Nature cancer最新文献

{"title":"Decoding pediatric brain tumors via CSF-derived methylomes","authors":"Camila S. Fang, Alexandra M. Miller","doi":"10.1038/s43018-026-01139-w","DOIUrl":"10.1038/s43018-026-01139-w","url":null,"abstract":"Cerebrospinal fluid (CSF)-derived cell-free DNA holds promise for CNS tumors, but its limited yield poses challenges. A study now presents M-PACT, a framework that uses sub-nanogram CSF-derived cell-free DNA methylomes for tumor classification, paving the way for minimally invasive diagnosis of pediatric brain tumors.","PeriodicalId":18885,"journal":{"name":"Nature cancer","volume":"7 4","pages":"556-558"},"PeriodicalIF":28.5,"publicationDate":"2026-03-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147581443","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Reprogramming of stroma-derived chemokine networks drives the loss of tissue organization in nodal B cell lymphoma","authors":"Felix Czernilofsky, Anna Mathioudaki, Lea Jopp-Saile, Raphael Lutz, Dominik Vonficht, Xi Wang, Christina Schniederjohann, Harald Voehringer, Tobias Roider, Marc-Andrea Baertsch, Claus Rodemer, Henry Löffler-Wirth, Michael Grau, Donnacha Fitzgerald, Johannes Mammen, Jan Kosla, Nora Liebers, Peter-Martin Bruch, Diana Ordoñez-Rueda, Alexander Brobeil, Gunhild Mechtersheimer, Caroline Pabst, Carsten Müller-Tidow, Andreas Trumpp, Marc Seifert, Frank Neumann, Mathias Heikenwälder, Vladimir Benes, Wolfgang Huber, Jörg Distler, Georg Lenz, Hans Binder, Reiner Siebert, Garry P. Nolan, Moritz Gerstung, Judith B. Zaugg, Daniel Hübschmann, Simon Haas, Sascha Dietrich","doi":"10.1038/s43018-026-01136-z","DOIUrl":"10.1038/s43018-026-01136-z","url":null,"abstract":"Lymph node (LN) function requires the organization of cells into higher-order spatial units. However, the principles governing LN architecture in health and disease remain poorly understood. Here, we used single-cell and spatial mapping to investigate the mechanisms directing immune cell organization in human LNs and its disruption in architecturally distinct lymphoma entities: indolent follicular lymphoma (FL) and aggressive diffuse large B cell lymphoma (DLBCL). Our data substantiate the central role of LN-resident stromal cells in chemokine-driven lymphocyte zonation and reveal an inflammatory feedback loop fueled by tumor-reactive T cells that triggers stromal remodeling, progressive loss of homeostatic chemokine gradients, and tissue disorganization from a non-malignant state to FL and DLBCL. Loss of homeostatic chemokines was associated with adverse patient survival, identifying the underlying architectural rearrangement as a key event during lymphomagenesis. Collectively, our results highlight the principles of LN organization and suggest how lymphoma-induced microenvironmental reprogramming drives the loss of tissue organization. Czernilofsky et al. identified factors that reprogram stromal cells into an inflammatory, dysfunctional state, leading to the structural disorganization of lymph nodes in B cell lymphoma at single-cell and spatial resolutions.","PeriodicalId":18885,"journal":{"name":"Nature cancer","volume":"7 3","pages":"538-552"},"PeriodicalIF":28.5,"publicationDate":"2026-03-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.nature.comhttps://www.nature.com/articles/s43018-026-01136-z.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147513544","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Tucatinib–trastuzumab–capecitabine for treatment of leptomeningeal metastasis in women with HER2+ breast cancer: TBCRC049 phase 2 study results","authors":"Rashmi K. Murthy, Barbara J. O’Brien, Donald A. Berry, Akshara Singareeka-Raghavendra, Maria Gule Monroe, Jason Johnson, Jason White, Jill Schwartz-Gomez, Ariel Topletz-Erickson, Mina Lobbous, Kristen Riley, Michelle Melisko, Aki Morikawa, Sherise D. Ferguson, John F. de Groot, Ian E. Krop, Vicente Valero, Mothaffar F. Rimawi, Antonio C. Wolff, Debu Tripathy, Nancy U. Lin, Erica M. Stringer-Reasor","doi":"10.1038/s43018-026-01120-7","DOIUrl":"10.1038/s43018-026-01120-7","url":null,"abstract":"Treatments for leptomeningeal metastasis (LM) are limited and prognosis is poor. In this phase 2, nonrandomized, single-arm, multicenter study, we evaluated a tucatinib–trastuzumab–capecitabine regimen in patients with newly diagnosed LM and human epidermal growth factor receptor 2-positive (HER2+) breast cancer. The primary endpoint was overall survival; secondary endpoints included central nervous system progression-free survival, LM objective response, neurological symptom