Cancer Biology & Medicine最新文献

{"title":"Drug resistance to antibody-drug conjugates: mechanisms, challenges, and perspectives.","authors":"Yajing Liu, Yuwei Liu, Tingting Wu, Xiaoming Bai, Shuman Wang, Luyun Zhang, Zhiwen Fu, Chen Shi","doi":"10.20892/j.issn.2095-3941.2025.0707","DOIUrl":"10.20892/j.issn.2095-3941.2025.0707","url":null,"abstract":"<p><p>Antibody-drug conjugates (ADCs) have emerged as a transformative class of cancer therapeutics by combining the target precision of antibodies with the potent cytotoxic effects of chemotherapeutic agents. This unique approach aims to enhance the effectiveness of cancer treatment while minimizing systemic toxicity. This review provides a comprehensive overview of ADC development, starting with explorations of the structural and mechanistic foundations, and advancing to in-depth analyses of ADCs that have achieved clinical success. Despite remarkable progress, the development of drug resistance remains a significant barrier to broader clinical application. We discuss the mechanisms underlying resistance, including alterations in target antigens, disruptions in ADC internalization, and dysfunctions of intracellular trafficking. To address these challenges, we propose several strategies, such as designing next-generation ADCs equipped with improved linkers and novel payloads, implementation of combination therapies, and simultaneous targeting of multiple pathways to circumvent resistance. In conclusion, this review highlights the critical need for innovative approaches in the evolving ADC landscape, aiming to overcome resistance mechanisms and fully harness the therapeutic promise of ADCs in cancer treatment.</p>","PeriodicalId":9611,"journal":{"name":"Cancer Biology & Medicine","volume":" ","pages":""},"PeriodicalIF":12.4,"publicationDate":"2026-04-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13326606/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147626934","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}

{"title":"Lactate drives immune resistance <i>via</i> a pharmaceutically reversible H3K18la-KIF20A-c-Myc-PD-L1 axis in hepatocellular carcinoma.","authors":"Shujia Chen, Lili Zhao, Ping Han, Jie Liu, Jiancun Hou, Xiaomei Liu, Qiang Zhao, Rongqi Wang, Fengmei Wang, Jia Li","doi":"10.20892/j.issn.2095-3941.2026.0110","DOIUrl":"https://doi.org/10.20892/j.issn.2095-3941.2026.0110","url":null,"abstract":"<p><strong>Objective: </strong>Resistance to immunotherapy, driven by the immunosuppressive tumor microenvironment, remains a major clinical challenge in hepatocellular carcinoma (HCC). Although metabolic reprogramming is a known culprit, the precise epigenetic mechanisms linking lactate accumulation to immune evasion are poorly defined.</p><p><strong>Methods: </strong>Immunohistochemistry analysis of 89 pairs of HCC and paracancerous tissues was conducted to correlate histone h3 lysine 18 lactylation (H3K18la) levels with TNM stage. A separate clinical cohort of 46 patients with HCC was enrolled to assess the association between H3K18la levels and anti-PD-1 therapy resistance. Chromatin immunoprecipitation sequencing in HCC cells, performed to screen for downstream targets, identified kinesin family member 20A (KIF20A). The regulatory relationships among H3K18la, KIF20A, c-Myc, and PD-L1 were verified with dual-luciferase reporter assays and chromatin immunoprecipitation-PCR. The immune evasion mechanism was explored through gene knockdown/overexpression in HCC cells, followed by co-culture with CD8⁺ T cells and functional analysis <i>via</i> flow cytometry. Finally, a subcutaneous mouse xenograft model was established to evaluate the synergistic efficacy of a glycolysis inhibitor combined with anti-PD-1 therapy on tumor growth and the tumor immune microenvironment.</p><p><strong>Results: </strong>Histone lactylation (forming H3K18la) was identified as a key epigenetic checkpoint linking tumor metabolism to immunotherapy failure in HCC. Elevated H3K18la is a reliable biomarker for tumor progression and resistance to anti-PD-1 therapy. Mechanistically, we discovered that lactate-driven H3K18la directly activates transcription of the oncogene KIF20A. KIF20A in turn stabilizes c-Myc protein, thereby enhancing PD-L1 expression and attenuating anti-tumor immunity. This immunosuppressive phenotype was therapeutically reversible: genetic silencing of KIF20A restored T cell function, and pharmacological inhibition of glycolysis acted synergistically with anti-PD-1 therapy in suppressing tumor growth and extending survival by dismantling the H3K18la-KIF20A axis.</p><p><strong>Conclusions: </strong>This study deciphered a novel druggable metabolic-epigenetic pathway (lactate-H3K18la-KIF20A-Myc-PD-L1) responsible for immune evasion in HCC. Targeting this axis might offer a promising strategy to reprogram the tumor microenvironment and restore immunotherapy sensitivity.</p>","PeriodicalId":9611,"journal":{"name":"Cancer Biology & Medicine","volume":" ","pages":""},"PeriodicalIF":8.4,"publicationDate":"2026-04-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147621843","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Metabolic engineering of SLC38A2 reprograms glutamine utilization and enhances CAR-macrophage antitumor function in solid tumors.","authors":"Mingzhu Liu, Qingxi Chen, Luoling Zhang, Yunxuan Zhou, Ning Wen, Jin Jin, Junchao Cai, Shicheng Su, Jiang Li, Qiyi Zhao","doi":"10.20892/j.issn.2095-3941.2025.0775","DOIUrl":"10.20892/j.issn.2095-3941.2025.0775","url":null,"abstract":"<p><strong>Objective: </strong>This study was aimed at investigating metabolic dysregulation in tumor-associated macrophages (TAMs) in breast cancer and developing a metabolically enhanced chimeric antigen receptor macrophage (CAR-M) strategy to boost antitumor potency in solid tumors.</p><p><strong>Methods: </strong>Integrated scRNA-seq and metabolomic analyses were performed to characterize metabolic alterations in macrophages within the breast cancer tumor microenvironment (TME). According to the identified metabolic vulnerabilities, SLC38A2-overexpressing anti-HER2 CAR-Ms were engineered. Glutamine uptake and phagocytic activity were assessed to evaluate functional enhancement.</p><p><strong>Results: </strong>TAMs in breast cancer exhibited substantial metabolic dysregulation, particularly impaired glutamine metabolism accompanied by decreased expression of the glutamine transporter SLC38A2. Overexpression of SLC38A2 in anti-HER2 CAR-Ms, compared with conventional anti-HER2 CAR-Ms, enhanced glutamine uptake and markedly augmented phagocytosis of HER2⁺ breast cancer cells.</p><p><strong>Conclusions: </strong>Metabolic engineering <i>via</i> SLC38A2 restored glutamine fitness and enhanced the antitumor activity of HER2-targeted CAR-Ms, thus providing a promising strategy to boost CAR-M-mediated tumor suppression in solid tumors.</p>","PeriodicalId":9611,"journal":{"name":"Cancer Biology & Medicine","volume":" ","pages":""},"PeriodicalIF":12.4,"publicationDate":"2026-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13059898/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147590348","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}

