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Obstacles and improvement strategies for CAR-T cell therapy in solid tumors. CAR-T细胞治疗实体瘤的障碍和改进策略。
IF 2.9 4区 医学 Q3 ENDOCRINOLOGY & METABOLISM Pub Date : 2026-02-10 DOI: 10.1007/s12672-026-04473-8
Zhihao Luo, Qian Hu, Meng Ren, Li Wang, Qingshuang Zou, Xiaosha Wen, Shang Chen, Quan Liu, Dixian Luo, Zifen Guo
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引用次数: 0
Immune-related LncRNA signatures define tumor microenvironment subtypes and predict immunotherapy response in NSCLC. 免疫相关LncRNA特征定义肿瘤微环境亚型并预测非小细胞肺癌的免疫治疗反应。
IF 2.9 4区 医学 Q3 ENDOCRINOLOGY & METABOLISM Pub Date : 2026-02-10 DOI: 10.1007/s12672-026-04429-y
Ang Li, Yutao Pang, Xiao Yang, Hongfei Zhang, Dong Wu, Liyao Lin, Zhan He, Zhu Liang, Jie Chen, Fasheng Li
{"title":"Immune-related LncRNA signatures define tumor microenvironment subtypes and predict immunotherapy response in NSCLC.","authors":"Ang Li, Yutao Pang, Xiao Yang, Hongfei Zhang, Dong Wu, Liyao Lin, Zhan He, Zhu Liang, Jie Chen, Fasheng Li","doi":"10.1007/s12672-026-04429-y","DOIUrl":"https://doi.org/10.1007/s12672-026-04429-y","url":null,"abstract":"","PeriodicalId":11148,"journal":{"name":"Discover. Oncology","volume":"17 1","pages":"272"},"PeriodicalIF":2.9,"publicationDate":"2026-02-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146156320","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Research progress and trends on PET/CT imaging of pancreatic cancer: a bibliometric analysis. 胰腺癌PET/CT影像学研究进展及趋势:文献计量学分析。
IF 2.9 4区 医学 Q3 ENDOCRINOLOGY & METABOLISM Pub Date : 2026-02-10 DOI: 10.1007/s12672-026-04605-0
Xiaojiao Wang, Lizhi Zhu, Yingying Zhang, Bin Cui, Chunli Ding, Siyu Liang, Changjing Zuo, Juanli Mao
{"title":"Research progress and trends on PET/CT imaging of pancreatic cancer: a bibliometric analysis.","authors":"Xiaojiao Wang, Lizhi Zhu, Yingying Zhang, Bin Cui, Chunli Ding, Siyu Liang, Changjing Zuo, Juanli Mao","doi":"10.1007/s12672-026-04605-0","DOIUrl":"https://doi.org/10.1007/s12672-026-04605-0","url":null,"abstract":"","PeriodicalId":11148,"journal":{"name":"Discover. Oncology","volume":" ","pages":""},"PeriodicalIF":2.9,"publicationDate":"2026-02-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146156310","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Development and validation of a prognosis model for low-grade gliomas based on metabolic gene risk scoring and immune microenvironment interaction. 基于代谢基因风险评分和免疫微环境相互作用的低级别胶质瘤预后模型的建立和验证
IF 2.9 4区 医学 Q3 ENDOCRINOLOGY & METABOLISM Pub Date : 2026-02-10 DOI: 10.1007/s12672-026-04635-8
Haobin Liu, Yuxiao Wu, Haoyu Sun, Xiao Han, Qian Liu, Yuening Zhang, Jinling Zhang
<p><strong>Purpose: </strong>Low-grade gliomas(LGGs) show significant clinical and molecular heterogeneity, complicating progression prediction with conventional indicators. Metabolic reprogramming, a cancer hallmark, is linked to immune microenvironment remodeling, yet its role in LGG prognostic modeling remains underexplored. This study aims to develop a robust metabolism-related prognostic signature and elucidate its interaction with the immune microenvironment.