improvement, pharmacokinetics and safety. The trial met its prespecified interim efficacy threshold and exceeded the historical control of 4.4 months. Among 17 enrolled women, all had magnetic resonance imaging-confirmed LM, 15 (88%) were symptomatic and 8 (47%) had abnormal cerebrospinal fluid cytology. For a median follow-up of 18 months (range 9.0–26.7 months), 6 of 17 (41%) remained alive. Tucatinib reached therapeutic levels in the cerebrospinal fluid. The median overall survival was 10 months (95% confidence interval 4.1 months, not reached). The median time to central nervous system progression was 6.9 months (95% confidence interval 2.8, 13.8 months). Of 13 response-evaluable patients, 5 (38%) achieved composite LM objective response. Of 12 evaluable patients, 7 (58%) had improved neurological deficits. This prospective study suggests clinical benefit with a systemic regimen for HER2+ LM including objective responses, improved symptoms and extended survival. These data support systemic therapy as an approach in HER2+ breast cancer LM. ClinicalTrials.gov registration: NCT03501979 . Murthy and colleagues discussed recent research on the effect of a tucanitib–trastuzumab–capecitabine regimen in patients with HER2+ breast cancer and leptomeningeal metastasis.","PeriodicalId":18885,"journal":{"name":"Nature cancer","volume":"7 3","pages":"424-434"},"PeriodicalIF":28.5,"publicationDate":"2026-03-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.nature.comhttps://www.nature.com/articles/s43018-026-01120-7.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147481115","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"The genomic model P-CARE enables precision prostate cancer screening in a national healthcare system","authors":"","doi":"10.1038/s43018-025-01111-0","DOIUrl":"10.1038/s43018-025-01111-0","url":null,"abstract":"We developed and clinically implemented the genomic prostate cancer risk prediction model P-CARE that identifies men at a high or low risk of prostate cancer. P-CARE enabled the design and initiation of a precision screening trial across the national healthcare system in which it was developed.","PeriodicalId":18885,"journal":{"name":"Nature cancer","volume":"7 3","pages":"412-413"},"PeriodicalIF":28.5,"publicationDate":"2026-03-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147458671","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A functional map of m6A sites in cancer","authors":"Yalong Wang, Han Xu","doi":"10.1038/s43018-026-01137-y","DOIUrl":"10.1038/s43018-026-01137-y","url":null,"abstract":"RNA N6-methyladenosine (m6A) is the most abundant internal RNA modification, yet its functional landscape in cancer remains poorly defined. A study now introduces a METTL3-based RNA base-editing screen that maps functional m6A sites and reveals m6A-dependent translational activation of the tumor suppressor CHD9 in prostate cancer and beyond.","PeriodicalId":18885,"journal":{"name":"Nature cancer","volume":"7 3","pages":"399-401"},"PeriodicalIF":28.5,"publicationDate":"2026-03-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147458597","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Prospective evaluation of artificial intelligence integration into breast cancer screening in multiple workflow settings: the GEMINI study","authors":"Clarisse Florence de Vries, Gerald Lip, Roger Todd Staff, Jaroslaw Artur Dymiter, Benjamin Tse, Annie Ng, Georgia Fox, Cary Oberije, Lesley Ann Anderson","doi":"10.1038/s43018-026-01126-1","DOIUrl":"10.1038/s43018-026-01126-1","url":null,"abstract":"Artificial intelligence (AI) tools can improve breast screening performance but different screening sites have varying needs. Here the GEMINI prospective evaluation of 10,889 women, within one UK region, used both live AI integration and simulations to model 17 different ways AI could be used in breast screening. All women received routine care. One AI tool was assessed. When the AI tool recommended recall but routine double reading did not, cases underwent additional human review, detecting 11 additional cancers. The primary AI workflow could improve cancer detection by 10.4% (1 per 1,000), maintain the recall rate (0.8% reduction) and reduce workload by up to 31%. Other workflow variations significantly improved all measured metrics (superiority in cancer detection rate, recall rate, positive predictive value (PPV), sensitivity and specificity) with up to 36% workload savings. Different AI integrations in breast screening could offer various clinical and operational gains, allowing for adaptation to local healthcare needs. De Vries et al. performed prospective evaluation of AI for breast cancer screening leveraged in many different workflow settings and report several clinical and operational gains depending on the type of AI integration.","PeriodicalId":18885,"journal":{"name":"Nature cancer","volume":"7 3","pages":"484-493"},"PeriodicalIF":28.5,"publicationDate":"2026-03-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.nature.comhttps://www.nature.com/articles/s43018-026-01126-1.