Pub Date : 2024-07-05DOI: 10.1038/s43018-024-00799-w
C. van Dooijeweert, R. N. Flach, N. D. ter Hoeve, C. P. H. Vreuls, R. Goldschmeding, J. E. Freund, P. Pham, T. Q. Nguyen, E. van der Wall, G. W. J. Frederix, N. Stathonikos, P. J. van Diest
{"title":"Author Correction: Clinical implementation of artificial-intelligence-assisted detection of breast cancer metastases in sentinel lymph nodes: the CONFIDENT-B single-center, non-randomized clinical trial","authors":"C. van Dooijeweert, R. N. Flach, N. D. ter Hoeve, C. P. H. Vreuls, R. Goldschmeding, J. E. Freund, P. Pham, T. Q. Nguyen, E. van der Wall, G. W. J. Frederix, N. Stathonikos, P. J. van Diest","doi":"10.1038/s43018-024-00799-w","DOIUrl":"10.1038/s43018-024-00799-w","url":null,"abstract":"","PeriodicalId":18885,"journal":{"name":"Nature cancer","volume":null,"pages":null},"PeriodicalIF":23.5,"publicationDate":"2024-07-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.nature.com/articles/s43018-024-00799-w.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141538197","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 : 2024-07-03DOI: 10.1038/s43018-024-00793-2
Danh-Tai Hoang, Gal Dinstag, Eldad D. Shulman, Leandro C. Hermida, Doreen S. Ben-Zvi, Efrat Elis, Katherine Caley, Stephen-John Sammut, Sanju Sinha, Neelam Sinha, Christopher H. Dampier, Chani Stossel, Tejas Patil, Arun Rajan, Wiem Lassoued, Julius Strauss, Shania Bailey, Clint Allen, Jason Redman, Tuvik Beker, Peng Jiang, Talia Golan, Scott Wilkinson, Adam G. Sowalsky, Sharon R. Pine, Carlos Caldas, James L. Gulley, Kenneth Aldape, Ranit Aharonov, Eric A. Stone, Eytan Ruppin
Advances in artificial intelligence have paved the way for leveraging hematoxylin and eosin-stained tumor slides for precision oncology. We present ENLIGHT–DeepPT, an indirect two-step approach consisting of (1) DeepPT, a deep-learning framework that predicts genome-wide tumor mRNA expression from slides, and (2) ENLIGHT, which predicts response to targeted and immune therapies from the inferred expression values. We show that DeepPT successfully predicts transcriptomics in all 16 The Cancer Genome Atlas cohorts tested and generalizes well to two independent datasets. ENLIGHT–DeepPT successfully predicts true responders in five independent patient cohorts involving four different treatments spanning six cancer types, with an overall odds ratio of 2.28 and a 39.5% increased response rate among predicted responders versus the baseline rate. Notably, its prediction accuracy, obtained without any training on the treatment data, is comparable to that achieved by directly predicting the response from the images, which requires specific training on the treatment evaluation cohorts. Hoang et al. developed a deep-learning framework called ENLIGHT–DeepPT that predicts therapy response based on imputed transcriptomics and shows predictive power across patient cohorts and cancer types.
{"title":"A deep-learning framework to predict cancer treatment response from histopathology images through imputed transcriptomics","authors":"Danh-Tai Hoang, Gal Dinstag, Eldad D. Shulman, Leandro C. Hermida, Doreen S. Ben-Zvi, Efrat Elis, Katherine Caley, Stephen-John Sammut, Sanju Sinha, Neelam Sinha, Christopher H. Dampier, Chani Stossel, Tejas Patil, Arun Rajan, Wiem Lassoued, Julius Strauss, Shania Bailey, Clint Allen, Jason Redman, Tuvik Beker, Peng Jiang, Talia Golan, Scott Wilkinson, Adam G. Sowalsky, Sharon R. Pine, Carlos Caldas, James L. Gulley, Kenneth Aldape, Ranit Aharonov, Eric A. Stone, Eytan Ruppin","doi":"10.1038/s43018-024-00793-2","DOIUrl":"10.1038/s43018-024-00793-2","url":null,"abstract":"Advances in artificial intelligence have paved the way for leveraging hematoxylin and eosin-stained tumor slides for precision oncology. We present ENLIGHT–DeepPT, an indirect two-step approach consisting of (1) DeepPT, a deep-learning framework that predicts genome-wide tumor mRNA expression from slides, and (2) ENLIGHT, which predicts response to targeted and immune therapies from the inferred expression values. We show that DeepPT successfully predicts transcriptomics in all 16 The Cancer Genome Atlas cohorts tested and generalizes well to two independent datasets. ENLIGHT–DeepPT successfully predicts true responders in five independent patient cohorts involving four different treatments spanning six cancer types, with an overall odds ratio of 2.28 and a 39.5% increased response rate among predicted responders versus the baseline rate. Notably, its prediction accuracy, obtained without any training on the treatment data, is comparable to that achieved by directly predicting the response from the images, which requires specific training on the treatment evaluation cohorts. Hoang et al. developed a deep-learning framework called ENLIGHT–DeepPT that predicts therapy response based on imputed transcriptomics and shows predictive power across patient cohorts and cancer types.","PeriodicalId":18885,"journal":{"name":"Nature cancer","volume":null,"pages":null},"PeriodicalIF":23.5,"publicationDate":"2024-07-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141498463","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 : 2024-06-28DOI: 10.1038/s43018-024-00784-3
