Pub Date : 2025-12-10DOI: 10.1038/s43018-025-01086-y
Hana Aliee, Leire Bejarano-Bosque, Roger Castells-Graells, Deborah Caswell, Mirco Julian Friedrich, Carino Gurjao, Li Ren Kong, Shuang Liu, Simone Minnie, Reineke A. Schoot, Zefang Tang
Twelve early-career researchers who started their independent research groups in 2025 reflect on their experiences from this first year of the journey, describe the opportunities they have had and the challenges they have faced, and share their hopes and plans for the future.
{"title":"The 2025 generation","authors":"Hana Aliee, Leire Bejarano-Bosque, Roger Castells-Graells, Deborah Caswell, Mirco Julian Friedrich, Carino Gurjao, Li Ren Kong, Shuang Liu, Simone Minnie, Reineke A. Schoot, Zefang Tang","doi":"10.1038/s43018-025-01086-y","DOIUrl":"10.1038/s43018-025-01086-y","url":null,"abstract":"Twelve early-career researchers who started their independent research groups in 2025 reflect on their experiences from this first year of the journey, describe the opportunities they have had and the challenges they have faced, and share their hopes and plans for the future.","PeriodicalId":18885,"journal":{"name":"Nature cancer","volume":"6 12","pages":"1930-1934"},"PeriodicalIF":28.5,"publicationDate":"2025-12-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145724821","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}
Pub Date : 2025-12-10DOI: 10.1038/s43018-025-01080-4
Melanie Senior
Bispecific antibodies and ADCs battle for the limelight, CAR-T therapy sees late surge and China’s growth continues.
双特异性抗体和adc争夺风头，CAR-T疗法姗姗来迟，中国的增长仍在继续。
{"title":"Cancer drug approvals and setbacks in 2025","authors":"Melanie Senior","doi":"10.1038/s43018-025-01080-4","DOIUrl":"10.1038/s43018-025-01080-4","url":null,"abstract":"Bispecific antibodies and ADCs battle for the limelight, CAR-T therapy sees late surge and China’s growth continues.","PeriodicalId":18885,"journal":{"name":"Nature cancer","volume":"6 12","pages":"1902-1904"},"PeriodicalIF":28.5,"publicationDate":"2025-12-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145724841","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}
Pub Date : 2025-12-10DOI: 10.1038/s43018-025-01076-0
W. Kimryn Rathmell, Lalita A. Shevde
Fostering a nimble, innovative and resilient biomedical workforce is crucial. Here, we consider how to accelerate the readiness of early career investigators to lead, inverting the traditional pyramid view of academia to place them at the top, with expansive possibilities for advancement.
{"title":"Flipping the narrative on launching a rewarding career in academic medicine","authors":"W. Kimryn Rathmell, Lalita A. Shevde","doi":"10.1038/s43018-025-01076-0","DOIUrl":"10.1038/s43018-025-01076-0","url":null,"abstract":"Fostering a nimble, innovative and resilient biomedical workforce is crucial. Here, we consider how to accelerate the readiness of early career investigators to lead, inverting the traditional pyramid view of academia to place them at the top, with expansive possibilities for advancement.","PeriodicalId":18885,"journal":{"name":"Nature cancer","volume":"6 12","pages":"1918-1921"},"PeriodicalIF":28.5,"publicationDate":"2025-12-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145724814","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}
Pub Date : 2025-12-10DOI: 10.1038/s43018-025-01083-1
Wenners Ballard, Muskan Agarwal, Stephen V. Liu
Targeted therapies continue to transform the landscape of non-small-cell lung cancer (NSCLC). In 2025, the US Food and Drug Administration approved two targeted therapies, an antibody–drug conjugate and a tyrosine kinase inhibitor, for specific molecular subtypes of NSCLC. In this Clinical Outlook, we discuss their impact on the field.
