Clinical Medicine Insights-Oncology最新文献

{"title":"Efficacy and Safety of Ribociclib Plus Endocrine Therapy Versus Endocrine Therapy Alone in HR-Positive/HER2-Negative Breast Cancer: A Systematic Review and Meta-Analysis of Randomized Controlled Trials.","authors":"Reechashree Dhungana, Parikshit Prasai, Bishal Paudel, Kamal Ranabhat, Simit Sapkota, Sunil Shrestha","doi":"10.1177/11795549251402955","DOIUrl":"10.1177/11795549251402955","url":null,"abstract":"<p><strong>Background: </strong>Recent trials of ribociclib, a cyclin-dependent kinase inhibitor, have shown promising results in patients with hormone receptor-positive (HR+)/HER2-negative (HER2-) breast cancer. This meta-analysis evaluates the efficacy and safety of combining ribociclib with endocrine therapy (ET) versus ET alone in this patient population.</p><p><strong>Methodology: </strong>A comprehensive search of PubMed, Embase, CENTRAL, Scopus, and Web of Science (up to July 2024, no language restrictions) identified randomized controlled trials (RCTs) comparing endocrine therapy (ET) with and without ribociclib for HR+/HER2- breast cancer. Bias was assessed using Cochrane's Risk of Bias tool. Hazard ratios (HRs) for overall survival (OS) and progression-free survival (PFS) and odds ratios (ORs) for Grade III + adverse effects (neutropenia, hepatobiliary toxicity, QT prolongation, and interstitial pneumonitis) were calculated with 95% confidence intervals (CI). A random-effects model accounted for heterogeneity (<i>I</i>² statistic). The protocol was registered in PROSPERO (CRD42024558512).</p><p><strong>Results: </strong>The meta-analysis of 5 RCTs (7286 participants) showed ribociclib plus ET significantly improved OS (HR 0.76, 95% CI 0.68-0.85, <i>P</i> < .001) and PFS (HR 0.57, 95% CI 0.51-0.64, <i>P</i> < .001) compared with ET alone. Grade III + adverse effects of special interest that were more common with ribociclib plus ET include neutropenia (OR 75.76, 95% CI 35.23-162.93, <i>P</i> < .001), hepatobiliary toxicity (OR 2.54, 95% CI 1.32-4.90, <i>P</i> = .005), and QT prolongation (OR 2.95, 95% CI 1.69-5.16, <i>P</i> < .001). The rare grade III + interstitial pneumonitis events (OR 3.36, 95% CI 0.56-20.07, <i>P</i> = .18) also warrant ongoing vigilance.</p><p><strong>Conclusion: </strong>Ribociclib combined with ET improves OS and PFS but is associated with higher rates of adverse effects, compared with ET alone, highlighting the need for careful monitoring and management.</p><p><strong>Funding: </strong>None.</p>","PeriodicalId":48591,"journal":{"name":"Clinical Medicine Insights-Oncology","volume":"19 ","pages":"11795549251402955"},"PeriodicalIF":1.9,"publicationDate":"2025-12-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12717364/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145805944","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":"Colonic Gastrointestinal Stromal Tumors Demonstrate Unique Biological Characteristics: A Retrospective, Propensity Score-Matched Cohort Study Pooling Multicenter and Literature-Derived Individual Patient Data.","authors":"Zhuo-Fei Li, Guo-Shuai Chen, Han Li, Chen Li, Hao Wu, Ke-Wei Jiang, Ying-Jiang Ye","doi":"10.1177/11795549251399463","DOIUrl":"10.1177/11795549251399463","url":null,"abstract":"<p><strong>Background: </strong>Colonic gastrointestinal stromal tumors (cGISTs) represent an exceptionally rare subtype of gastrointestinal stromal tumors (GISTs) and exhibit distinct clinicopathological features. Nonetheless, limited research has systematically assessed the prognostic differences between cGISTs and GISTs originating from other anatomical sites under comparable baseline and oncological conditions. Current prognostic stratification systems for GISTs have significant limitations in evaluating colonic subtypes.</p><p><strong>Methods: </strong>A retrospective case-control study. Surgical cGIST cases (2012-2024) from 4 tertiary hospitals were analyzed, along with 676 contemporaneous gastric GISTs (gGISTs) controls. Additional individual patient data were extracted from published articles, reviews, letters, and comments identified through a systematic literature search. Propensity score matching (1:4) was performed to balance baseline variables before comparing survival outcomes.