Gliomas represent one of the most common types of primary brain tumor. Due to their poor prognosis and propensity for recurrence, new therapeutic targets are urgently required. A consensus is emerging that there is a significant relationship between tumor formation and embryonic development. However, the precise mechanisms and regulatory targets remain unclear. A variety of bioinformatics techniques, including GSVA, differential expression analysis, machine learning algorithms and others, were employed to elucidate the significance of germ layer development (GLD) in glioma and identify MEST as the key gene. To validate the results, in vivo and in vitro experiments were conducted, including tumor xenografts, RT-qPCR, immunocytofluorescence, transwell assays and others, which confirmed the central role of the selected oncogenic gene. Here, we performed a comprehensive bioinformatics analysis of GLD genes, providing a novel insight into the landscape of the GLD in gliomas, and confirmed the GLD-related gene MEST as a key oncogenic therapeutic target via machine learning feature selection framework. Furthermore, we have identified the core gene MEST and have conducted extensive research to elucidate its pivotal role in glioma progression through in vivo and in vitro experiments. We leveraged the GLD patterns in glioma and found that the MEST might promote the glioma development through activating RAS signaling and Wnt signaling.
{"title":"Leveraging the germ layer development patterns to predict prognosis and identify MEST as a novel therapeutic target in glioma.","authors":"Wei Zhang, Shunjin Xia, Yanming Xiao, Hongwei Liu, Chaoqian Wang, Luohuan Dai, Yinhua Chen, Xuelei Lin, Hongyi Liu, Nian Jiang","doi":"10.1186/s12935-025-04163-5","DOIUrl":"10.1186/s12935-025-04163-5","url":null,"abstract":"<p><p>Gliomas represent one of the most common types of primary brain tumor. Due to their poor prognosis and propensity for recurrence, new therapeutic targets are urgently required. A consensus is emerging that there is a significant relationship between tumor formation and embryonic development. However, the precise mechanisms and regulatory targets remain unclear. A variety of bioinformatics techniques, including GSVA, differential expression analysis, machine learning algorithms and others, were employed to elucidate the significance of germ layer development (GLD) in glioma and identify MEST as the key gene. To validate the results, in vivo and in vitro experiments were conducted, including tumor xenografts, RT-qPCR, immunocytofluorescence, transwell assays and others, which confirmed the central role of the selected oncogenic gene. Here, we performed a comprehensive bioinformatics analysis of GLD genes, providing a novel insight into the landscape of the GLD in gliomas, and confirmed the GLD-related gene MEST as a key oncogenic therapeutic target via machine learning feature selection framework. Furthermore, we have identified the core gene MEST and have conducted extensive research to elucidate its pivotal role in glioma progression through in vivo and in vitro experiments. We leveraged the GLD patterns in glioma and found that the MEST might promote the glioma development through activating RAS signaling and Wnt signaling.</p>","PeriodicalId":9385,"journal":{"name":"Cancer Cell International","volume":" ","pages":"68"},"PeriodicalIF":6.0,"publicationDate":"2026-01-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12870398/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145917107","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Background: Oral cancer (OC) is the most common type of head and neck cancer, with a high mortality rate, and is a leading cause of cancer-related deaths worldwide. Drug-induced ferroptosis is a novel form of non-apoptotic cell death that offers a promising strategy for cancer therapy. Accumulating evidence has emphasized the significant role of methotrexate (MTX) in the treatment of many malignancies; however, its role in the ferroptosis pathway in OCs and its underlying mechanisms remain poorly understood.
Methods: After treating the OC cells with MTX, several cellular function assays were performed, including cell proliferation, apoptosis, colony formation, and wound healing assays. Distinctive features of ferroptosis were detected, and qPCR and western blot (WB) assays were performed to validate the expression of genes and proteins related to ferroptosis pathways in MTX-treated cells. In vitro experiments were conducted to further explore the mechanisms by which MTX regulates the stability of nuclear factor erythroid 2-related factor 2 (NRF2) in OC cells. Finally, in a mouse model using MOC1 cells, some experiments were performed to demonstrate MTX-induced ferroptosis and tumor suppression.
Results: In this study, based on in vitro and in vivo experiments, we found that MTX significantly reduced OC cell viability by inducing ferroptosis. Mechanistically, MTX administration increased the phosphorylation of Kelch-like ECH-associated protein 1 (KEAP1) at threonine 43 via activation of the ERK/MAPK signaling pathway, thereby maintaining the protein complex formed by KEAP1 and NRF2. As result of the decreased NRF2 expression, the levels of SLC7A11 and GPX4 proteins were markedly suppressed in MTX-treated OC cells, ultimately leading to the induction of ferroptosis in OC.