{"title":"Expanding targeted therapy for lung cancer","authors":"Wenners Ballard, Muskan Agarwal, Stephen V. Liu","doi":"10.1038/s43018-025-01083-1","DOIUrl":"10.1038/s43018-025-01083-1","url":null,"abstract":"Targeted therapies continue to transform the landscape of non-small-cell lung cancer (NSCLC). In 2025, the US Food and Drug Administration approved two targeted therapies, an antibody–drug conjugate and a tyrosine kinase inhibitor, for specific molecular subtypes of NSCLC. In this Clinical Outlook, we discuss their impact on the field.","PeriodicalId":18885,"journal":{"name":"Nature cancer","volume":"6 12","pages":"1916-1917"},"PeriodicalIF":28.5,"publicationDate":"2025-12-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145724844","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}
Pub Date : 2025-12-10DOI: 10.1038/s43018-025-01091-1
As we do every December, we revisit the highs and lows of the past year in a dedicated Focus issue of commissioned comment, news and highlights from the primary research literature.
{"title":"A look back at 2025","authors":"","doi":"10.1038/s43018-025-01091-1","DOIUrl":"10.1038/s43018-025-01091-1","url":null,"abstract":"As we do every December, we revisit the highs and lows of the past year in a dedicated Focus issue of commissioned comment, news and highlights from the primary research literature.","PeriodicalId":18885,"journal":{"name":"Nature cancer","volume":"6 12","pages":"1901-1901"},"PeriodicalIF":28.5,"publicationDate":"2025-12-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.nature.comhttps://www.nature.com/articles/s43018-025-01091-1.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145724703","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}
Pub Date : 2025-12-10DOI: 10.1038/s43018-025-01062-6
René Bernards, Anton Berns, Johanna A. Joyce, Michael Baumann
Cancer is causing a global health crisis, straining even wealthy nations with rising cases, costs and workforce limits. Europe lags in translating basic research discoveries into clinical applications. We must invest in prevention, fundamental research, clinical trials, biotech support, workforce and patient involvement to stay competitive.
{"title":"European cancer research requires renewed urgency","authors":"René Bernards, Anton Berns, Johanna A. Joyce, Michael Baumann","doi":"10.1038/s43018-025-01062-6","DOIUrl":"10.1038/s43018-025-01062-6","url":null,"abstract":"Cancer is causing a global health crisis, straining even wealthy nations with rising cases, costs and workforce limits. Europe lags in translating basic research discoveries into clinical applications. We must invest in prevention, fundamental research, clinical trials, biotech support, workforce and patient involvement to stay competitive.","PeriodicalId":18885,"journal":{"name":"Nature cancer","volume":"6 12","pages":"1922-1924"},"PeriodicalIF":28.5,"publicationDate":"2025-12-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145724877","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}
Pub Date : 2025-12-10DOI: 10.1038/s43018-025-01071-5
Zhiyun Duan, Qihao Duan, Benjamin Wild, Roland Eils
Foundation models hold transformative promise for oncology, yet their clinical implementation remains limited, largely owing to their current model design as narrow specialists optimized for static tasks, whereas clinical oncology requires generalist systems capable of integrating multimodal data, capturing disease evolution over time and considering patient perspectives. Design along these requirements is essential to integrating foundation models as trusted partners in cancer care.
