Technology in Cancer Research & Treatment最新文献

{"title":"CAMSAP3 Suppresses Breast Cancer Metastasis and Serves as an Independent Prognostic Marker.","authors":"Chao Han, Caiping Chen, Li Xue, Xiang Lu","doi":"10.1177/15330338251381866","DOIUrl":"10.1177/15330338251381866","url":null,"abstract":"<p><p>IntroductionBreast cancer metastasis remains the leading cause of disease-related mortality. While calmodulin-regulated spectrin-associated protein 3 (CAMSAP3) has been implicated as a metastasis suppressor in other cancers, its role in breast cancer remains poorly defined. This study aimed to investigate the prognostic significance and functional impact of CAMSAP3 in breast cancer.MethodsCAMSAP3 protein expression was evaluated by immunohistochemistry in 137 primary breast cancer specimens and correlated with clinicopathological features and survival outcomes. Kaplan-Meier and Cox regression analyses were performed to assess distant relapse-free survival (DRFS). Functional assays, including wound healing and Transwell invasion assays, were conducted in MDA-MB-231 and HCC1937 cells following CAMSAP3 overexpression or knockdown. External mRNA-level validation was performed using the Kaplan-Meier Plotter database.ResultsHigh CAMSAP3 expression was significantly associated with favorable features, including lower histological grade, hormone receptor positivity, reduced proliferation index, and fewer triple-negative phenotypes. Patients with high CAMSAP3 expression exhibited significantly improved DRFS, which was independently validated using a public mRNA dataset showing improved distant metastasis-free survival (DMFS). In vitro, CAMSAP3 overexpression inhibited migration and invasion of MDA-MB-231 cells, while CAMSAP3 knockdown enhanced these phenotypes in HCC1937 cells.ConclusionCAMSAP3 is a potential metastasis suppressor and independent prognostic marker in breast cancer. Its high expression is associated with less aggressive tumor characteristics and improved survival, possibly through inhibition of cancer cell migration and invasion.</p>","PeriodicalId":22203,"journal":{"name":"Technology in Cancer Research & Treatment","volume":"24 ","pages":"15330338251381866"},"PeriodicalIF":2.8,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12457760/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145126129","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 Efficacy and Prognosis of Anlotinib in Lung Cancer Patients Using CT Radiomics.","authors":"Yan Zhang, Yaohua Chen","doi":"10.1177/15330338251383674","DOIUrl":"10.1177/15330338251383674","url":null,"abstract":"<p><p><b>Purpose:</b> Our study aimed to develop and validate a predictive model based on chest CT radiomics features combined with clinical variables to evaluate the efficacy of anlotinib and its prognostic value in patients with advanced lung cancer. <b>Methods:</b> This single-center retrospective study included 68 patients with advanced lung cancer who received anlotinib monotherapy at a tertiary grade-A hospital in China between January 2021 and July 2024. All patients had experienced disease progression after receiving standardized chemotherapy, targeted therapy, or immunotherapy prior to enrollment, had not undergone radiotherapy, and had completed all prior treatments at our hospital. Chest CT scans were performed before anlotinib treatment, and radiomics features were extracted. Based on treatment response, patients were grouped, and a radiomics model, a clinical model, and a combined model were constructed. Model performance was evaluated using receiver operating characteristic (ROC) curves, the Hosmer-Lemeshow test, calibration curves, and decision curve analysis (DCA), with internal validation performed via bootstrap resampling (500 iterations). Additionally, Kaplan-Meier survival curves were generated for the high- and low-risk groups predicted by the combined model, and survival differences were compared using the log-rank test. <b>Results:</b> The areas under the ROC curve (AUCs) for the radiomics, clinical, and combined models were 0.721, 0.812, and 0.866, respectively, with the combined model significantly outperforming the other two models (DeLong test, <i>P</i> < .05). Internal validation showed an AUC of 0.866 (95% CI: 0.751-0.967) for the combined model. The integrated model demonstrated good calibration via Hosmer-Lemeshow testing (<i>χ²</i> = 7.81, <i>P</i> = .553) and showed significant clinical net benefit within the threshold probability range of 0.15-0.85 on decision curve analysis. Survival analysis revealed statistically significant differences between the actual treatment-responsive and non-responsive groups (log-rank <i>P</i> < .05), as well as between the model-predicted high-risk and low-risk groups (log-rank <i>P</i> < .05). Multivariable Cox regression confirmed the nomogram score derived from the integrated model as an independent predictor of overall survival (HR = 1.263, 95% CI: 1.090-1.463, <i>P</i> = .002). <b>Conclusion:</b> The combined model incorporating chest CT radiomics features and clinical characteristics demonstrated high accuracy and clinical utility in predicting the efficacy and prognosis of anlotinib treatment in patients with advanced lung cancer.