Nature Medicine最新文献

{"title":"Personalized neoantigen-targeting cancer vaccines in ovarian cancer: a phase 1 trial.","authors":"MacLean C Sellars, Jessica A Frank, Bohoon Shim, Allison Vanasse, Ruolin Liu, Cleo Forman, Chloe R Tu, Kyohei K Tabata, Antonia Kowelewski, Su-Chun Cheng, Catherine Song, Kan Xiong, Pia Jain, Andjela Crnjac, Haley E Sax, Vipheaviny Chea, Wesley Lu, J Thomas Janes, Micah Rickles-Young, Amit Sud, Savni Sarolkar, Martin Hayes, Oriol Olive, Haley Greenslade, Carrie Cibulskis, Nir Hacohen, Edward F Fritsch, Shuqiang Li, Kenneth J Livak, Nabihah Tayob, Elizabeth H Stover, Carolyn Krasner, Rebecca Porter, Ursula Matulonis, Gad Getz, Giacomo Oliveira, Patrick A Ott, Jeremy M Simon, Viktor A Adalsteinsson, Derin B Keskin, Panagiotis A Konstantinopoulos, Catherine J Wu","doi":"10.1038/s41591-026-04717-8","DOIUrl":"https://doi.org/10.1038/s41591-026-04717-8","url":null,"abstract":"<p><p>Personalized neoantigen-targeting cancer vaccines in the adjuvant setting are of increasing interest across malignancies. Here we report the results of a phase 1 clinical trial testing the feasibility and safety of personalized neoantigen-targeting cancer vaccines for high-grade epithelial ovarian cancer. 'NeoVax' consisted of pools of synthetic long peptides targeting patient-specific neoantigens admixed with the immunostimulant poly-ICLC, was combined with delayed administration of anti-PD-1 antibody, and was tested in ten patients (one newly diagnosed patient (Cohort A) and nine patients at first recurrence (Cohort B)) with platinum-sensitive ovarian cancer following standard-of-care platinum doublet chemotherapy. Nine of 12 evaluable Cohort B patients were vaccinated (75%, 90% CI 47-93%) and 1 of 9 Cohort A patients (11%, 90% CI 0.6-43%). No unexpected safety signals were encountered and no patients discontinued treatment due to toxicity. Across patients, >70% selected targets remained detectable by noninvasive cell-free DNA analysis despite a median of 6.5 months from the time of diagnostic biopsy to vaccine administration, during which, patients received standard-of-care chemotherapy. Biomarker analysis was suggestive of biologic activity of the vaccine in six of ten patients and this was associated with broader tumor and vaccine-specific immune responses in blood and tumor following vaccination. Resistant tumor clones reflected diverse mechanisms affecting antigen presentation, indicative of immune-selective pressure exerted by vaccination. Overall, the interplay between the repertoire of antigens presented by the tumor and the breadth of induced immunity seemed to dictate clinical efficacy following vaccination. ClinicalTrials.gov identifier: NCT04024878 .</p>","PeriodicalId":19037,"journal":{"name":"Nature Medicine","volume":" ","pages":""},"PeriodicalIF":52.5,"publicationDate":"2026-10-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149182983","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":"Talazoparib plus enzalutamide in high-volume metastatic hormone-naive prostate cancer: a randomized phase 2 trial.","authors":"Francesca Zacchi, Elena Castro, Kathleen Imbach, Alejo Rodriguez-Vida, Sara Simonetti, Begoña Mellado, Gisela Mir Arnau, Daniel Aguilar, Daniel Castellano, Miguel Angel Climent, Manuel J Ramos, Angel Borque-Fernando, Jose Antonio Guerrero, Paula Gonzalez-Alonso, Jhudit Perez-Escuredo, Vanessa Izquierdo, Maria Isabel Saez, Heura Domenech, Sara Arce-Gallego, Bernardo Herrera-Imbroda, Jacques Planas, David Lorente, Albert Font, Anna Oliveira, Pablo Cresta Morgado, Victor Esquefa, Julian Brandariz, Nicolas Anselmino, Keyi Zhu, Patricia Troncoso, Monica Aguilera, Ana Vivancos, Paolo Nuciforo, Irene Casanova-Salas, Eduard Porta, Joan Carles, Amado J Zurita, Joaquin Mateo","doi":"10.1038/s41591-026-04671-5","DOIUrl":"https://doi.org/10.1038/s41591-026-04671-5","url":null,"abstract":"<p><p>Combining inhibition of poly(ADP-ribose) polymerase and androgen receptor (AR) pathway has demonstrated clinical activity in men with metastatic prostate cancer, although the extent of benefit in tumors lacking homologous recombination repair (HRR) gene alterations remains uncertain. We conducted a randomized phase 2 trial evaluating talazoparib plus