Conclusions: Our data demonstrated that MTX-mediated activation of the ERK/KEAP1 signaling pathway significantly induced ferroptosis by inhibiting the NRF2/HO-1/SLC7A11/GPX4 axis, thereby suppressing OC progression. These findings suggest that MTX is a promising candidate for OC treatment, offering a meaningful and effective therapeutic-strategy.
背景:口腔癌(OC)是头颈部最常见的癌症类型,死亡率高,是全球癌症相关死亡的主要原因。药物诱导的铁下垂是一种新的非凋亡细胞死亡形式,为癌症治疗提供了一种有前途的策略。越来越多的证据强调了甲氨蝶呤(MTX)在治疗许多恶性肿瘤中的重要作用;然而,其在OCs中铁下垂途径中的作用及其潜在机制仍然知之甚少。方法:用MTX处理OC细胞后,进行细胞功能测定,包括细胞增殖、凋亡、菌落形成和伤口愈合测定。检测到铁下垂的独特特征,并采用qPCR和western blot (WB)方法验证mtx处理细胞中铁下垂通路相关基因和蛋白的表达。体外实验进一步探讨MTX调控OC细胞核因子红细胞2相关因子2 (NRF2)稳定性的机制。最后,在使用MOC1细胞的小鼠模型中,进行了一些实验来证明mtx诱导的铁下垂和肿瘤抑制。结果:本研究通过体外和体内实验,我们发现MTX通过诱导铁下垂显著降低OC细胞活力。机制上,MTX通过激活ERK/MAPK信号通路,增加kelch样ECH-associated protein 1 (KEAP1)苏氨酸43位点的磷酸化,从而维持KEAP1和NRF2形成的蛋白复合物。由于NRF2表达降低,mtx处理的OC细胞中SLC7A11和GPX4蛋白水平被显著抑制,最终导致OC中铁下垂。结论:我们的数据表明,mtx介导的ERK/KEAP1信号通路的激活通过抑制NRF2/HO-1/SLC7A11/GPX4轴显著诱导铁凋亡,从而抑制OC的进展。这些发现表明甲氨蝶呤是一种有希望的卵巢癌治疗候选药物,提供了一种有意义和有效的治疗策略。
{"title":"Methotrexate-triggered ferroptosis suppresses oral cancer progression by phosphorylated KEAP1-mediated NRF2 degradation to inhibit SLC7A11/GPX4 signaling pathway.","authors":"Chenchen Yu, Tingting Zhang, Jialu Yuan, Yijing Su, Hongli Zhang, Liqin Xu, Xiaomin Li, Jianan Cui, Rui Xu, Yan Zhou, Hongming Huang, Xiaorong Zhou, Yongqiang Zhou, Erhao Zhang","doi":"10.1186/s12935-025-04019-y","DOIUrl":"10.1186/s12935-025-04019-y","url":null,"abstract":"<p><strong>Background: </strong>Oral cancer (OC) is the most common type of head and neck cancer, with a high mortality rate, and is a leading cause of cancer-related deaths worldwide. Drug-induced ferroptosis is a novel form of non-apoptotic cell death that offers a promising strategy for cancer therapy. Accumulating evidence has emphasized the significant role of methotrexate (MTX) in the treatment of many malignancies; however, its role in the ferroptosis pathway in OCs and its underlying mechanisms remain poorly understood.</p><p><strong>Methods: </strong>After treating the OC cells with MTX, several cellular function assays were performed, including cell proliferation, apoptosis, colony formation, and wound healing assays. Distinctive features of ferroptosis were detected, and qPCR and western blot (WB) assays were performed to validate the expression of genes and proteins related to ferroptosis pathways in MTX-treated cells. In vitro experiments were conducted to further explore the mechanisms by which MTX regulates the stability of nuclear factor erythroid 2-related factor 2 (NRF2) in OC cells. Finally, in a mouse model using MOC1 cells, some experiments were performed to demonstrate MTX-induced ferroptosis and tumor suppression.</p><p><strong>Results: </strong>In this study, based on in vitro and in vivo experiments, we found that MTX significantly reduced OC cell viability by inducing ferroptosis. Mechanistically, MTX administration increased the phosphorylation of Kelch-like ECH-associated protein 1 (KEAP1) at threonine 43 via activation of the ERK/MAPK signaling pathway, thereby maintaining the protein complex formed by KEAP1 and NRF2. As result of the decreased NRF2 expression, the levels of SLC7A11 and GPX4 proteins were markedly suppressed in MTX-treated OC cells, ultimately leading to the induction of ferroptosis in OC.