</p>","PeriodicalId":22203,"journal":{"name":"Technology in Cancer Research & Treatment","volume":"24 ","pages":"15330338251383674"},"PeriodicalIF":2.8,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12501454/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145239662","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":"Anlotinib as Maintenance Therapy After First-Line Chemotherapy Combined with Consolidation Radiation for Extensive-Stage Small Cell Lung Cancer.","authors":"Jinbo Ma, Xiaoyan Ma, Wei Zhang, Shanliang Hu, Rukun Zang, Xiaolong Wu, Jie Song","doi":"10.1177/15330338251317571","DOIUrl":"10.1177/15330338251317571","url":null,"abstract":"<p><strong>Background: </strong>Small cell lung cancer is sensitive to chemotherapy and radiotherapy, but local recurrence and distant metastasis occur shortly after treatment. This study aimed to evaluate the real-world value of anlotinib as a maintenance therapy in patients with extensive-stage small cell lung cancer (ES-SCLC) after first-line chemotherapy and consolidative thoracic radiotherapy (CTRT).</p><p><strong>Patients and methods: </strong>A total of 150 patients with ES-SCLC treated with first-line chemotherapy and CTRT from April 2017 to December 2021 were retrospectively analyzed. After the completion of chemoradiotherapy, patients received anlotinib according to their desire. The primary endpoints were progression-free survival (PFS) and overall survival (OS) after the first diagnosis, and the secondary endpoints were prognostic factors and safety.</p><p><strong>Results: </strong>The ORR and DCR of patients with ES-SCLC were 50.0% and 80.3%, respectively, in the anlotinib group and 42.9% and 69.0% in the no-maintenance therapy group. The 3-year OS rates were 27.6% and 12.6% in the anlotinib and observation groups (HR = 2.52, <i>P</i> = 0.003), and the median OS times were 23.8 months and 15.3 months. The 3-year PFS rates were 18.2% and 8.8% in the anlotinib and observation groups (HR = 1.76, <i>P</i> = 0.034) with median PFS times of 11.5 months and 8.8 months. After stratification on the basis of clinical response, patients who achieved CR plus PR after chemoradiotherapy had a longer median OS in the anlotinib and observation groups (34.0 months <i>vs</i> 24.8 months, HR = 2.40, <i>P</i> = 0.009). There were higher incidence rates of hand-foot syndrome (27.3% <i>vs</i> 10.5%, <i>P</i> = 0.001), gingival bleeding/hemoptysis (18.5% <i>vs</i> 4.8%, <i>P</i> = 0.015) and rash (33.3% <i>vs</i> 4.8%, <i>P</i> < 0.001) in the anlotinib group than in the observation group.</p><p><strong>Conclusion: </strong>Maintenance therapy with anlotinib improved the survival of patients with ES-SCLC after first-line chemotherapy and CTRT. Owing to the small sample size of the real-world trial, the reliability of our study needs to be confirmed in more studies.</p>","PeriodicalId":22203,"journal":{"name":"Technology in Cancer Research & Treatment","volume":"24 ","pages":"15330338251317571"},"PeriodicalIF":2.7,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11786289/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143068111","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":"Electrochemotherapy for Recurrence and/or Metastatic Skin Cancers: A Prospective Case Series in Iran.","authors":"Seyed Mojtaba YazdanParast, Sepideh Mansouri, Farshid Rostami Pouria, Navid Manoochehri, Kosar Namakin, Alvand Naserghandi, Seyed Rouhollah Miri, Habibollah Mahmoodzadeh, Omid Nabavian, Shirin Zaresharifi, Mohammad Abdolahad","doi":"10.1177/15330338251338635","DOIUrl":"https://doi.org/10.1177/15330338251338635","url":null,"abstract":"<p><p>PurposeThis study aimed to investigate the efficacy of electrochemotherapy on the three common types of skin cancer, including basal cell carcinoma (BCC), cutaneous squamous cell carcinoma (cSCC), and melanoma.Methods26 patients with skin cancer were recruited from single cancer treatment centers from 2022 to 2024. Electrochemotherapy (ECT) was performed to treat the cancerous nodules; all nodules in a patient with multiple lesions were treated. However the biggest lesions were always pointed out (according to European Standard Operating Procedures on Electrochemotherapy protocol) and their clinical response and adverse effects were evaluated during the study.Resultstotally, 104 nodules of 26 patients were assessed. Clinical complete