enzalutamide versus enzalutamide alone in men with high-volume metastatic hormone-naive prostate cancer (mHNPC). Fifty-four patients starting androgen deprivation therapy received two cycles of enzalutamide lead-in before 1:2 randomization to enzalutamide (n = 17) or enzalutamide plus talazoparib (n = 37). The primary endpoint was met, with a 73% prostate-specific antigen (PSA) <0.2 ng ml^-1 response rate at 12 months in the combination arm (95% confidence interval (CI) = 56-86%), exceeding the prespecified efficacy threshold (P < 0.001); the PSA <0.2 rate in the control arm was 64.7% (95% CI = 38-86%, P = 0.54 for exploratory comparison between arms). Grade ≥3 adverse events occurred in 68% patients receiving the combination versus 35% with enzalutamide alone, predominantly anemia (41%). Two fatal therapy-emergent myeloid neoplasms occurred in the enzalutamide plus talazoparib arm in patients with underlying genomic susceptibility. Analyses of paired tumor biopsies acquired at baseline and during enzalutamide lead-in phase demonstrated marked tumor transcriptional reprogramming after AR inhibition, including suppression of proliferation-associated and HRR-related gene expression programs, but without functional impairment of homologous recombination activity. Overall, talazoparib plus enzalutamide demonstrated clinical activity in patients with high-volume mHNPC but did not establish clear additional clinical benefit over enzalutamide alone in this biomarker-unselected population, while being associated with increased toxicity. ClinicalTrials.gov identifier: NCT04332744 .</p>","PeriodicalId":19037,"journal":{"name":"Nature Medicine","volume":" ","pages":""},"PeriodicalIF":52.5,"publicationDate":"2026-10-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149182928","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":"Making AI work in healthcare","authors":"","doi":"10.1038/s41591-026-04726-7","DOIUrl":"10.1038/s41591-026-04726-7","url":null,"abstract":"Drawing on experiences across diverse settings, this issue of Nature Medicine explores the challenges of and lessons learned from the deployment of artificial intelligence models into healthcare.","PeriodicalId":19037,"journal":{"name":"Nature Medicine","volume":"32 10","pages":"3499-3499"},"PeriodicalIF":52.5,"publicationDate":"2026-10-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.nature.comhttps://www.nature.com/articles/s41591-026-04726-7.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149177777","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":"Human-artificial intelligence collaboration for comanaging epilepsy in real time.","authors":"Zack Goldblum, Haoer Shi, Zhongchuan Xu, William K S Ojemann, Carlos A Aguila, Kevin Long, Kevin Xie, Kerry C Nix, Katherine G Walsh, Ellie Chang, Sarah B Lavelle, Brandon Bach, Kathryn A Davis, Nishant Sinha, Lauren H Hammer, Erin C Conrad, Brian Litt","doi":"10.1038/s41591-026-04680-4","DOIUrl":"https://doi.org/10.1038/s41591-026-04680-4","url":null,"abstract":"<p><p>One-third of the world's 70 million people with epilepsy have seizures uncontrolled by medication, and implantable devices are a promising treatment. These devices can detect impending seizures, missed medication and impaired cognition, but, like most medical devices, they cannot share this information with patients in real time. This is a missed opportunity for devices to learn from clinical events and teach patients how their behaviors affect their health. Here we present a device platform that converses with patients to help them manage their epilepsy. The inpatient prototype links scalp and intracranial electroencephalography (EEG) to a secure, large language model-based artificial intelligence (AI) that communicates bidirectionally through a smartphone app. The AI processes biomarkers of sleep, medication, cognition and seizure probability, notifies patients of clinical events and trends, records symptoms and responses, and uses their feedback to retrain its seizure detector, reducing false alarms. We validated this platform in 13 patients who are undergoing video-EEG monitoring for epilepsy (scalp, n = 11; intracranial, n = 2). In a pseudoprospective simulation, seizure detectors improved precision from patient feedback alone, without expert intervention. We propose this system as a scalable, safeguarded platform for medical devices that can rapidly adapt to patient and provider needs across epilepsy and other medical conditions.