</p><p><strong>Conclusions: </strong>Our data demonstrated that MTX-mediated activation of the ERK/KEAP1 signaling pathway significantly induced ferroptosis by inhibiting the NRF2/HO-1/SLC7A11/GPX4 axis, thereby suppressing OC progression. These findings suggest that MTX is a promising candidate for OC treatment, offering a meaningful and effective therapeutic-strategy.</p>","PeriodicalId":9385,"journal":{"name":"Cancer Cell International","volume":" ","pages":"64"},"PeriodicalIF":6.0,"publicationDate":"2026-01-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12870982/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145910579","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-01-05DOI: 10.1186/s12935-025-04098-x
Jinman Fang, Qizhi Zhu, Bo Hong, Xueling Li, Hongzhi Wang
{"title":"Correction: An integrative analysis of transcriptome, methylome and single-cell RNA sequencing data identifies UBE2H as a marker of oxaliplatin resistance in colorectal cancer.","authors":"Jinman Fang, Qizhi Zhu, Bo Hong, Xueling Li, Hongzhi Wang","doi":"10.1186/s12935-025-04098-x","DOIUrl":"10.1186/s12935-025-04098-x","url":null,"abstract":"","PeriodicalId":9385,"journal":{"name":"Cancer Cell International","volume":"26 1","pages":"1"},"PeriodicalIF":6.0,"publicationDate":"2026-01-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12766932/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145905679","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Protein tyrosine phosphatase receptor-type O (PTPRO), a member of the PTP family, has garnered attention for its diagnostic and prognostic potential through the methylation of circulating tumor DNA (ctDNA). However, the utility of ctDNA has shown limited sensitivity and specificity, particularly in early-stage lung adenocarcinoma (LUAD). Given the enhanced stability of tumor-derived DNA in small extracellular vesicles (sEVs) from cancer cells, this research investigates the feasibility of using PTPRO methylation in saliva-derived sEVs as a non-invasive and easily accessible biomarker for the early detection of LUAD. To explore the relationship between PTPRO methylation and prognosis in early-stage LUAD, we conducted Kaplan-Meier survival analyses and assessed the methylation status of the PTPRO promoter using methylation-specific PCR (MSP) and q-MSP. Saliva samples were collected from 60 early-stage LUAD patients, 30 pneumonia patients, and 21 healthy controls, with isolation and characterization of salivary sEVs through transmission electron microscopy (TEM), nanoparticle tracking analysis (NTA), and immunoblotting. Kaplan-Meier analysis revealed hypermethylation of PTPRO was linked to poorer overall survival in early-stage LUAD patients. PTPRO methylation was detected in salivary sEVs of 73.3% of early-stage LUAD patients, compared to only 35% in plasma sEVs. Receiver operating characteristic (ROC) analysis confirmed that PTPRO methylation in salivary sEVs effectively distinguished early-stage LUAD patients from both pneumonia patients and healthy individuals. This suggests that PTPRO hypermethylation is associated with adverse prognosis in early-stage LUAD. The detection of PTPRO methylation in salivary sEVs demonstrates high sensitivity and specificity, indicating its potential as an epigenetic biomarker for the non-invasive diagnosis of early-stage LUAD.