</p><p><strong>Results: </strong>Compared with gGISTs, cGISTs exhibited distinct clinicopathological characteristics, including older average age (<i>P</i> = .001), larger tumor diameter (<i>P</i> = .003), higher mitotic index (<i>P</i> = .007), and lower positive expression rates of CD117 (79.25% vs 98.81%, <i>P</i> < .001), CD34 (80.43% vs 98.81%, <i>P</i> < .001), and DOG-1 (76.67% vs 98.35%, <i>P</i> < .001). After propensity score matching successfully eliminated baseline differences, gGIST patients demonstrated superior survival outcomes, with higher 1-, 3-, and 5-year recurrence-free survival (RFS) rates of 100.0%, 98.76%, and 94.13%, compared with 95.50%, 86.69%, and 86.69% in matched cGIST cases. Similarly, gGIST patients showed higher 1-, 3-, and 5-year overall survival (OS) rates of 100.0%, 99.39%, and 97.06%, compared with 95.50%, 86.58%, and 82.45% in matched cGIST cases. Of note, the difference in OS was statistically significant (<i>P</i> = .04), whereas the difference in RFS did not reach significance (<i>P</i> = .31).</p><p><strong>Conclusions: </strong>The cGISTs exhibit distinct clinicopathological characteristics and are associated with a significantly poorer prognosis compared with gGISTs. Therefore, diagnostic and therapeutic strategies for cGISTs warrant further exploration and refinement.</p>","PeriodicalId":48591,"journal":{"name":"Clinical Medicine Insights-Oncology","volume":"19 ","pages":"11795549251399463"},"PeriodicalIF":1.9,"publicationDate":"2025-12-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12708988/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145783447","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 Value of Patient-Derived Tumor Cell Cluster-Based Drug Sensitivity Assay in Advanced NSCLC.","authors":"Yangchun Gu, Leilei Yang, Hua Zhang, Shenyi Yin, Lu Yang, Zhentao Liu, Jinyu Yu, Huiying Huang, Juan Li, Baoshan Cao","doi":"10.1177/11795549251405740","DOIUrl":"10.1177/11795549251405740","url":null,"abstract":"<p><strong>Background: </strong>Patient-derived tumor cell cluster (PTC)-based drug sensitivity assays show promise for enabling precision drug selection; however, their predictive value in advanced non-small cell lung cancer (NSCLC) requires further elucidation.</p><p><strong>Methods: </strong>To assess the concordance between PTC-based drug sensitivity and clinical outcomes, we conducted a single-center prospective cohort study at Peking University Third Hospital from August 2021 to August 2024. We enrolled 38 consecutive patients, from whom 44 fresh tumor specimens were obtained for PTC-based drug sensitivity assays and compared with paired clinical outcomes of chemotherapy and targeted therapy regimens. Concordance was assessed using the Kappa statistic and receiver operating characteristic curve analysis. A Cox proportional-hazard model was used to identify prognostic factors for progression-free survival (PFS).</p><p><strong>Results: </strong>We observed an 81.8% (36/44) concordance between the PTC killing rate (>0% vs 0%) and the best overall clinical response (disease controlled vs disease progression per RECIST v1.1) (Kappa = 0.484, area under the curve (AUC) = 0.740). The concordance with the local response of the biopsied lesions was even higher, at 87.5% (35/40) (Kappa = 0.593, AUC = 0.841). A PTC killing rate >0% was correlated with significantly longer PFS (8.6 vs 2.0 months, <i>P</i> < .001) and emerged as an independent predictor of PFS in multivariate analysis (hazard ratio (HR) 3.507, 95% confidence interval (CI) 1.289-9.536). Exploratory subgroup analysis revealed concordance rates of 73.7% (14/19) for malignant effusion-derived PTCs and 88.0% (22/25) for tumor tissue-derived PTCs; 95.2% (20/21) for first-line therapy and 69.6% (16/23) for later-line therapies; and 80.0% (12/15) for targeted therapy and 85.2% (23/27) for chemotherapy. Notably, the concordance rate reached 100% (14/14) in patients receiving chemotherapy plus immune checkpoint inhibitors.</p><p><strong>Conclusions: </strong>These findings validate the predictive value of the PTC-based drug sensitivity assay in guiding personalized treatment for patients with advanced NSCLC and support its clinical translation.</p><p><strong>Registration: </strong>Chinese Clinical Trial Registry, Registration No.: ChiCTR2100048791, https://www.chictr.org.cn/showproj.html?proj=129885.