response was achieved in 53 lesions, while partial response was observed in 51 lesions after first month of treatment. The most common adverse effect was pain which was in 65% of cases.ConclusionBCC shows a notably higher clinical complete response rate. Because the research was conducted at a single center and given the novelty of this treatment in Iran, the number of patients included in the study was limited. Electrochemotherapy (ECT) has shown significant clinical effectiveness for superficial tumors, especially for patients who have health issues related to standard therapies or who are resistant to conventional treatments. It is generally well-tolerated, with side effects predominantly consisting of temporary pain. Ongoing research aims to expand its use in deep-seated tumors that are resistant to conventional therapies.</p>","PeriodicalId":22203,"journal":{"name":"Technology in Cancer Research & Treatment","volume":"24 ","pages":"15330338251338635"},"PeriodicalIF":2.7,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12066867/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144052575","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":"Characterization of T-Cell Receptor Profiles Predicts Survival Situation in Patients with Hepatocellular Carcinoma.","authors":"Fengyan Wang, Li Deng, Ziqiang Li, Qiwei Cao, Runze Jiang, Changqing Xu, Jing Yang","doi":"10.1177/15330338251329699","DOIUrl":"10.1177/15330338251329699","url":null,"abstract":"<p><p>PurposeHepatocellular carcinoma (HCC) is the most common liver malignancy in the world, and tumor-infiltrating T cells have been shown to be closely related to the prognosis of HCC. This study investigated the potential and efficacy of T cell receptor (TCR) repertoire characterization as a biomarker for predicting survival differences.MethodsIn this study, we used high-throughput sequencing technology to systematically analyze the characteristics of TCR repertoires in tumor tissues obtained from 23 long-survivors and 8 short-survivors diagnosed with HCC.ResultsThe TCR composition in HCC long-survivors was found to be less diverse than in the short-survivors. In addition, in the context of V and J gene segments, long-survivors showed significantly higher usage of TRBJ1-3, TRBV10-1, TRBV15, and TRBV6-5, and lower usage of TRBJ2-2. Both principal component analysis (PCA) and the motif diagram of complementary determination region 3 (CDR3) sequences could clearly discriminate short- and long-survivors. And there were five up-regulated and one down-regulated CDR3 sequences in the LS group compared with the SS group. According to the characteristics of TCR repertoire, we also established the survival-related evaluation system and the prediction model for the survival period of HCC patients.ConclusionOur study adds to the existing knowledge of TCR rearrangement profiles in HCC patients by elucidating the differential TCR rearrangement profiles between long-term and short-term surviving HCC patients. Also, our analysis identified a number of TCR genes that are significantly associated with survival, and these may not only serve as prognostic biomarkers but may also play an important role in antigen-specific immunotherapy.</p>","PeriodicalId":22203,"journal":{"name":"Technology in Cancer Research & Treatment","volume":"24 ","pages":"15330338251329699"},"PeriodicalIF":2.7,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11954561/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143731678","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":"Deep Learning-Based Auto-Segmentation for Liver Yttrium-90 Selective Internal Radiation Therapy.","authors":"Jun Li, Wookjin Choi, Rani Anne","doi":"10.1177/15330338251327081","DOIUrl":"10.1177/15330338251327081","url":null,"abstract":"<p><p>The aim was to evaluate a deep learning-based auto-segmentation method for liver delineation in Y-90 selective internal radiation therapy (SIRT). A deep learning (DL)-based liver segmentation model using the U-Net3D architecture was built. Auto-segmentation of the liver was tested in CT images of SIRT patients. DL auto-segmented liver contours were evaluated against physician manually-delineated contours. Dice similarity coefficient (DSC) and mean distance to agreement (MDA) were calculated. The DL-model-generated contours were compared with the contours generated using an Atlas-based method. Ratio of volume (RV, the ratio of DL-model auto-segmented liver volume to manually-delineated liver volume), and ratio of activity (RA, the ratio of Y-90 activity calculated using a DL-model auto-segmented liver volume to Y-90 activity calculated using a manually-delineated liver volume), were assessed. Compared with the contours generated with the Atlas method, the contours generated with the DL model had better agreement with the manually-delineated contours, which had larger DSCs (average: 0.94 ± 0.01 vs 0.83 ± 0.10) and smaller MDAs (average: 1.8 ± 0.4 mm vs 7.1 ± 5.1 mm). The average RV and average RA calculated using the DL-model-generated volumes are 0.99 ± 0.03 and 1.00 ± 0.00, respectively. The DL segmentation model was able to identify and segment livers in the CT images and provide reliable results. It outperformed the Atlas method. The model can be applied for SIRT procedures.