{"title":"Circulating extracellular vesicle PTPRO methylation: an exploratory biomarker for minimally invasive diagnosis of early-stage lung adenocarcinoma.","authors":"Hongmei Dong, Shuanglong Chen, Weiheng Cui, Pingshan Yang, Fan Liu, Songwang Cai, Hongzheng Ren, Shuyao Zhang, Shegan Gao, Hao Zhang","doi":"10.1186/s12935-025-04127-9","DOIUrl":"10.1186/s12935-025-04127-9","url":null,"abstract":"<p><p>Protein tyrosine phosphatase receptor-type O (PTPRO), a member of the PTP family, has garnered attention for its diagnostic and prognostic potential through the methylation of circulating tumor DNA (ctDNA). However, the utility of ctDNA has shown limited sensitivity and specificity, particularly in early-stage lung adenocarcinoma (LUAD). Given the enhanced stability of tumor-derived DNA in small extracellular vesicles (sEVs) from cancer cells, this research investigates the feasibility of using PTPRO methylation in saliva-derived sEVs as a non-invasive and easily accessible biomarker for the early detection of LUAD. To explore the relationship between PTPRO methylation and prognosis in early-stage LUAD, we conducted Kaplan-Meier survival analyses and assessed the methylation status of the PTPRO promoter using methylation-specific PCR (MSP) and q-MSP. Saliva samples were collected from 60 early-stage LUAD patients, 30 pneumonia patients, and 21 healthy controls, with isolation and characterization of salivary sEVs through transmission electron microscopy (TEM), nanoparticle tracking analysis (NTA), and immunoblotting. Kaplan-Meier analysis revealed hypermethylation of PTPRO was linked to poorer overall survival in early-stage LUAD patients. PTPRO methylation was detected in salivary sEVs of 73.3% of early-stage LUAD patients, compared to only 35% in plasma sEVs. Receiver operating characteristic (ROC) analysis confirmed that PTPRO methylation in salivary sEVs effectively distinguished early-stage LUAD patients from both pneumonia patients and healthy individuals. This suggests that PTPRO hypermethylation is associated with adverse prognosis in early-stage LUAD. The detection of PTPRO methylation in salivary sEVs demonstrates high sensitivity and specificity, indicating its potential as an epigenetic biomarker for the non-invasive diagnosis of early-stage LUAD.</p>","PeriodicalId":9385,"journal":{"name":"Cancer Cell International","volume":" ","pages":"62"},"PeriodicalIF":6.0,"publicationDate":"2026-01-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12870393/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145905610","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
<p><strong>Background: </strong>As immune checkpoint inhibitors (ICI)-based combination therapies are increasingly explored for treating NK/T-cell lymphoma (NKTCL), there is a critical clinical need to identify patients who will benefit from ICI without relying on costly genomic testing.</p><p><strong>Methods: </strong>A machine learning model was developed using routine blood tests and clinical characteristics from 364 ICI-treated NKTCL patients. The case records of 1259 NKTCL patients discharged from Sun Yat-Sen University Cancer Center, Guangzhou, between January 2018 and December 2023 were retrospectively analyzed. After screening, 364 ICI-treated patients were included in the study. These patients were randomly assigned to training (n = 254) and validation (n = 110) cohorts in a 2:1 ratio. Lasso regression and five machine learning algorithms, including random forest (RF), were applied for feature selection and clinical benefit prediction. The RF model demonstrated optimal predictive performance using five key features. To predict overall survival, we combined the RF model with two critical clinical factors-Ann Arbor stage and Eastern Cooperative Oncology Group (ECOG) performance status-to develop the stage-ECOG-RF (SER) model. This model generates a risk score to quantify the probability of poor survival following ICI treatment. In total, the SER model including seven features is significantly associated with clinical outcomes and long-term survival.