</p>","PeriodicalId":48591,"journal":{"name":"Clinical Medicine Insights-Oncology","volume":"19 ","pages":"11795549251405740"},"PeriodicalIF":1.9,"publicationDate":"2025-12-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12705941/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145776076","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":"Impact of Latent Tuberculosis Infection and T-SPOT.TB Dynamics Alterations on Prognosis in Advanced NSCLC Treated With ICIs--IPTW-Based Retrospective Study.","authors":"Yijiao Xu, Jianying Liu, Qingwei Zhang, Yijun Song, Shuwen Yang, Haiyan Chen, Congyi Xie, DaWei Yang, Zhisheng Chen, Hongni Jiang","doi":"10.1177/11795549251394955","DOIUrl":"10.1177/11795549251394955","url":null,"abstract":"<p><strong>Background: </strong>To investigate the impact of latent tuberculosis infection (LTBI) on the prognosis of non-small cell lung cancer (NSCLC) patients treated with anti-PD-1 immunotherapy and to assess the correlation between dynamic alterations in T-SPOT.TB results and prognosis.</p><p><strong>Methods: </strong>This retrospective cohort study analyzed clinical data from 127 patients with NSCLC who received anti-PD-1 therapy and underwent T-SPOT.TB testing at our institution between January 2020 and March 2024. Baseline imbalances between groups were addressed using inverse probability of treatment weighting (IPTW). Restricted cubic spline (RCS) modeling, Cox regression and other analyses were conducted both before and after IPTW.</p><p><strong>Results: </strong>Among the entire cohort, 50 patients were in the LTBI group and 77 in the Normal group. No significant differences were observed in mPFS or mOS between the two groups. RCS analysis revealed a nonlinear (U-shaped) relationship between pre-TSPOT values and OS. Patients with a T-SPOT positive (but value ⩽18) exhibited longer OS compared with the other two groups (HR = 0.13, 95% CI [0.03 ~ 0.54], <i>P</i> = .005; after IPTW HR = 0.21, 95% CI [0.05-0.90], <i>P</i> = .035). Among 63 patients monitored for dynamic TSPOT changes, 35 (55.56%) remained persistently negative, 15 (23.81%) remained persistently positive, 2 (3.17%) converted from negative to positive, and 11 (17.46%) converted from positive to negative. No significant differences in ORR, PFS, or OS across these groups.</p><p><strong>Conclusions: </strong>Although no statistically significant differences in treatment efficacy and prognosis were observed between the LTBI and Normal groups, this finding should not be interpreted as therapeutic equivalence, particularly given the limited sample size. Pre-treatment T-SPOT values showed a nonlinear (U-shaped) relationship with patient prognosis (OS). Lower pre-treatment T-SPOT value were associated with longer OS. The dynamic changes in T-SPOT during treatment were not significantly associated with outcomes. Four patients developed active tuberculosis during immunotherapy, with heterogeneous T-SPOT patterns, underscoring the need for TB monitoring in ICI-treated patients.</p>","PeriodicalId":48591,"journal":{"name":"Clinical Medicine Insights-Oncology","volume":"19 ","pages":"11795549251394955"},"PeriodicalIF":1.9,"publicationDate":"2025-11-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12663048/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145649893","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":"Machine Learning-Based Enhanced MRI Radiomics for PDCD1 Prognostication and Expression Prediction in Breast Cancer.","authors":"Yingying Gao, Zihan Li, Ziyun Li, Xueyan Gao","doi":"10.1177/11795549251399383","DOIUrl":"10.1177/11795549251399383","url":null,"abstract":"<p><strong>Background: </strong>Programmed cell death 1 (PDCD1) is an immune checkpoint inhibitor that plays an important role in immune evasion in breast cancer (BC). In this study, we aimed to evaluate the correlation between <i>PDCD1</i> expression, immune cell tumor infiltration, and prognosis. In addition, we also developed a predictive model to determine <i>PDCD1</i> expression levels in patients with BC based on radiomics features extracted from magnetic resonance imaging (MRI).</p><p><strong>Methods: </strong>Clinical data of 1082 patients with BC extracted from The Cancer Genome Atlas (TCGA) and MRI data of 108 patients with BC extracted from The Cancer Imaging Archive (TCIA) were used to determine the correlation between <i>PDCD1</i> expression levels and the prognosis, clinical stage, survival, and levels of immune cell tumor infiltration in patients with BC. Predictive radiomics features for PDCD1 were extracted by 2 physicians from MRI data. The top 5 predictive features were evaluated and selected to build 2 machine learning models.