</p>","PeriodicalId":22203,"journal":{"name":"Technology in Cancer Research & Treatment","volume":"24 ","pages":"15330338251327081"},"PeriodicalIF":2.7,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11951913/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143731684","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Diagnostic Value of ¹⁸F-FDG PET/CT Radiomics in Lymphoma: A Systematic Review and Meta-Analysis.","authors":"Chaoying Liu, Jun Zhao, Heng Zhang, Xinye Ni","doi":"10.1177/15330338251342860","DOIUrl":"10.1177/15330338251342860","url":null,"abstract":"&lt;p&gt;&lt;p&gt;IntroductionVarious machine learning models and features have been proposed for lymphoma diagnosis using &lt;sup&gt;18&lt;/sup&gt;F-fluorodeoxyglucose (&lt;sup&gt;18&lt;/sup&gt;F-FDG) PET/CT radiomics. This research aimed to systematically evaluate the diagnostic value of &lt;sup&gt;18&lt;/sup&gt;F-FDG PET/CT radiomics in lymphoma by conducting a meta-analysis.MethodsData from published studies regarding the diagnosis of lymphoma using &lt;sup&gt;18&lt;/sup&gt;F-FDG PET/CT radiomics, from January 2010 to July 2024, were gathered from PubMed, Web of Science, and the Cochrane Library. Following their separate searches and screenings of the literature, two researchers extracted data and assessed the caliber of all the included studies. The quality assessment involved the Quality Assessment of Diagnostic Accuracy Studies 2 (QUADAS-2), the Radiomics Quality Score (RQS), and the METhodological RadiomICs Score (METRICS). The meta-analysis was conducted by using RevMan 5.4.1, R 4.4.0, and Stata 17.0 software. Six meta-regressions were conducted on study performance, considering sample size, image modality, region of interest (ROI) selection, ROI segmentation, radiomics mode, and algorithms.ResultsIn total, 20 studies classified as type 2a or above according to the Transparent Reporting of a Multivariable Prediction Model for Individual Prognosis or Diagnosis (TRIPOD) statement were included for this systematic review and meta-analysis. The studies achieved an average RQS of 13 (ranging from 10 to 17), accounting for 36.1% of the total points. The average METRICS score was 69.3% (ranging from 54.8% to 80.9%). The quality category of the studies is mainly \"good\". The results of our meta-analysis showed that the pooled sensitivity (SEN), specificity (SPE), positive likelihood ratio, negative likelihood ratio and diagnostic odds ratio with 95% confidence interval (&lt;i&gt;CI&lt;/i&gt;) were 0.82 (0.78, 0.88), 0.83 (0.76, 0.87), 4.7 (3.4, 6.6), 0.20 (0.15, 0.28) and 23 (13, 42), respectively. The area under the curve of the summary receiver operating characteristic curve was 0.90 (0.87, 0.92). The results of Spearman correlation analysis revealed no threshold effect among the studies (&lt;i&gt;P&lt;/i&gt; = .423). Significant heterogeneity was observed among the studies (overall &lt;i&gt;I&lt;sup&gt;2&lt;/sup&gt;&lt;/i&gt; = 83.7%; 95% &lt;i&gt;CI&lt;/i&gt;: 76.0, 88.9; &lt;i&gt;P&lt;/i&gt; &lt; .01). Meta-regressions indicated that sample size and ROI selection contributed to the heterogeneity in SEN, while algorithms affected the heterogeneity in SPE (&lt;i&gt;P&lt;/i&gt; &lt; .05). Deeks' test confirmed there was no significant publication bias in all the included studies. The Fagan nomogram showed an absolute increase of 34% in the post-test probability following a positive test result.ConclusionThe results supported that &lt;sup&gt;18&lt;/sup&gt;F-FDG PET/CT radiomics has high diagnostic value for lymphoma. However, there is high heterogeneity among different studies. In the future, clinical practicality needs to be substantiated by more prospective studies with rigorous adherence to existing g","PeriodicalId":22203,"journal":{"name":"Technology in Cancer Research & Treatment","volume":"24 ","pages":"15330338251342860"},"PeriodicalIF":2.7,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12099142/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144111985","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":"Multimodal Model for Non-Invasive Detection of DRD2, SSTR2 and ESR1 Receptor Profiling in Pituitary Neuroendocrine Tumors: A Retrospective Study.","authors":"Jianglong Lu, Xianpeng Wang, Jinghao Jin, Fanjie Xu, Runhua Tang, Cheng Han, Zerui Wu, Zhipeng Su, Yuhang