{"title":"Foundation models in oncology win benchmarks but miss the clinic","authors":"Zhiyun Duan, Qihao Duan, Benjamin Wild, Roland Eils","doi":"10.1038/s43018-025-01071-5","DOIUrl":"10.1038/s43018-025-01071-5","url":null,"abstract":"Foundation models hold transformative promise for oncology, yet their clinical implementation remains limited, largely owing to their current model design as narrow specialists optimized for static tasks, whereas clinical oncology requires generalist systems capable of integrating multimodal data, capturing disease evolution over time and considering patient perspectives. Design along these requirements is essential to integrating foundation models as trusted partners in cancer care.","PeriodicalId":18885,"journal":{"name":"Nature cancer","volume":"6 12","pages":"1925-1927"},"PeriodicalIF":28.5,"publicationDate":"2025-12-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145724830","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}
Pub Date : 2025-12-04DOI: 10.1038/s43018-025-01070-6
Federico Giovannoni, Craig A. Strathdee, Camilo Faust Akl, Brian M. Andersen, Zhaorong Li, Hong-Gyun Lee, María Florencia Torti, Joseph M. Rone, Pere Duart-Abadia, Martina Molgora, Linxing Kong, Michael Floyd, Jian Teng, Yulia Gyulakian, Peter Grezsik, Terry Farkaly, Agnieszka Denslow, Sonia Feau, Irene Rodriguez-Sanchez, Judith Jacques, Marco Colonna, Edward M. Kennedy, Tooba Cheema, Lorena Lerner, Christophe Quéva, Francisco J. Quintana
Glioblastoma (GBM) is an aggressive, immunotherapy-resistant brain tumor. Here, we engineered an oncolytic virus platform based on herpes simplex virus 1 for GBM viroimmunotherapy. We mutated the highly cytopathic MacIntyre strain to increase spread and oncolytic activity, limit genetic drift, prevent neuron infection and enable PET tracing. We incorporated microRNA target cassettes to attenuate replication in healthy brain cells. Moreover, we engineered the gD envelope protein to specifically target GBM using EGFR-specific or integrin-specific binders. Lastly, we incorporated five immunomodulators to remodel the tumor microenvironment (TME) by locally expressing IL-12, anti-PD1, a bispecific T cell engager, 15-hydroxyprostaglandin dehydrogenase and anti-TREM2 to target T cells and myeloid cells in the GBM TME. A single intratumoral injection increased survival in GBM preclinical models, while promoting tumor-specific T cell, natural killer cell and myeloid cell responses in the TME. In summary, we engineered a retargeted, safe and traceable oncolytic virus with strong cytotoxic and immunostimulatory activities for GBM immunotherapy. Quintana and colleagues describe the engineering of oncolytic viruses armed with multiple immunomodulators and with targeted tropism for tumor cells for glioblastoma immunotherapy.
{"title":"Retargeted oncolytic viruses engineered to remodel the tumor microenvironment for glioblastoma immunotherapy","authors":"Federico Giovannoni, Craig A. Strathdee, Camilo Faust Akl, Brian M. Andersen, Zhaorong Li, Hong-Gyun Lee, María Florencia Torti, Joseph M. Rone, Pere Duart-Abadia, Martina Molgora, Linxing Kong, Michael Floyd, Jian Teng, Yulia Gyulakian, Peter Grezsik, Terry Farkaly, Agnieszka Denslow, Sonia Feau, Irene Rodriguez-Sanchez, Judith Jacques, Marco Colonna, Edward M. Kennedy, Tooba Cheema, Lorena Lerner, Christophe Quéva, Francisco J. Quintana","doi":"10.1038/s43018-025-01070-6","DOIUrl":"10.1038/s43018-025-01070-6","url":null,"abstract":"Glioblastoma (GBM) is an aggressive, immunotherapy-resistant brain tumor. Here, we engineered an oncolytic virus platform based on herpes simplex virus 1 for GBM viroimmunotherapy. We mutated the highly cytopathic MacIntyre strain to increase spread and oncolytic activity, limit genetic drift, prevent neuron infection and enable PET tracing. We incorporated microRNA target cassettes to attenuate replication in healthy brain cells. Moreover, we engineered the gD envelope protein to specifically target GBM using EGFR-specific or integrin-specific binders. Lastly, we incorporated five immunomodulators to remodel the tumor microenvironment (TME) by locally expressing IL-12, anti-PD1, a bispecific T cell engager, 15-hydroxyprostaglandin dehydrogenase and anti-TREM2 to target T cells and myeloid cells in the GBM TME. A single intratumoral injection increased survival in GBM preclinical models, while promoting tumor-specific T cell, natural killer cell and myeloid cell responses in the TME. In summary, we engineered a retargeted, safe and traceable oncolytic virus with strong cytotoxic and immunostimulatory activities for GBM immunotherapy. Quintana and colleagues describe the engineering of oncolytic viruses armed with multiple immunomodulators and with targeted tropism for tumor cells for glioblastoma immunotherapy.","PeriodicalId":18885,"journal":{"name":"Nature cancer","volume":"6 12","pages":"1994-2010"},"PeriodicalIF":28.5,"publicationDate":"2025-12-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145678163","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}
Pub Date : 2025-11-28DOI: 10.1038/s43018-025-01095-x
Vincenzo Giacco
The ESMO Congress 2025 took place from 17 to 21 October in Berlin. Marking ESMO’s 50th anniversary, the meeting showcased breakthroughs in precision oncology, antibody–drug conjugates, and AI-driven cancer care, providing new insights and innovation in clinical oncology.