</p><p><strong>Results: </strong>The <i>PDCD1</i> expression levels were significantly higher in tumor tissues from patients with BC (<i>P</i> < .001). High <i>PDCD1</i> expression levels were associated with improved overall survival, hazard ratio (HR) = 0.63, 95% confidence interval (CI) 0.425-0.934, <i>P</i> = .021. The <i>PDCD1</i> expression levels showed a significant positive correlation with immune cell infiltration, including CD8 (<i>P</i> < .001) and Treg (<i>P</i> < .001). Both MRI radiomics models demonstrated good accuracy, strong clinical utility, and a high level of consistency in discriminating between low and high <i>PDCD1</i> expression levels (<i>P</i> > .05).</p><p><strong>Conclusions: </strong><i>PDCD1</i> expression showed a good correlation with prognosis and tumor immune cell infiltration. The MRI radiomics model accurately predicted <i>PDCD1</i> expression levels and could potentially serve as a noninvasive tool to predict early tumor response to immunotherapy.</p>","PeriodicalId":48591,"journal":{"name":"Clinical Medicine Insights-Oncology","volume":"19 ","pages":"11795549251399383"},"PeriodicalIF":1.9,"publicationDate":"2025-11-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12663040/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145649911","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 Population-Specific Ensemble Machine Learning Model for Predicting Borderline or Malignancy Risk of Ovarian Masses in Macao: A Multicenter Retrospective Study.","authors":"Chan-Fong Chio, Lai-Fong Sin, Hoi-Sun Loi, Hou-Kong Cheang, I-San Chan, Shunjia Hong, Wai-Ieng Fong, Kin-Iong Chan, Sio-In Wong","doi":"10.1177/11795549251388312","DOIUrl":"10.1177/11795549251388312","url":null,"abstract":"<p><strong>Background: </strong>Preoperative discrimination between benign and malignant ovarian tumors is important. The applicability of published prediction tools may be limited across different health systems. We aim to develop a machine learning model specifically for Macao's population to predict the borderline or malignancy risk of ovarian masses using routinely available clinical data in Macao's health system.</p><p><strong>Methods: </strong>The study cohorts were derived from 2 major hospitals in Macao, including 496 patients who underwent oophorectomy or cystectomy for ovarian masses at CHCSJ between January 2014 and December 2023, along with a simulated prospective cohort of 95 patients from CHCSJ between January 2024 and November 2024, and an external validation cohort of 61 patients from KWH between January 2020 and September 2024. Patients' clinical information, ultrasound features, and laboratory test results before initial treatment were collected. LASSO regression was used for feature selection, and classifiers were developed using various machine learning algorithms. The predictions were compared with postoperative pathological diagnoses. The predictive performance was also compared with the RMI-4.</p><p><strong>Results: </strong>Age, menopausal status, 5 ultrasound features, and 7 laboratory tests were identified as predictors of borderline and malignant ovarian tumors. An ensemble learning model based on a voting classifier was selected as the final model. Our model outperformed RMI-4 in the internal test set, simulated prospective cohort, and external validation cohort, achieving an area under the curve (AUC) of 0.923-0.951 (vs 0.810-0.868, <i>P</i> < .05). Decision curve analysis demonstrated superior clinical utility, and SHAP analysis confirmed its interpretability.</p><p><strong>Conclusions: </strong>We propose a machine learning model targeting Macao's population for predicting the borderline or malignancy risk of ovarian masses. Our model is accurate, low-cost, easily accessible, and interpretable. On the basis of no workflow changes, machine learning techniques can maximize the predictive potential of routinely available clinical data in a specific health system.</p>","PeriodicalId":48591,"journal":{"name":"Clinical Medicine Insights-Oncology","volume":"19 ","pages":"11795549251388312"},"PeriodicalIF":1.9,"publicationDate":"2025-11-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12965330/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147379352","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":"Unveiling HJURP as a Biomarker of Poor Prognosis and Immunotherapy Resistance in Lung Adenocarcinoma: A Multicenter Study.","authors":"Qinglin Tan, Peiliang Kong, Guobiao Chen, Chen Chen, Huiting Mo, Yuancheng Huang, Manman Zhang, Yanmin Cai, Hanbin Zhang, Jianming Lu, Yifen Wu","doi":"10.1177/11795549251388872","DOIUrl":"10.1177/11795549251388872","url":null,"abstract":"<p><strong>Background: </strong>Lung adenocarcinoma (LUAD) is the most common lung cancer, associated with high metastasis and low survival rates. Identifying reliable biomarkers is essential for better prognosis and treatment.