Guo","doi":"10.1177/15330338251353305","DOIUrl":"10.1177/15330338251353305","url":null,"abstract":"<p><p><b>Introduction</b>: The dopamine receptor D2 (DRD2), somatostatin receptor 2 (SSTR2), and oestrogen receptor 1 (ESR1) have been demonstrated to play a critical role in determining treatment response in pituitary neuroendocrine tumors (PitNETs). However, the identification of these receptors preoperative presented a significant challenge. The objective of this study was to develop a predictive model that employs both radiomics and deep learning features in conjunction with conventional magnetic resonance imaging (MRI) to predict the expression of these three receptors in PitNETs in a retrospective study. <b>Materials and Methods</b>: A total of 186 patients with complete imaging data (coronal T1-weighted, T2-weighted, and contrast-enhanced T1-weighted MRI) were included for model construction (training set, n = 148; validation set, n = 38). Semiquantitative analysis of re-verse transcription polymerase chain reaction and immunohistochemistry of the samples was performed to complete the classification of high or low expressions of these three drug targets in patients. A multimodal model was validated using a receiver operating characteristic analysis on an independent validation set. <b>Results</b>: The dynamic multi-layer perceptron (MLP) classifier showed an area under the curve (AUC) of 0.9571 (DRD2), 0.9191 (SSTR2), and 0.9485 (ESR1) in the training set and an AUC of 0.9260 (DRD2), 0.9084 (SSTR2), and 0.9409 (ESR1) in the validation set, which fitted well with the training set. The dynamic MLP classifier achieved the highest performance among all the individual models in the validation set. <b>Conclusions</b>: The dynamic MLP classifier can noninvasively predict the expression of key targets of PitNETs, which will help guide clinical drug treatment decisions.</p>","PeriodicalId":22203,"journal":{"name":"Technology in Cancer Research & Treatment","volume":"24 ","pages":"15330338251353305"},"PeriodicalIF":2.7,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12188075/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144476804","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":"Central-boost Ablative Radiation Therapy for Solid Tumors: Study Protocol of a Single-arm, Phase II Trial (CBART).","authors":"Lingong Jiang, Yangsen Cao, Xiaolan Yin, Chunshan Yu, Yusheng Ye, Xiaofei Zhu, Huojun Zhang","doi":"10.1177/15330338251350833","DOIUrl":"10.1177/15330338251350833","url":null,"abstract":"<p><p>BackgroundThough stereotactic body radiation therapy (SBRT) has been widely used in advanced tumors, ablative doses may not be appropriate in the case of large tumors or those abutting to the gastrointestinal tracts, resulting in unfavorable outcomes. Therefore, partial irradiation with high doses to tumors have been investigated. In order to achieve a larger high dose area within the tumor center, we developed a novel radiation modality, which was central-boost ablative radiation therapy (CBART). It was delivered by SBRT, with a central ablative dose in the tumor and a relatively low margin dose. And we tried to assess the efficacy of CBART for patients with large tumors or tumors adjacent to the gastrointestinal tracts.MethodsIt is a prospective, single-arm, phase II trial. Eligible patients would receive CBART. Gross tumor volume (GTV) was defined as a radiographically evident gross disease. The margin of GTV was shrinked to form central core GTV (cGTV). The volume of cGTV should be 50% of GTV volume. A 2-5 mm margin expansion on GTV formed planning target volume (PTV). While no margin expansion was performed on cGTV. The prescription dose of tumor margin was 30-45Gy/5f, determined by the tumor location and pathological features. While the prescription dose of cGTV was 120%-150% of that of tumor margin. Ninety percent of PTV and cGTV should be covered by the prescription dose. After CBART, sequential systemic therapy, including chemotherapy, targeted therapy or immunotherapy would be given according to pathological types and tumor stages. The primary outcome is one-year local control rate.DiscussionAn ablative dose to the hypoxic tumor center while a relatively low dose to the tumor margin may improve local control in the case of large tumors or those abutting the gastrointestinal tracts. Further investigations are required to assess the clinical benefits of CBART.</p>","PeriodicalId":22203,"journal":{"name":"Technology in Cancer Research & Treatment","volume":"24 ","pages":"15330338251350833"},"PeriodicalIF":2.7,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12163299/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144275926","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":"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}