</p><p><strong>Materials and methods: </strong>Multi-omics data from 1322 LGG patients were obtained from public databases, including the Cancer Genome Atlas (TCGA), the Chinese Glioma Genome Atlas (CGGA), and others. Metabolism-related genes were identified using three strategies: (1) differential expression analysis; (2) univariate Cox regression; and (3) weighted gene co-expression network analysis (WGCNA). Overlapping genes were further refined using protein-protein interaction (PPI) network analysis and four algorithms. We systematically compared 101 machine learning algorithms and selected the Cox model with likelihood-based boosting (CoxBoost) and Ridge regression (Ridge) to construct the hub metabolism-related gene risk score (HMRG-RS).</p><p><strong>Result: </strong>A total of 7 hub metabolic genes were identified (TYMS, PLA2G5, GPX7, GLRX, CYP17A1, ALOX15B, ACACB). HMRG-RS demonstrated good prognostic predictive performance across multiple external validation cohorts, with an average concordance index (C-index) of 0.723 and 1/3/5-year area under the receiver operating characteristic curve (AUC) of 0.778/0.797/0.745. Patients in the high-risk group exhibited significantly shorter survival and an immunosuppressive microenvironment characterized by M2 macrophage enrichment and increased tumor mutational burden(TMB). Notably, the prognostic value of HMRG-RS and the metabolic subtypes it characterizes were significantly dependent on Isocitrate dehydrogenase 1 (IDH1) mutation status. Drug sensitivity analysis revealed differential responsiveness to specific chemotherapeutic/targeted agents (e.g., AZD6482, fluvastatin) across risk groups. Molecular docking further predicted multiple therapeutic compounds (e.g., prunellin, mometasone, isoliquiritigenin) with high affinity for pivotal metabolic genes. Single-cell analysis confirmed high expression of hub metabolism-related genes (HMRGs) in myeloid cells (particularly metabolically active protumor M2 macrophages), implicating them in lipid metabolism reprogramming and immune evasion.</p><p><strong>Conclusion: </strong>This study constructed and validated a metabolism-driven prognostic model. The model enables prognostic stratification of LGG patients and links high-risk scores to metabolic dysregulation and an immunosuppressive microenvironment characterized by M2 macrophage enrichment, based on multi-omics data. Mechanistic exploration indicates this association is particularly pronounced in myeloid cells, predominantly within metaboli
目的:低级别胶质瘤(LGGs)表现出明显的临床和分子异质性,使常规指标的进展预测复杂化。代谢重编程是癌症的一个标志,与免疫微环境重塑有关,但其在LGG预后模型中的作用仍未得到充分探讨。本研究旨在建立一个强大的代谢相关的预后信号,并阐明其与免疫微环境的相互作用。材料和方法:从癌症基因组图谱(TCGA)、中国胶质瘤基因组图谱(CGGA)等公共数据库中获取1322例LGG患者的多组学数据。代谢相关基因的鉴定采用三种策略:(1)差异表达分析;(2)单变量Cox回归;(3)加权基因共表达网络分析(WGCNA)。利用蛋白相互作用(PPI)网络分析和四种算法进一步细化重叠基因。我们系统地比较了101种机器学习算法,并选择了基于似然增强(Cox boost)和Ridge回归(Ridge)的Cox模型来构建枢纽代谢相关基因风险评分(HMRG-RS)。结果:共鉴定出7个枢纽代谢基因(TYMS、PLA2G5、GPX7、GLRX、CYP17A1、ALOX15B、ACACB)。HMRG-RS在多个外部验证队列中表现出良好的预后预测性能,平均一致性指数(C-index)为0.723,受试者工作特征曲线下的1/3/5年面积(AUC)为0.778/0.797/0.745。高危组患者生存期明显缩短,免疫抑制微环境以M2巨噬细胞富集和肿瘤突变负担(TMB)增加为特征。值得注意的是,HMRG-RS的预后价值及其表征的代谢亚型显著依赖于异柠檬酸脱氢酶1 (IDH1)突变状态。药物敏感性分析显示,不同风险组对特定化疗/靶向药物(如AZD6482、氟伐他汀)的反应性存在差异。分子对接进一步预测了与关键代谢基因高亲和力的多种治疗性化合物(如prunellin、mometasone、isoiquirigenin)。单细胞分析证实,中枢代谢相关基因(HMRGs)在骨髓细胞(特别是代谢活跃的M2巨噬细胞)中高表达,暗示它们参与脂质代谢重编程和免疫逃避。结论:本研究构建并验证了代谢驱动的预后模型。基于多组学数据,该模型能够对LGG患者进行预后分层,并将高风险评分与代谢失调和以M2巨噬细胞富集为特征的免疫抑制微环境联系起来。机制探索表明,这种关联在骨髓细胞中尤其明显,主要是在代谢相关的M2巨噬细胞亚群中。此外,计算分析显示风险组之间的药物敏感性差异,并确定潜在的治疗化合物,为未来探索针对代谢-免疫相互作用的治疗策略提供线索。