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147434277","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"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 using artificial intelligence as a second reader in breast screening including arbitration","authors":"Lucy M. Warren, Jenny Venton, Kenneth C. Young, Mark Halling-Brown, Christopher J. Kelly, Marc Wilson, Megumi Morigami, Lisanne Khoo, Deborah Cunningham, Richard Sidebottom, Mamatha Reddy, Hema Purushothaman, Delara Khodabakhshi, Lesley Honeyfield, Amandeep Hujan, Tsvetina Stoycheva, Andy Joiner, Reena Chopra, Aminata Sy, Dominic Ward, Lin Yang, Rory Sayres, Daniel Golden, Namrata Malhotra, Rachita Mallya, Lihong Xi, Della Ogunleye, Charlotte Purdy, Alistair Mackenzie, Susan Thomas, Shravya Shetty, Fiona J. Gilbert, Ara Darzi, Hutan Ashrafian","doi":"10.1038/s43018-026-01128-z","DOIUrl":"10.1038/s43018-026-01128-z","url":null,"abstract":"The impact of incorporating artificial intelligence (AI) into a double-read breast-screening workflow, including arbitration, is unclear. This retrospective study included 50,000 representative women from two NHS breast-screening centers. All the women had long-term follow-up, allowing us to determine whether use of AI leads to earlier cancer detection. Cases requiring arbitration (8,732 cases) were read by 22 readers in a reader study, following their normal arbitration workflow. Overall, after arbitration, replacing the second reader with AI was noninferior (5% margin) to two human readers in terms of sensitivity and specificity (P < 0.001) while offering a workload benefit. Arbitration improved the specificity of the AI arm by overruling cases incorrectly recalled by the AI tool; however, it also overruled the AI tool recall decision for some interval and next-round cancers. Further development of the AI tool alongside improvement in its explainability could lead to the earlier detection of cancers. Warren et al. used data from a retrospective cohort of 50,000 women attending breast screening. Arbitration between human and AI decisions was performed in a reader study following normal arbitration workflow. After arbitration, replacing the second human reader with AI in a double-read breast screening workflow was noninferior to two human readers.","PeriodicalId":18885,"journal":{"name":"Nature cancer","volume":"7 3","pages":"507-521"},"PeriodicalIF":28.5,"publicationDate":"2026-03-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.nature.comhttps://www.nature.com/articles/s43018-026-01128-z.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147434325","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"AI for breast cancer screening","authors":"Allan Hackshaw, Rosalind Given-Wilson","doi":"10.1038/s43018-025-01109-8","DOIUrl":"10.1038/s43018-025-01109-8","url":null,"abstract":"Whether support from artificial intelligence (AI) models improves breast screening is a topic of research in national cancer screening programmes and clinical oncology. Three studies now show that AI tools can assist radiologists with evaluating mammograms, substantially reducing workloads and possibly improving screening performance.","PeriodicalId":18885,"journal":{"name":"Nature cancer","volume":"7 3","pages":"402-404"},"PeriodicalIF":28.5,"publicationDate":"2026-03-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147434245","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Diagnostic accuracy, fairness and clinical implementation of AI for breast cancer screening: results of multicenter retrospective and prospective technical feasibility studies","authors":"Christopher J. Kelly, Marc Wilson, Lucy M. Warren, Richard Sidebottom, Mark Halling-Brown, Lin Yang, Megumi Morigami, Jenny Venton, Reena Chopra, Jane Chang, Jonathan Dixon, Fiona J. Gilbert, Daniel I. Golden, Elzbieta Gruzewska, Lesley Honeyfield, Amandeep Hujan, Delara Khodabakhshi, Emma Lewis, Namrata Malhotra, Rachita Mallya, Della Ogunleye, Charlotte Purdy, Rory Sayres, Marcin Sieniek, Tsvetina Stoycheva, Aminata Sy, Susan Thomas, Dominic Ward, Lihong