxicity was further enhanced using their aptamer conjugate, particularly against the MDA-MB-231 cell line.ConclusionThe novel triple-drug-loaded, aptamer-conjugated nanoliposome formula may be a future cancer treatment strategy.</p>","PeriodicalId":22203,"journal":{"name":"Technology in Cancer Research & Treatment","volume":"24 ","pages":"15330338251356548"},"PeriodicalIF":2.7,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12227944/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144554947","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":"Pretreatment CT-Based Machine Learning Radiomics Model Predicts Response in Inoperable Stage III NSCLC Treated with Concurrent Radiochemotherapy Plus PD-1 Inhibitors.","authors":"Ya Li, Min Zhang, Yong Hu, Bo Du, Youlong Mo, Tianchu He, Mingdan Zhao, Benlan Li, Ji Xia, Zhongjun Huang, Fangyang Lu, Zhen Huang, Bing Lu, Jie Peng","doi":"10.1177/15330338251351109","DOIUrl":"10.1177/15330338251351109","url":null,"abstract":"<p><p>ObjectiveTo develop and validate a CT-based radiomics model for predicting sequential immunotherapy response after concurrent radiochemotherapy (CCRT) in patients with unresectable stage III non-small cell lung cancer (NSCLC).MethodsThe study retrospectively included 71 patients who received sequential immunotherapy after concurrent chemoradiotherapy (CCRT) between January 2019 and December 2022, while prospectively including 17 additional patients between January 2023 and July 2023. The study documented each patient's tumor response and prognosis within two months of completing treatment. Patients were then categorized based on their treatment response, resulting in the identification of two distinct groups: treatment-responsive group and treatment-insensitive group. First, ITK-SNAP software was used to delineate the primary tumor lesions in the lung window and define a region of interest (ROI). Second, features were extracted using Python (version 3.6) and filtered using Least absolute shrinkage and selection operator regression. Third, radiological models were built using six machine learning algorithms: logistic regression (LR), discriminant analysis (DA), neural network (NN), random forest (RF), support vector machine (SVM) and K-Nearest Neighbour (KNN). Finally, Kaplan-Meier survival analysis was performed for high- and low-risk patients predicted by radiomic modeling.ResultsBased on the performance of radiomics models constructed by various machine learning algorithms in the prospective validation set, the LR with the highest AUC value (AUC: 90.00%) was finally selected, which also performed well in the independent test set (AUC: 84.96%). Risk stratification of patients based on the radiomic model constructed by LR was excellent for PFS (P = 0.001) and OS (P = 0.019) in the training set, PFS (P = 0.010) and OS (P = 0.028) in the prospective validation set, and PFS (P = 0.014) and OS (P = 0.041) in the test set.ConclusionPretreatment CT-based radiomics model accurately and efficiently predicts treatment response and risk stratification in patients with unresectable stage III NSCLC treated with concurrent chemoradiotherapy and sequential programmed death-1 inhibitor therapy. Prior to prospective data collection, the study was registered with the China Clinical Trial Registry under the trial registration name: Prediction of concurrent chemoradiotherapy efficacy and its related molecular signaling pathway by medical artificial intelligence model based on CT of lung cancer, with the registration number: ChiCTR2100053175 (https://www.chictr.org.cn/showproj.html?proj = 136872).</p>","PeriodicalId":22203,"journal":{"name":"Technology in Cancer Research & Treatment","volume":"24 ","pages":"15330338251351109"},"PeriodicalIF":2.7,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12163266/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144275927","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":"Orosomucoid 1 is a Potential Prognostic Biomarker for Uterine Sarcoma.","authors":"Dan Yuan, Yue Huang, Ying Cai, Chi Zhang, Jin-Jing Wang, Jian-Guo Zhou","doi":"10.1177/15330338251343487","DOIUrl":"10.1177/15330338251343487","url":null,"abstract":"<p><p>IntroductionUterine sarcoma (US) is a rare tumor characterized by high aggressiveness, a tendency for recurrence and distant metastasis, and an extremely poor prognosis. In this study, we evaluated the expression of Orosomucoid 1 (ORM1) in different subtypes of US and the relationship between survival rates and clinicopathological features.MethodA retrospective study was conducted on 50 cases diagnosed with US in our hospital from 2011 to 2023. Immunohistochemistry (IHC) was used to detect the expression levels of ORM1 in different subtypes of US.The chi-square test and Kaplan-Meier survival analysis were used to analyze the relationship between ORM1 expression and clinical parameters as well as prognosis. Cox analysis was employed to evaluate the relationships between prognosis and clinical parameters in US.ResultCompared to normal proliferative endometrial tissue (NPE), the expression of ORM1 was downregulated in low-grade endometrial stromal sarcoma (LG-ESS), high-grade endometrial stromal sarcoma (HG-ESS), and undifferentiated uterine sarcoma (UUS) (P < .001,P < .001,and P < .001, respectively). Compared to normal uterine smooth muscle tissue (UNSM), the expression of ORM1 was upregulated in leiomyosarcoma (LMS) (P = .006). High ORM1 expression levels in US patients were associated with poor overall survival (OS) and progression-free survival (PFS) (P = .027 and P = .005, respectively). Multivariate COX analysis revealed that tumor stage and ORM1 expression are independent prognostic factors for US patients.ConclusionORM1 is expressed at low levels in ESS and at high levels in LMS. ORM1 potentially serve as a novel biomarker for the diagnosis, classification, and prognosis of US.</p>","PeriodicalId":22203,"journal":{"name":"Technology in Cancer Research & Treatment","volume":"24 ","pages":"15330338251343487"},"PeriodicalIF":2.7,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12089707/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144102682","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}