{"title":"Development and validation of a prognosis model for low-grade gliomas based on metabolic gene risk scoring and immune microenvironment interaction.","authors":"Haobin Liu, Yuxiao Wu, Haoyu Sun, Xiao Han, Qian Liu, Yuening Zhang, Jinling Zhang","doi":"10.1007/s12672-026-04635-8","DOIUrl":"https://doi.org/10.1007/s12672-026-04635-8","url":null,"abstract":"&lt;p&gt;&lt;strong&gt;Purpose: &lt;/strong&gt;Low-grade gliomas(LGGs) show significant clinical and molecular heterogeneity, complicating progression prediction with conventional indicators. Metabolic reprogramming, a cancer hallmark, is linked to immune microenvironment remodeling, yet its role in LGG prognostic modeling remains underexplored. This study aims to develop a robust metabolism-related prognostic signature and elucidate its interaction with the immune microenvironment.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Materials and methods: &lt;/strong&gt;Multi-omics data from 1322 LGG patients were obtained from public databases, including the Cancer Genome Atlas (TCGA), the Chinese Glioma Genome Atlas (CGGA), and others. Metabolism-related genes were identified using three strategies: (1) differential expression analysis; (2) univariate Cox regression; and (3) weighted gene co-expression network analysis (WGCNA). Overlapping genes were further refined using protein-protein interaction (PPI) network analysis and four algorithms. We systematically compared 101 machine learning algorithms and selected the Cox model with likelihood-based boosting (CoxBoost) and Ridge regression (Ridge) to construct the hub metabolism-related gene risk score (HMRG-RS).&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Result: &lt;/strong&gt;A total of 7 hub metabolic genes were identified (TYMS, PLA2G5, GPX7, GLRX, CYP17A1, ALOX15B, ACACB). HMRG-RS demonstrated good prognostic predictive performance across multiple external validation cohorts, with an average concordance index (C-index) of 0.723 and 1/3/5-year area under the receiver operating characteristic curve (AUC) of 0.778/0.797/0.745. Patients in the high-risk group exhibited significantly shorter survival and an immunosuppressive microenvironment characterized by M2 macrophage enrichment and increased tumor mutational burden(TMB). Notably, the prognostic value of HMRG-RS and the metabolic subtypes it characterizes were significantly dependent on Isocitrate dehydrogenase 1 (IDH1) mutation status. Drug sensitivity analysis revealed differential responsiveness to specific chemotherapeutic/targeted agents (e.g., AZD6482, fluvastatin) across risk groups. Molecular docking further predicted multiple therapeutic compounds (e.g., prunellin, mometasone, isoliquiritigenin) with high affinity for pivotal metabolic genes. Single-cell analysis confirmed high expression of hub metabolism-related genes (HMRGs) in myeloid cells (particularly metabolically active protumor M2 macrophages), implicating them in lipid metabolism reprogramming and immune evasion.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Conclusion: &lt;/strong&gt;This study constructed and validated a metabolism-driven prognostic model. The model enables prognostic stratification of LGG patients and links high-risk scores to metabolic dysregulation and an immunosuppressive microenvironment characterized by M2 macrophage enrichment, based on multi-omics data. Mechanistic exploration indicates this association is particularly pronounced in myeloid cells, predominantly within metaboli","PeriodicalId":11148,"journal":{"name":"Discover. Oncology","volume":" ","pages":""},"PeriodicalIF":2.9,"publicationDate":"2026-02-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146149455","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