</p><p><strong>Results: </strong>Five feature variables-lymphocyte count, platelet count, bone marrow involvement, cholesterol (CHO), and EBV-DNA copy number-were selected from 23 laboratory tests and clinical characteristics with complete data (0% missing rate). In the training cohort, the RF algorithm showed an area under the receiver operating characteristic curve (AUC) of 0.878, outperforming extreme gradient boosting (XGBoost), support vector machine (SVM), decision trees (DT), logistic regression and SVM algorithms. The RF model demonstrated sensitivity of 83.3% and specificity of 78.9%. In the validation cohort, the AUC of the RF model was 0.752, with sensitivity of 68.8% and specificity of 69.1%. The SER model, which integrates the RF model with Ann Arbor stage and ECOG, attained time-dependent area under the receiver operating characteristic curve (AUC(t)) values of 0.736 and 0.650 for predicting 3- and 5-year overall survival. This surpasses the prognostic index of natural killer lymphoma (PINK-E) and the net reclassification index (NRI) models, which showed AUC(t) values of 0.722 and 0.532, and 0.707 and 0.541 at 3 and 5 years, respectively.</p><p><strong>Conclusions: </strong>Based on routine blood tests and clinical data, the SER model for ICI therapy of NKTCL-optimized with the RF algorithm and incorporating Ann Arbor stage and ECOG-demonstrates superior predictive performance compared to PINK-E and NRI. It provides a valuable reference for early prediction of ICI therapy failure a
背景:随着基于免疫检查点抑制剂(ICI)的联合疗法越来越多地用于治疗NK/ t细胞淋巴瘤(NKTCL),临床迫切需要在不依赖昂贵的基因组检测的情况下确定将从ICI中受益的患者。方法:利用364例ci治疗的NKTCL患者的血常规检查和临床特征建立机器学习模型。回顾性分析2018年1月至2023年12月广州中山大学肿瘤中心1259例NKTCL患者的病例记录。筛选后,364例ci治疗患者纳入研究。这些患者按2:1的比例随机分配到训练组(n = 254)和验证组(n = 110)。应用Lasso回归和随机森林(RF)等5种机器学习算法进行特征选择和临床获益预测。RF模型使用五个关键特征展示了最佳的预测性能。为了预测总生存期,我们将RF模型与两个关键临床因素- ann Arbor分期和Eastern Cooperative Oncology Group (ECOG)的表现状态相结合,建立了分期-ECOG-RF (SER)模型。该模型产生一个风险评分来量化ICI治疗后生存不良的概率。总的来说,包括7个特征的SER模型与临床结果和长期生存显著相关。结果:从23项实验室检查和临床特征中筛选出5个特征变量:淋巴细胞计数、血小板计数、骨髓受累、胆固醇(CHO)和EBV-DNA拷贝数,数据完整(缺失率0%)。在训练队列中,RF算法的接收者工作特征曲线下面积(AUC)为0.878,优于极端梯度增强(XGBoost)、支持向量机(SVM)、决策树(DT)、逻辑回归和支持向量机(SVM)算法。RF模型的敏感性为83.3%,特异性为78.9%。在验证队列中,RF模型的AUC为0.752,灵敏度为68.8%,特异性为69.1%。SER模型将RF模型与Ann Arbor分期和ECOG相结合,在预测3年和5年总生存时,受试者工作特征曲线下的时间依赖面积(AUC(t))分别为0.736和0.650。这超过了自然杀伤性淋巴瘤的预后指数(PINK-E)和净重分类指数(NRI)模型,后者在3年和5年的AUC(t)分别为0.722和0.532,0.707和0.541。结论:基于血常规检查和临床资料,采用RF算法优化并纳入Ann Arbor分期和ecog的nktcl ICI治疗SER模型的预测性能优于PINK-E和NRI。为ICI治疗失败的早期预测及远期生存提供了有价值的参考。
{"title":"The prognostic predictive SER model for NK/T-cell lymphoma in the era of modern immunotherapy.","authors":"Runkun Han, Denghan Zhang, Shenrui Bai, Yifei Ma, Bushu Xu, Hao Chen, Ao Zhang","doi":"10.1186/s12935-025-04108-y","DOIUrl":"10.1186/s12935-025-04108-y","url":null,"abstract":"<p><strong>Background: </strong>As immune checkpoint inhibitors (ICI)-based combination therapies are increasingly explored for treating NK/T-cell lymphoma (NKTCL), there is a critical clinical need to identify patients who will benefit from ICI without relying on costly genomic testing.</p><p><strong>Methods: </strong>A machine learning model was developed using routine blood tests and clinical characteristics from 364 ICI-treated NKTCL patients. The case records of 1259 NKTCL patients discharged from Sun Yat-Sen University Cancer Center, Guangzhou, between January 2018 and December 2023 were retrospectively analyzed. After screening, 364 ICI-treated patients were included in the study. These patients were randomly assigned to training (n = 254) and validation (n = 110) cohorts in a 2:1 ratio. Lasso regression and five machine learning algorithms, including random forest (RF), were applied for feature selection and clinical benefit prediction. The RF model demonstrated optimal predictive performance using five key features. To predict overall survival, we combined the RF model with two critical clinical factors-Ann Arbor stage and Eastern Cooperative Oncology Group (ECOG) performance status-to develop the stage-ECOG-RF (SER) model. This model generates a risk score to quantify the probability of poor survival following ICI treatment. In total, the SER model including seven features is significantly associated with clinical outcomes and long-term survival.</p><p><strong>Results: </strong>Five feature variables-lymphocyte count, platelet count, bone marrow involvement, cholesterol (CHO), and EBV-DNA copy number-were selected from 23 laboratory tests and clinical characteristics with complete data (0% missing rate). In the training cohort, the RF algorithm showed an area under the receiver operating characteristic curve (AUC) of 0.878, outperforming extreme gradient boosting (XGBoost), support vector machine (SVM), decision trees (DT), logistic regression and SVM algorithms. The RF model demonstrated sensitivity of 83.3% and specificity of 78.9%. In the validation cohort, the AUC of the RF model was 0.752, with sensitivity of 68.8% and specificity of 69.1%. The SER model, which integrates the RF model with Ann Arbor stage and ECOG, attained time-dependent area under the receiver operating characteristic curve (AUC(t)) values of 0.736 and 0.650 for predicting 3- and 5-year overall survival. This surpasses the prognostic index of natural killer lymphoma (PINK-E) and the net reclassification index (NRI) models, which showed AUC(t) values of 0.722 and 0.532, and 0.707 and 0.541 at 3 and 5 years, respectively.