Xi, Shawn Xu, Shravya Shetty, Ara Darzi, Kenneth Young, Hema Purushothaman, Lisanne Khoo, Mamatha Reddy, Hutan Ashrafian, Deborah Cunningham","doi":"10.1038/s43018-026-01127-0","DOIUrl":"10.1038/s43018-026-01127-0","url":null,"abstract":"Artificial intelligence (AI) promises to enhance breast cancer screening. Here we evaluated Google’s mammography AI system (version 1.2) across two phases: a retrospective study using 115,973 mammograms from five National Health Service screening services with 39-month follow-up and prospective noninterventional feasibility deployment at 12 sites (9,266 cases). The primary endpoint was AI sensitivity and specificity versus first reader using a 5% noninferiority margin. The secondary endpoints were performance versus second or consensus readers and breast-level analyses. Retrospectively, AI achieved superior sensitivity (0.541 versus 0.437 for first reader, P < 0.001) and noninferior specificity (0.943 versus 0.952, P < 0.001). Cancer detection rate increased from 7.54 to 9.33 per 1,000 women, with AI detecting 25.0% of interval cancers. Performance was particularly strong for first screens (39.3% fewer recalls, 8.8% higher detection) and invasive cancers. No systematic demographic disparities were observed. Simulated second-reader replacement reduced reading time by 32% while increasing detection by 17.7%. Prospective deployment confirmed technical feasibility but revealed a distribution shift requiring threshold recalibration. Implementation requires adaptive calibration and continuous monitoring to ensure safety and equity. Kelly et al. assessed an artificial intelligence system for breast cancer screening in retrospective datasets, followed by prospective feasibility evaluation, and report its accuracy, fairness and clinical implementation in multiple workflow settings.","PeriodicalId":18885,"journal":{"name":"Nature cancer","volume":"7 3","pages":"494-506"},"PeriodicalIF":28.5,"publicationDate":"2026-03-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.nature.comhttps://www.nature.com/articles/s43018-026-01127-0.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147434274","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"CRTAM inhibition mitigates toxicity of immune checkpoint inhibitors without antitumor efficacy trade-off","authors":"Si-Cong Ma \u0000 (, ), Zi-Xuan Rong \u0000 (, ), Zi-Peng Xu \u0000 (, ), Yan-Pei Zhang \u0000 (, ), Kui-Mao Zhuang \u0000 (, ), Hao Sun \u0000 (, ), Chuan-Hui Cao \u0000 (, ), Ze-Nan Wu \u0000 (, ), Hai-Peng Zhang \u0000 (, ), Qiang Zuo \u0000 (, ), Jia-Run Lin \u0000 (, ), Jia-Xin Cheng \u0000 (, ), Hua-Ting Qu \u0000 (, ), Duan-Duan Han \u0000 (, ), Wei Wei \u0000 (, ), Ke Liu \u0000 (, ), Xiao-Ting Cai \u0000 (, ), Ze-Qin Guo \u0000 (, ), Xue Bai \u0000 (, ), Li Liu \u0000 (, ), De-Hua Wu \u0000 (, ), Zhong-Yi Dong \u0000 (, )","doi":"10.1038/s43018-026-01135-0","DOIUrl":"10.1038/s43018-026-01135-0","url":null,"abstract":"The benefit from immune checkpoint blockade (ICB) can be mitigated by the onset of immune-related adverse events (irAEs). The identification of checkpoints specific to irAEs could mitigate toxicity without antitumor efficacy trade-off. Here we integrated transcriptome and pharmacovigilance data to decipher the efficacy–toxicity equilibrium of ICB-regulated molecules and identified cytotoxic and regulatory T cell molecule (CRTAM) as an irAE checkpoint. Crtam knockout or T cell lineage-specific Crtam ablation impaired irAE induction in preclinical models. CRTAM⁺ T cells preferentially infiltrated normal tissues over tumors through the CRTAM–cell adhesion molecule 1 interaction and promoted interleukin 23-centered type 3 immunity. CRTAM inhibition preserved the ‘hot’ tumor microenvironment required for efficacy while mitigating toxicity in tumor-bearing irAE models. Quantification of the CRTAM–type 3 immune axis in blood samples enabled monitoring of irAEs in cohorts treated with ICB. Our study identifies CRTAM as a T cell checkpoint of irAEs, providing a potential target to uncouple efficacy from toxicity during immunotherapy. Dong and colleagues report that blockade of T cell-expressed cytotoxic and regulatory T cell molecule results in selective mitigation of immune-related toxicities without affecting antitumor efficacy of immune checkpoint inhibitors.","PeriodicalId":18885,"journal":{"name":"Nature cancer","volume":"7 4","pages":"650-666"},"PeriodicalIF":28.5,"publicationDate":"2026-03-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147365533","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}