</p>","PeriodicalId":19037,"journal":{"name":"Nature Medicine","volume":" ","pages":""},"PeriodicalIF":52.5,"publicationDate":"2026-10-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149183005","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":"Autologous and broadly neutralizing antibodies drive ART-free HIV control.","authors":"Worapong Nasomsong, Jonathan Z Li","doi":"10.1038/s41591-026-04714-x","DOIUrl":"https://doi.org/10.1038/s41591-026-04714-x","url":null,"abstract":"","PeriodicalId":19037,"journal":{"name":"Nature Medicine","volume":" ","pages":""},"PeriodicalIF":52.5,"publicationDate":"2026-10-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149182945","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":"Characterizing the onset and progression of cancer cachexia using routine clinical data.","authors":"","doi":"10.1038/s41591-026-04720-z","DOIUrl":"https://doi.org/10.1038/s41591-026-04720-z","url":null,"abstract":"","PeriodicalId":19037,"journal":{"name":"Nature Medicine","volume":" ","pages":""},"PeriodicalIF":52.5,"publicationDate":"2026-10-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149182955","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 health-system-scale, episode-resolved multimodal atlas of cancer cachexia.","authors":"Venise Jan Castillon, Amy X Xie, Sonia Boscenco, Ethan Tse, Neil Ruthen, Jamie Wang, Ziad Bakouny, Michele Waters, Chenlian Fu, Christopher Fong, Mustafa Saleh, Tarek Baroud, Wungki Park, Urvi A Shah, A Ari Hakimi, Puneeth Iyengar, Justin Jee, Eileen White, Alexander Gusev, Tobias Janowitz, Marcus D Goncalves, Ed Reznik","doi":"10.1038/s41591-026-04689-9","DOIUrl":"https://doi.org/10.1038/s41591-026-04689-9","url":null,"abstract":"<p><p>Cancer cachexia is a wasting syndrome with outsized impact on morbidity and mortality, yet its drivers and systemic consequences remain poorly defined. In this study, we repurposed longitudinal clinicogenomic data from 52,236 patients with cancer profiled by MSK-IMPACT (2010-2024) at Memorial Sloan Kettering Cancer Center to define episode-resolved trajectories of consensus-defined cachectic weight loss and linked these events to outcomes, serology and tumor genotypes. Cachectic episodes clustered near periods of disease progression and were associated with inferior outcomes in nearly all cancer types. Across diverse malignancies, cachectic weight loss episodes exhibited a consistent serologic signature characterized by lower albumin and hemoglobin and higher levels of liver enzymes. Numerous somatic tumor genotypes, including TP53 mutation across several diseases, were also associated with more frequent onset of cachectic episodes. Motivated by these observations, we developed a multivariate model to predict impending risk of cachectic weight loss in patients with lung, colorectal and prostate cancer, validated in an independent, external cohort from Dana-Farber Cancer Institute (n = 5,785). Routine clinicogenomic data are, therefore, a scalable resource for discovery in cancer cachexia.</p>","PeriodicalId":19037,"journal":{"name":"Nature Medicine","volume":" ","pages":""},"PeriodicalIF":52.5,"publicationDate":"2026-10-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149171358","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":"Population-scale reconstruction of menopause dynamics reveals a physiological cliff at the final menstrual period","authors":"Glen Pridham,&nbsp;Yoav Hayut,&nbsp;Noa Lavi-Shoseyov,&nbsp;Michal Neeman,&nbsp;Noa Hovav,&nbsp;Yoel Toledano,&nbsp;Uri Alon","doi":"10.1038/s41591-026-04614-0","DOIUrl":"10.1038/s41591-026-04614-0","url":null,"abstract":"Menopause reshapes female physiology, yet current understanding is limited by small longitudinal cohorts that characterize it as a gradual transition. Large-scale biomedical datasets remain underutilized because the final menstrual period (FMP) age is rarely recorded. Here we present a computational framework, inspired by astronomy, that