A long-term survival prediction model for non-small cell lung cancer based on blood inflammatory biomarkers. 基于血液炎症生物标志物的非小细胞肺癌长期生存预测模型
IF 2.9 4区 医学 Q3 ENDOCRINOLOGY & METABOLISM Pub Date : 2026-02-10 DOI: 10.1007/s12672-026-04582-4
Yuxia Du, Weihong Qiu, Fei He, Zhibin Zhou, Weimin Ye
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引用次数: 0
Biomarker guided combination strategies and perioperative integration for immune cold microsatellite stable colorectal cancer. 生物标志物引导的免疫冷微卫星稳定型结直肠癌联合治疗策略及围手术期整合。
IF 2.9 4区 医学 Q3 ENDOCRINOLOGY & METABOLISM Pub Date : 2026-02-10 DOI: 10.1007/s12672-026-04575-3
Nan Yao, Wenqiang Li, Ning Duan, Fuzhou Han, Guoyong Yu, Jun Qu
{"title":"Biomarker guided combination strategies and perioperative integration for immune cold microsatellite stable colorectal cancer.","authors":"Nan Yao, Wenqiang Li, Ning Duan, Fuzhou Han, Guoyong Yu, Jun Qu","doi":"10.1007/s12672-026-04575-3","DOIUrl":"https://doi.org/10.1007/s12672-026-04575-3","url":null,"abstract":"","PeriodicalId":11148,"journal":{"name":"Discover. Oncology","volume":" ","pages":""},"PeriodicalIF":2.9,"publicationDate":"2026-02-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146156151","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Comprehensive analysis of diverse cytokine patterns in the prognosis and tumor microenvironment of lung adenocarcinoma. 多种细胞因子模式在肺腺癌预后及肿瘤微环境中的综合分析。
IF 2.9 4区 医学 Q3 ENDOCRINOLOGY & METABOLISM Pub Date : 2026-02-10 DOI: 10.1007/s12672-026-04483-6
Yueliang Xu, Chenhan Zhang, Yajun Fang, Yi Li
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引用次数: 0
Hepatic stellate cell derived lipid droplets drive protumoral M2 macrophage polarization in hepatocellular carcinoma. 肝星状细胞源性脂滴驱动肝癌M2巨噬细胞极化。
IF 2.9 4区 医学 Q3 ENDOCRINOLOGY & METABOLISM Pub Date : 2026-02-09 DOI: 10.1007/s12672-026-04626-9
Yundan You, Sha Huang, Jingjie Xu, Qifei Li, Yu Wang, Zhouwei Zhan, Yong Ye, Bin Lan, Xuefeng Wang, Zengqing Guo, Qiaoting Hu

Background: During chronic liver injury, hepatic stellate cells (HSCs) lose their vitamin-A-rich lipid droplets (LDs), yet whether these organelles are merely degraded or released via vesicles and functionally relevant remains unclear. We investigated the fate of HSCs LDs and their impact on hepatic macrophage phenotype and hepatocellular carcinoma (HCC) development.

Methods: Chronic liver injury was induced in C57BL/6 mice using carbon tetrachloride (CCl4) for up to 12 weeks. HSCs activation and lipid droplet dynamics were assessed by immunofluorescence, transmission electron microscopy, and flow cytometry. Single-cell RNA sequencing data from normal and inflamed livers were analyzed to characterize cell populations and interactions. HSC-derived LDs were isolated by gradient centrifugation and their effects on macrophage polarization were evaluated in vitro and in vivo. An orthotopic HCC model was used to assess the impact of lipid droplet-educated macrophages on tumor growth. Clinical relevance was validated using The Cancer Genome Atlas-liver hepatocellular carcinoma (TCGA-LIHC) cohort data.