{"title":"Surgery-centered integrated strategies for personalized hepatocellular carcinoma care.","authors":"Yuhan Cui, Zuchao Du, Jiahao Xu, Lihui Gu, Jiaqi Du, Mingda Wang, Tian Yang","doi":"10.20892/j.issn.2095-3941.2026.0045","DOIUrl":"10.20892/j.issn.2095-3941.2026.0045","url":null,"abstract":"<p><p>Hepatocellular carcinoma (HCC) remains a major global health burden characterized by late-stage diagnosis and high postoperative recurrence rates. This review presents a surgery-centered precision management framework integrating 3 synergistic components: early detection, precision surgery, and recurrence prevention. Early detection strategies incorporate multiparameter risk models including the gender, age, AFP-L3, AFP, and DCP (GALAD) as well as age, sex, AFP, and PIVKA-II (ASAP) scores, alongside circulating tumor DNA methylation-based liquid biopsy, thus enabling tumor identification at stages amenable to curative resection. Precision surgery optimizes patient selection through refined staging systems including the Chinese liver cancer staging (CNLC), and functional assessments including the albumin-bilirubin (ALBI) grade, whereas conversion therapy and minimally invasive approaches extend surgical eligibility to selected patients with intermediate-stage disease. To mitigate the risk of postoperative recurrence, distinguishing between early and late recurrence patterns and monitoring minimal residual disease are critical strategies. Perioperative systemic therapies, particularly immune checkpoint inhibitor-based combinations, show promise for eradicating micrometastatic disease. This integrated framework provides a cohesive, evidence-based approach to personalized HCC management aimed at maximizing curative potential and long-term survival.</p>","PeriodicalId":9611,"journal":{"name":"Cancer Biology & Medicine","volume":" ","pages":""},"PeriodicalIF":12.4,"publicationDate":"2026-03-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13498881/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147580781","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}