reconstructs FMP-anchored trajectories from cross-sectional data by removing the blurring caused by variation in FMP age across individuals. Applying this to two independent cohorts totaling 300 million laboratory tests revealed a step-like physiological cliff at the FMP including endocrine, skeletal, hepatic, renal and lipid systems. These discontinuities are absent in male individuals, are concordant across populations and appear markedly attenuated by menopausal hormone therapy. Dysregulation began more than a decade before FMP. These findings support a systemic, quantifiable view of menopause and provide a generalizable strategy for recovering hidden biological trajectories applicable to other transitions such as puberty or disease progression. By using a novel computational framework, a cross-sectional analysis on laboratory data from two independent cohorts reveals that the final menstrual period marks an abrupt, multisystem physiological shift, with sex hormone changes beginning more than 10 years before menopause onset.","PeriodicalId":19037,"journal":{"name":"Nature Medicine","volume":"32 10","pages":"3823-3831"},"PeriodicalIF":52.5,"publicationDate":"2026-10-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.nature.comhttps://www.nature.com/articles/s41591-026-04614-0.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149170031","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-assisted scoping review of code sharing in clinical prediction model research.","authors":"Thomas Sounack, Raffaele Giancotti, Catherine A Gao, Lasai Barreñada, Hyeonhoon Lee, Hyung-Chul Lee, Leo Anthony Celi, Karel G M Moons, Gary S Collins, Charlotta Lindvall, Tom Pollard","doi":"10.1038/s41591-026-04691-1","DOIUrl":"https://doi.org/10.1038/s41591-026-04691-1","url":null,"abstract":"<p><p>Clinical prediction models are increasingly deployed to support diagnostic and prognostic decisions, making reproducibility essential for assessing their reliability and generalizability. Analytical code supports independent assessment of these processes, yet its availability in the literature remains limited. This scoping review quantifies current practices in sharing analytical code to inform the development of TRIPOD-Code, a reporting guideline for code availability and reproducibility. Here a large-language-model-assisted pipeline was developed to screen articles citing TRIPOD or TRIPOD+AI, extract repository links and assess retrieved repositories against 14 predefined reproducibility-related features. Among 3,967 articles, 482 (12.2%) included code-sharing statements. Sharing prevalence varied widely by journal and country. Repository assessment showed substantial heterogeneity in reproducibility features. These findings underscore the need for clearer expectations beyond code availability, including documentation, dependency specification and executable structure. Strengthening these practices may improve the usability of clinical prediction model studies and support their deployment in real-world clinical settings.</p>","PeriodicalId":19037,"journal":{"name":"Nature Medicine","volume":" ","pages":""},"PeriodicalIF":52.5,"publicationDate":"2026-10-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149149229","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":"Addendum: Aberrant epithelial GREM1 expression initiates colonic tumorigenesis from cells outside the stem cell niche.","authors":"Hayley Davis, Shazia Irshad, Mukesh Bansal, Hannah Rafferty, Tatjana Boitsova, Chiara Bardella, Emma Jaeger, Annabelle Lewis, Luke Freeman-Mills, Francesc C Giner, Pedro Rodenas-Cuadrado, Sreelakshmi Mallappa, Susan Clark, Huw Thomas, Rosemary Jeffery, Richard Poulsom, Manuel Rodriguez-Justo, Marco Novelli, Runjan Chetty, Andrew Silver, Owen J Sansom, Florian R Greten, Lai Mun Wang, James E East, Ian Tomlinson, Simon J Leedham","doi":"10.1038/s41591-026-04736-5","DOIUrl":"https://doi.org/10.1038/s41591-026-04736-5","url":null,"abstract":"","PeriodicalId":19037,"journal":{"name":"Nature Medicine","volume":" ","pages":""},"PeriodicalIF":52.5,"publicationDate":"2026-10-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149149107","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}