</p><p><strong>Methods: </strong>In this study, we analyzed RNA sequencing data, mutation information, and clinical data from the TCGA-LUAD cohort and other multicenter datasets to investigate the role of Holliday junction recognition protein (HJURP) in LUAD. We employed immunohistochemistry in tissue microarray cohort to validate the prognostic significance of HJURP. The DepMap project was used to validate the effect of HJURP knockout in vitro.</p><p><strong>Results: </strong>Holliday junction recognition protein was identified as an adverse prognostic factor in the TCGA-LUAD cohort and diverse ethnic groups. Its expression correlated with poor immunotherapy outcomes, and HJURP knockout suppressed cancer cell proliferation. High HJURP expression was linked to increased mutation frequency, particularly in TP53 and TTN. Pan-cancer analysis also indicated HJURP as a poor prognostic factor in various solid tumors.</p><p><strong>Conclusions: </strong>Holliday junction recognition protein emerges as a significant biomarker in LUAD, consistently associated with poor prognosis across multiple cohorts. Its role in various oncogenic pathways and correlation with advanced disease stages underscore the potential of HJURP as a target for therapeutic intervention and as a marker for prognosis in LUAD.</p>","PeriodicalId":48591,"journal":{"name":"Clinical Medicine Insights-Oncology","volume":"19 ","pages":"11795549251388872"},"PeriodicalIF":1.9,"publicationDate":"2025-10-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12575928/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145432805","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":"Navigating Cancer Complexity: Integrative Multi-Omics Methodologies for Clinical Insights.","authors":"Martina Catalano, Alberto D'Angelo, Francesco De Logu, Romina Nassini, Daniele Generali, Giandomenico Roviello","doi":"10.1177/11795549251384582","DOIUrl":"10.1177/11795549251384582","url":null,"abstract":"<p><p>Recent advancements in cancer multi-omics have transformed our understanding of cancer biology by integrating genomics, transcriptomics, proteomics, and metabolomics. These integrative approaches have led to the identification of novel biomarkers and therapeutic targets, offering deeper insights into the molecular intricacies of various cancers, including breast, lung, gastric, pancreatic, and glioblastoma. Despite these advances, challenges remain, such as the integration of disparate data types and the interpretation of complex biological interactions. However, developments in proteogenomics and mass spectrometry have enhanced the correlation between molecular profiles and clinical features, refining the prediction of therapeutic responses. Future research in cancer drug discovery is poised to benefit from multi-omics approaches, improving the precision and efficacy of personalized therapies. By developing integrative network-based models, researchers aim to address challenges related to heterogeneity, reproducibility, and data interpretation. A standardized framework for multi-omics data integration could revolutionize cancer research, optimizing the identification of novel drug targets and enhancing our understanding of cancer biology. This complete approach holds the promise of advancing personalized therapies by fully characterizing the molecular landscape of cancer, ultimately improving patient outcomes through more effective and targeted treatment strategies. This narrative review underscores the potential of multi-omics approaches to transform cancer research and improve patient outcomes through more precise and effective treatments.</p>","PeriodicalId":48591,"journal":{"name":"Clinical Medicine Insights-Oncology","volume":"19 ","pages":"11795549251384582"},"PeriodicalIF":1.9,"publicationDate":"2025-10-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12553891/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145379416","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":"Research Progress of LEF1 Gene in Malignant Tumors.","authors":"Youmei Zhao, Chenglong Pan, Shu Yang, Xiaoling Ma, Yanfei Yao, Ziqi Li, Qianlin Ma, Xiaoyu Wang, Chunyan Wang, Zhi Nie","doi":"10.1177/11795549251371111","DOIUrl":"10.1177/11795549251371111","url":null,"abstract":"<p><p>Currently, one of the most dynamic and rapidly advancing areas in biomedical