Results: Activated HSCs in fibrotic livers showed progressive fragmentation and release of LDs, which were subsequently internalized by hepatic macrophages. Single-cell transcriptomic analysis revealed enhanced HSC-macrophage interactions and upregulation of lipid metabolism pathways in both cell types during liver inflammation. HSC-derived LDs acted as a direct metabolic cue to induced M2 polarization of macrophages, characterized by elevated secretion of transforming growth factor-beta (TGF-β1), interleukin-10 (IL-10), and C-C Motif Chemokine Ligand 17 (CCL17). In orthotopic HCC models, co-injection of tumor cells with lipid droplet-educated macrophages significantly enhanced tumor growth compared to control macrophages. TCGA analysis showed that high CD163 expression correlated with poor overall survival in HCC patients.

Conclusion: Our findings identifies a distinct mechanism whereby activated HSCs transfer LDs to hepatic macrophages, inducing M2 polarization and creating a pro-tumorigenic microenvironment. This HSC-macrophage crosstalk represents a potential metabolic therapeutic target for preventing HCC development in patients with chronic liver disease.

背景:在慢性肝损伤过程中,肝星状细胞(hsc)失去其富含维生素a的脂滴(ld),但这些细胞器是仅仅被降解还是通过囊泡释放,其功能相关尚不清楚。我们研究了造血干细胞LDs的命运及其对肝巨噬细胞表型和肝细胞癌(HCC)发展的影响。方法:采用四氯化碳(CCl4)诱导C57BL/6小鼠慢性肝损伤12周。采用免疫荧光、透射电镜和流式细胞术观察造血干细胞的活化和脂滴动力学。分析了正常肝脏和炎症肝脏的单细胞RNA测序数据,以表征细胞群和相互作用。采用梯度离心分离hsc源性ld,体外和体内观察其对巨噬细胞极化的影响。采用原位肝癌模型评估脂滴教育巨噬细胞对肿瘤生长的影响。临床相关性通过癌症基因组图谱-肝肝细胞癌(TCGA-LIHC)队列数据验证。结果:肝纤维化肝中活化的hsc呈现渐进式分裂和释放ld,随后被肝巨噬细胞内化。单细胞转录组学分析显示,在肝脏炎症期间,两种细胞类型的hsc -巨噬细胞相互作用增强,脂质代谢途径上调。hsc衍生的ld作为诱导巨噬细胞M2极化的直接代谢线索,其特征是转化生长因子-β (TGF-β1)、白细胞介素-10 (IL-10)和C-C Motif趋化因子配体17 (CCL17)的分泌升高。在原位肝癌模型中,与对照巨噬细胞相比,肿瘤细胞与脂滴教育巨噬细胞共同注射可显著促进肿瘤生长。TCGA分析显示,HCC患者中CD163的高表达与较差的总生存率相关。结论:我们的研究发现了一种独特的机制,激活的hsc将ld转移到肝巨噬细胞,诱导M2极化并创造促肿瘤微环境。这种hsc -巨噬细胞串扰代表了慢性肝病患者预防HCC发展的潜在代谢治疗靶点。
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引用次数: 0
Identification of a 32-gene signature that determines HPV status in head and neck cancer. 确定头颈癌中决定HPV状态的32个基因特征。
IF 2.9 4区 医学 Q3 ENDOCRINOLOGY & METABOLISM Pub Date : 2026-02-09 DOI: 10.1007/s12672-026-04640-x
Daniel Shikun Zhou, Yao-Qi Lu
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引用次数: 0
Feasibility of an oral hydration regimen post high-dose methotrexate in children with acute leukemia: a pilot study. 急性白血病儿童高剂量甲氨蝶呤后口服水化方案的可行性:一项初步研究。
IF 2.9 4区 医学 Q3 ENDOCRINOLOGY & METABOLISM Pub Date : 2026-02-09 DOI: 10.1007/s12672-026-04608-x
Padma Sagarika Karri, Ruksana Sidhique Pr, Jagdish Prasad Meena, Rachna Seth, Aditya Kumar Gupta
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引用次数: 0
期刊
Discover. Oncology
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