{"title":"Key insights from ESMO Congress 2025","authors":"Vincenzo Giacco","doi":"10.1038/s43018-025-01095-x","DOIUrl":"10.1038/s43018-025-01095-x","url":null,"abstract":"The ESMO Congress 2025 took place from 17 to 21 October in Berlin. Marking ESMO’s 50th anniversary, the meeting showcased breakthroughs in precision oncology, antibody–drug conjugates, and AI-driven cancer care, providing new insights and innovation in clinical oncology.","PeriodicalId":18885,"journal":{"name":"Nature cancer","volume":"6 12","pages":"1938-1939"},"PeriodicalIF":28.5,"publicationDate":"2025-11-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145636132","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}
Spatial quantification is a critical step in most computational pathology tasks, from guiding pathologists to areas of clinical interest to discovering tissue phenotypes behind novel biomarkers. To circumvent the need for manual annotations, modern computational pathology methods have favored multiple-instance learning approaches that can accurately predict whole-slide image labels, albeit at the expense of losing their spatial awareness. Here we prove mathematically that a model using instance-level aggregation could achieve superior spatial quantification without compromising on whole-slide image prediction performance. We then introduce a superpatch-based measurable multiple-instance learning method, SMMILe, and evaluate it across 6 cancer types, 3 highly diverse classification tasks and 8 datasets involving 3,850 whole-slide images. We benchmark SMMILe against nine existing methods using two different encoders—an ImageNet pretrained and a pathology-specific foundation model—and show that in all cases SMMILe matches or exceeds state-of-the-art whole-slide image classification performance while simultaneously achieving outstanding spatial quantification. Gao et al. present SMMILe, a multiple-instance learning-based tool that leverages whole-slide images for accurate spatial quantification without compromising on classification performance, and show it outperforms state-of-the-art methods.
{"title":"SMMILe enables accurate spatial quantification in digital pathology using multiple-instance learning","authors":"Zeyu Gao, Anyu Mao, Yuxing Dong, Hannah Clayton, Jialun Wu, Jiashuai Liu, ChunBao Wang, Kai He, Tieliang Gong, Chen Li, Mireia Crispin-Ortuzar","doi":"10.1038/s43018-025-01060-8","DOIUrl":"10.1038/s43018-025-01060-8","url":null,"abstract":"Spatial quantification is a critical step in most computational pathology tasks, from guiding pathologists to areas of clinical interest to discovering tissue phenotypes behind novel biomarkers. To circumvent the need for manual annotations, modern computational pathology methods have favored multiple-instance learning approaches that can accurately predict whole-slide image labels, albeit at the expense of losing their spatial awareness. Here we prove mathematically that a model using instance-level aggregation could achieve superior spatial quantification without compromising on whole-slide image prediction performance. We then introduce a superpatch-based measurable multiple-instance learning method, SMMILe, and evaluate it across 6 cancer types, 3 highly diverse classification tasks and 8 datasets involving 3,850 whole-slide images. We benchmark SMMILe against nine existing methods using two different encoders—an ImageNet pretrained and a pathology-specific foundation model—and show that in all cases SMMILe matches or exceeds state-of-the-art whole-slide image classification performance while simultaneously achieving outstanding spatial quantification. Gao et al. present SMMILe, a multiple-instance learning-based tool that leverages whole-slide images for accurate spatial quantification without compromising on classification performance, and show it outperforms state-of-the-art methods.","PeriodicalId":18885,"journal":{"name":"Nature cancer","volume":"6 12","pages":"2025-2041"},"PeriodicalIF":28.5,"publicationDate":"2025-11-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.nature.comhttps://www.nature.com/articles/s43018-025-01060-8.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145549864","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}
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