</p><p><strong>Conclusions: </strong>Based on routine blood tests and clinical data, the SER model for ICI therapy of NKTCL-optimized with the RF algorithm and incorporating Ann Arbor stage and ECOG-demonstrates superior predictive performance compared to PINK-E and NRI. It provides a valuable reference for early prediction of ICI therapy failure a","PeriodicalId":9385,"journal":{"name":"Cancer Cell International","volume":" ","pages":"58"},"PeriodicalIF":6.0,"publicationDate":"2026-01-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12866186/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145899397","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-01-04DOI: 10.1186/s12935-025-04131-z
Shoudu Yuan, Qi Ye, Ran Qin, Sogand Rajabi
Leukemia survivorship presents ongoing clinical and functional challenges, including persistent fatigue, metabolic disturbances, and reduced quality of life. Integrative, non-pharmacologic strategies that combine exercise and targeted nutrition may help address these late effects. This narrative review synthesizes current evidence on the physiological, molecular, and clinical impact of exercise training and nutritional interventions among leukemia survivors. Exercise programs, ranging from aerobic and resistance training to high-intensity interval and mobile health-based formats, consistently improve cardiorespiratory fitness, muscular strength, and fatigue outcomes, while modulating inflammatory cytokines such as interleukin-6 and tumor necrosis factor-α. Nutritional components including polyphenol-rich functional foods, omega-3 fatty acids, and microbiota-supportive diets contribute anti-inflammatory and antioxidant effects that may complement exercise in restoring immune and metabolic balance. Together, these approaches form a promising foundation for personalized supportive care in leukemia survivorship. Yet, most studies remain limited by small sample sizes, heterogeneous protocols, and short follow-ups. Future research should prioritize larger, leukemia-specific clinical trials integrating exercise and nutrition components, with standardized outcome measures to enable evidence-based recommendations for survivorship care.
{"title":"Integrative exercise and nutrition strategies in leukemia survivorship: implications for cognitive function and quality of life.","authors":"Shoudu Yuan, Qi Ye, Ran Qin, Sogand Rajabi","doi":"10.1186/s12935-025-04131-z","DOIUrl":"10.1186/s12935-025-04131-z","url":null,"abstract":"<p><p>Leukemia survivorship presents ongoing clinical and functional challenges, including persistent fatigue, metabolic disturbances, and reduced quality of life. Integrative, non-pharmacologic strategies that combine exercise and targeted nutrition may help address these late effects. This narrative review synthesizes current evidence on the physiological, molecular, and clinical impact of exercise training and nutritional interventions among leukemia survivors. Exercise programs, ranging from aerobic and resistance training to high-intensity interval and mobile health-based formats, consistently improve cardiorespiratory fitness, muscular strength, and fatigue outcomes, while modulating inflammatory cytokines such as interleukin-6 and tumor necrosis factor-α. Nutritional components including polyphenol-rich functional foods, omega-3 fatty acids, and microbiota-supportive diets contribute anti-inflammatory and antioxidant effects that may complement exercise in restoring immune and metabolic balance. Together, these approaches form a promising foundation for personalized supportive care in leukemia survivorship. Yet, most studies remain limited by small sample sizes, heterogeneous protocols, and short follow-ups. Future research should prioritize larger, leukemia-specific clinical trials integrating exercise and nutrition components, with standardized outcome measures to enable evidence-based recommendations for survivorship care.</p>","PeriodicalId":9385,"journal":{"name":"Cancer Cell International","volume":" ","pages":"60"},"PeriodicalIF":6.0,"publicationDate":"2026-01-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12870353/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145899422","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}