{"title":"Virtual histology imaging of lymph nodes <i>via</i> dynamic full-field optical coherence tomography and deep learning to differentiate metastasis.","authors":"Shuwei Zhang, Houpu Yang, Yiyin Zhang, Xiaoxian Li, Jin Zhao, Yuanyuan Zhang, Ping Xue, Hua Kang, Hongchuan Jiang, Wenhui Ren, Shu Wang","doi":"10.20892/j.issn.2095-3941.2025.0747","DOIUrl":"10.20892/j.issn.2095-3941.2025.0747","url":null,"abstract":"<p><strong>Objective: </strong>The current pathological diagnosis of lymph node metastasis is time-consuming, labor-intensive, and dependent on sectioning of paraffin blocks. Herein, in a prospective cohort of patients with breast cancer, we validated dynamic full-field optical coherence tomography (D-FFOCT), a virtual pathology tool integrating deep learning for nodal metastasis detection, and offering rapid and label-free histologic approximations of fresh tissues.</p><p><strong>Methods: </strong>In a prospective dual-center cohort of 155 patients with breast cancer, 747 freshly bisected lymph node slides were obtained <i>via</i> D-FFOCT. Surgeons interpreted each slide with histopathology as the gold standard. A deep learning model was trained on 28,911 patches (corresponding to 590 slides) and tested on 7,736 patches (corresponding to 157 slides). The results were mapped to the slide level for potential intraoperative evaluation.</p><p><strong>Results: </strong>D-FFOCT strongly correlated with hematoxylin and eosin (H&E)-stained histological images. Surgeons achieved 97.10% specificity in nodal diagnosis with D-FFOCT. The performance of the artificial intelligence (AI) model was not inferior to that of human experts and had a sensitivity/specificity of 87.88%/91.94% and an area under the receiver operating characteristic curve of 0.899 at the slide level. The human-AI collaborative system reduced labor requirements by 75% and increased the specificity by 6.5%, to 98.39%.</p><p><strong>Conclusions: </strong>D-FFOCT has excellent potential as a tool for assessing lymph node metastatic status without tissue preparation or consumption. The integration of D-FFOCT with deep learning decreases labor demands and maintains high accuracy, thereby enabling streamlined nodal prediction independent of routine pathology procedures.</p>","PeriodicalId":9611,"journal":{"name":"Cancer Biology & Medicine","volume":" ","pages":""},"PeriodicalIF":12.4,"publicationDate":"2026-03-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13059866/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147572257","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}

{"title":"Animal models and pathogenesis of gastric cancer: from premalignant conditions-to-metastasis.","authors":"Yumeng Pan, Licong Zhao, Jingyuan Fang","doi":"10.20892/j.issn.2095-3941.2025.0576","DOIUrl":"10.20892/j.issn.2095-3941.2025.0576","url":null,"abstract":"<p><p>Gastric cancer (GC) remains one of the most prevalent malignancies of the gastrointestinal tract worldwide, ranking fifth in incidence and continuing to be a leading cause of cancer-related mortality. Elucidating the mechanisms underlying GC development and progression, as well as exploring effective preventive and therapeutic strategies, is therefore of paramount importance. Animal models are indispensable tools in this endeavor, providing platforms to investigate carcinogenic processes, recapitulate disease features, and evaluate therapeutic interventions, thereby bridging the gap between laboratory discoveries and clinical application. However, the establishment of reliable GC models remains challenging due to variations in tumor induction techniques, experimental conditions, and the profound heterogeneity and aggressive metastatic potential of GC. In this review we systematically summarize animal models used for studying gastric premalignant conditions and GC organized by disease stage. We analyze recent advances and limitations of each model, considering methodologic approaches, underlying mechanisms, and translational potential. Particular emphasis is placed on aligning model characteristics with contemporary clinical challenges. Ultimately, we highlight the pivotal role of animal models in advancing precision medicine for GC, offering novel perspectives to inform both mechanistic research and therapeutic development.</p>","PeriodicalId":9611,"journal":{"name":"Cancer Biology & Medicine","volume":" ","pages":""},"PeriodicalIF":12.4,"publicationDate":"2026-03-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13244311/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147572265","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}