research is the study of cell signaling systems. In particular, researchers have directed significant attention toward the Wnt signaling pathway, which has emerged as a critical player in several biological processes, including embryonic development, cancer progression, and the maintenance of tissue homeostasis. The growing body of research demonstrating the Wnt pathway's critical functions in various activities emphasizes the pathway's importance. Lymphoid enhancer factor-1 (LEF-1) is a crucial component of the Wnt signaling cascade, among its numerous components. The β-catenin/LEF complex, which is essential for triggering transcriptional responses, is formed when the N-terminal domain of LEF-1 binds with β-catenin. This complex acts as a central \"activation hub\" within the Wnt pathway, integrating signals from β-catenin and LEF-1 to facilitate gene expression that is critical for cellular functions. This narrative review focuses on highlighting the latest advancements in LEF-1 research, particularly its role in cancer. By emphasizing the significance of LEF-1 in the processes of carcinogenesis, the discussion aims to shed light on the potential implications of these findings for developing innovative treatment strategies. Understanding the function of LEF-1 not only enhances our comprehension of tumor biology but also opens pathways to novel therapeutic interventions.</p>","PeriodicalId":48591,"journal":{"name":"Clinical Medicine Insights-Oncology","volume":"19 ","pages":"11795549251371111"},"PeriodicalIF":1.9,"publicationDate":"2025-10-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12547134/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145379472","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":"Comparison of the Efficacy of First-Line Pemetrexed-Platinum and Gemcitabine-Platinum Regimens in Malignant Peritoneal Mesothelioma.","authors":"Doğan Bayram, Safa Can Efil, Serap Türk, Oğuz Kara, Serhat Sekmek, Şebnem Yücel, Selin Aktürk Esen, Gökhan Uçar, Oznur Bal, Efnan Algin, Doğan Uncu","doi":"10.1177/11795549251385075","DOIUrl":"10.1177/11795549251385075","url":null,"abstract":"<p><strong>Background: </strong>Malignant peritoneal mesothelioma (MPeM) is a rare and progressive cancer originating from the mesothelial cells of the peritoneum. In patients with early-stage disease who are suitable for surgery, the treatment of choice is CRS + HIPEC, whereas in advanced-stage patients, systemic treatments are applied. Pemetrexed plus platinum regimens are at the forefront of first-line systemic treatments. Gemcitabine plus platinum regimens are rarely used as first-line treatment for MPeM. The aim of our study is to compare the efficacy of first-line pemetrexed plus platinum with gemcitabine plus platinum regimens in patients with MPeM.</p><p><strong>Methods: </strong>In this study, a retrospective analysis was conducted on 48 patients with MPeM who were followed up in our clinic between 2001 and 2025. In our study, 28 patients received pemetrexed plus platinum as a first-line regimen, while 20 patients received gemcitabine plus platinum. The median overall survival (OS), median progression-free survival (PFS), and response rates for both regimens were analyzed. In addition, prognostic factors influencing overall survival were investigated in the entire patient population.</p><p><strong>Results: </strong>The median PFS and OS were 11.1 months and 17.0 months for pemetrexed and 8.01 months and 14.4 months for gemcitabine. Although pemetrexed showed numerically higher PFS and OS, the difference was not statistically significant. The objective response rate (ORR) and disease control rate (DCR) were 32.1% and 57.1% for pemetrexed, compared with 25% and 40% for gemcitabine, showing pemetrexed's superiority in response rates. In the entire patient population, CRS + HIPEC was the main prognostic factor for survival.</p><p><strong>Conclusion: </strong>We have demonstrated that the pemetrexed + platinum regimen has better response rates compared with the gemcitabine + platinum regimen in MPeM patients. However, gemcitabine-based regimens can be used as an alternative to pemetrexed in patients with MPeM.</p>","PeriodicalId":48591,"journal":{"name":"Clinical Medicine Insights-Oncology","volume":"19 ","pages":"11795549251385075"},"PeriodicalIF":1.9,"publicationDate":"2025-10-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12541155/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145356447","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}