{"title":"Global epidemiology of ovarian cancer: patterns, trends, and risk factors.","authors":"Ruyuan Li, Anqi Zhao, Meicen Liu, Lingeng Lu, Bin Li, Hongmei Zeng","doi":"10.20892/j.issn.2095-3941.2025.0619","DOIUrl":"10.20892/j.issn.2095-3941.2025.0619","url":null,"abstract":"<p><p>Ovarian cancer was the eighth most frequently diagnosed cancer among women in 2022. The global age-standardized incidence rate of ovarian cancer decreased from 7.22/100,000 to 6.71/100,000 from 1990 to 2021. However, incidence trends varied across countries. Declining ovarian cancer incidence rates were reported in high-income countries, such as the United States, Austria, the Netherlands, and Norway, while there were increasing incidence rates in Africa and parts of Asia, including Japan and India. The global age-standardized mortality rate of ovarian cancer decreased from 4.73/100,000 to 4.06/100,000 between 1999 and 2021 with varying trends among countries. Moreover, the age-standardized 5-year net ovarian cancer survival rate in most countries remained < 50%. Several specific factors related to ovarian cancer risk have been identified, including reproductive factors, use of oral contraceptives, anti-inflammatory diets, endometriosis, pelvic inflammatory disease, obesity, diabetes, and occupational asbestos exposure. No screening or prevention strategy has been proven effective in downstaging or reducing mortality from ovarian cancer in an average-risk population without a family cancer history or pathogenic variants. Indeed, risk-reducing salpingo-oophorectomy remains the gold standard for lowering the risk of ovarian cancer in high-risk individuals with hereditary mutations. This review provides a comprehensive overview of the epidemiology, risk factors, screening, and prevention of ovarian cancer, aiming to offer a global perspective on public health strategies for addressing the disease.</p>","PeriodicalId":9611,"journal":{"name":"Cancer Biology & Medicine","volume":" ","pages":""},"PeriodicalIF":12.4,"publicationDate":"2026-03-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13449713/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147509783","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}

{"title":"Enhancing FIT-based colorectal cancer screening through risk prediction: a comparative evaluation of 17 models in a large Chinese cohort.","authors":"Le Wang, Weimiao Wu, Bin Liu, Chen Zhu, Yumeng Ding, Yi Zhou, Weiwei Chen, Lijuan Dai, Xueni Chen, Yuefan Shen, Tingting Pan, Xiaohui Sun, Huizhang Li, Dong Hang, Yingying Mao, Partha Basu, Lingbin Du","doi":"10.20892/j.issn.2095-3941.2025.0702","DOIUrl":"10.20892/j.issn.2095-3941.2025.0702","url":null,"abstract":"","PeriodicalId":9611,"journal":{"name":"Cancer Biology & Medicine","volume":" ","pages":""},"PeriodicalIF":12.4,"publicationDate":"2026-03-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13449708/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147519953","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}

{"title":"Lung cancer mortality trends in China from 2013 to 2021 and projections to 2030.","authors":"Xin Liang, Xiang Li, Yifei Yao, Xiaoqiu Dai","doi":"10.20892/j.issn.2095-3941.2025.0625","DOIUrl":"10.20892/j.issn.2095-3941.2025.0625","url":null,"abstract":"<p><strong>Objective: </strong>This study was aimed at analyzing temporal trends in lung cancer mortality from 2013 to 2021, and projecting future trends until 2030.</p><p><strong>Methods: </strong>Mortality data were extracted from the China Causes of Death Surveillance Dataset, which covers 2.37 billion person-years. Age-standardized mortality rates (ASMRs) were calculated with Segi's world standard population. Joinpoint regression was used to analyze temporal trends, and linear regression was applied to assess changes in mean age at death. A Bayesian age-period-cohort model was used to project mortality trends through 2030. Contributions of risk factors and demographic changes (population size and age structure) to mortality trends were decomposed with the population split method.</p><p><strong>Results: </strong>From 2013 to 2021, the crude lung cancer mortality rate increased by 2.3% annually, whereas the ASMR remained stable overall but showed significant 2.9% annual declines during 2015 and 2021. The ASMRs in urban areas (-2.9% per year) and eastern regions (-1.5% per year) showed significant decreasing trends throughout the entire period. The mean age at death increased across all areas, and the largest increases were observed in rural areas. Deaths among people ≥65 years of age rose by 1.6%-5.6% during the entire period. Decomposition analysis indicated that the increased death counts were driven primarily by population aging (32%-43%) and population growth (8%-31%), whereas risk factors contributed negatively (-3% to -29%). Projections suggested that the number of lung cancer deaths will reach approximately 760,200 by 2030, with continued increases in the crude mortality rate but slight declines in the ASMR.</p><p><strong>Conclusions: </strong>The lung cancer burden in China shows marked regional disparities and challenges due to population aging. To further decrease lung cancer deaths, optimized allocation of medical resources, strengthened prevention and control of lung cancer risk factors, and integration of effective policies will be required.</p>","PeriodicalId":9611,"journal":{"name":"Cancer Biology & Medicine","volume":" ","pages":""},"PeriodicalIF":12.4,"publicationDate":"2026-03-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13449714/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147497670","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}

{"title":"From overtreatment to precision: a new clinical standard for DCIS management.","authors":"Schlomo Schneebaum","doi":"10.20892/j.issn.2095-3941.2026.0010","DOIUrl":"10.20892/j.issn.2095-3941.2026.0010","url":null,"abstract":"","PeriodicalId":9611,"journal":{"name":"Cancer Biology & Medicine","volume":" ","pages":""},"PeriodicalIF":12.4,"publicationDate":"2026-03-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13326597/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147484813","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}