Evelyn Ramberger, Valeriia Sapozhnikova, Yuen Lam Dora Ng, Anna Dolnik, Matthias Ziehm, Oliver Popp, Eric Sträng, Miriam Kull, Florian Grünschläger, Josefine Krüger, Manuela Benary, Sina Müller, Xiang Gao, Arunima Murgai, Mohamed Haji, Annika Schmidt, Raphael Lutz, Axel Nogai, Jan Braune, Dominik Laue, Christian Langer, Cyrus Khandanpour, Florian Bassermann, Hartmut Döhner, Monika Engelhardt, Christian Straka, Michael Hundemer, Dieter Beule, Simon Haas, Ulrich Keller, Hermann Einsele, Lars Bullinger, Stefan Knop, Philipp Mertins, Jan Krönke
Multiple myeloma (MM) is a plasma cell malignancy of the bone marrow. Despite therapeutic advances, MM remains incurable, and better risk stratification as well as new therapies are therefore highly needed. The proteome of MM has not been systematically assessed before and holds the potential to uncover insight into disease biology and improved prognostication in addition to genetic and transcriptomic studies. Here we provide a comprehensive multiomics analysis including deep tandem mass tag-based quantitative global (phospho)proteomics, RNA sequencing, and nanopore DNA sequencing of 138 primary patient-derived plasma cell malignancies encompassing treatment-naive MM, plasma cell leukemia and the premalignancy monoclonal gammopathy of undetermined significance, as well as healthy controls. We found that the (phospho)proteome of malignant plasma cells are highly deregulated as compared with healthy plasma cells and is both defined by chromosomal alterations as well as posttranscriptional regulation. A prognostic protein signature was identified that is associated with aggressive disease independent of established risk factors in MM. Integration with functional genetics and single-cell RNA sequencing revealed general and genetic subtype-specific deregulated proteins and pathways in plasma cell malignancies that include potential targets for (immuno)therapies. Our study demonstrates the potential of proteogenomics in cancer and provides an easily accessible resource for investigating protein regulation and new therapeutic approaches in MM. Krönke and colleagues present a multiomic resource of plasma cell malignancies, including multiple myeloma, that comprises phosphoproteomics, RNA and DNA sequencing and provides insights into cancer type biology and candidate therapeutic targets.
多发性骨髓瘤（MM）是一种骨髓浆细胞恶性肿瘤。尽管治疗手段不断进步，但多发性骨髓瘤仍无法治愈，因此亟需更好的风险分层和新疗法。MM 的蛋白质组以前从未被系统评估过，除了基因和转录组研究外，蛋白质组还有可能揭示疾病的生物学特性并改善预后。在这里，我们提供了一项全面的多组学分析，包括基于深度串联质量标签的全局（磷）定量蛋白质组学、RNA测序和纳米孔DNA测序，分析对象是138例原发性浆细胞恶性肿瘤患者，包括未经治疗的MM、浆细胞白血病和恶性肿瘤前意义未定的单克隆性腺病以及健康对照组。我们发现，与健康浆细胞相比，恶性浆细胞的（磷酸化）蛋白质组高度失调，并由染色体改变和转录后调控共同决定。研究发现了一种预后蛋白特征，它与MM的侵袭性疾病相关，与已确定的风险因素无关。与功能遗传学和单细胞 RNA 测序相结合，发现了浆细胞恶性肿瘤中一般的和基因亚型特异性的失调蛋白和通路，其中包括潜在的（免疫）疗法靶点。我们的研究证明了蛋白质基因组学在癌症中的潜力，并为研究 MM 的蛋白质调控和新的治疗方法提供了易于获取的资源。
{"title":"The proteogenomic landscape of multiple myeloma reveals insights into disease biology and therapeutic opportunities","authors":"Evelyn Ramberger, Valeriia Sapozhnikova, Yuen Lam Dora Ng, Anna Dolnik, Matthias Ziehm, Oliver Popp, Eric Sträng, Miriam Kull, Florian Grünschläger, Josefine Krüger, Manuela Benary, Sina Müller, Xiang Gao, Arunima Murgai, Mohamed Haji, Annika Schmidt, Raphael Lutz, Axel Nogai, Jan Braune, Dominik Laue, Christian Langer, Cyrus Khandanpour, Florian Bassermann, Hartmut Döhner, Monika Engelhardt, Christian Straka, Michael Hundemer, Dieter Beule, Simon Haas, Ulrich Keller, Hermann Einsele, Lars Bullinger, Stefan Knop, Philipp Mertins, Jan Krönke","doi":"10.1038/s43018-024-00784-3","DOIUrl":"10.1038/s43018-024-00784-3","url":null,"abstract":"Multiple myeloma (MM) is a plasma cell malignancy of the bone marrow. Despite therapeutic advances, MM remains incurable, and better risk stratification as well as new therapies are therefore highly needed. The proteome of MM has not been systematically assessed before and holds the potential to uncover insight into disease biology and improved prognostication in addition to genetic and transcriptomic studies. Here we provide a comprehensive multiomics analysis including deep tandem mass tag-based quantitative global (phospho)proteomics, RNA sequencing, and nanopore DNA sequencing of 138 primary patient-derived plasma cell malignancies encompassing treatment-naive MM, plasma cell leukemia and the premalignancy monoclonal gammopathy of undetermined significance, as well as healthy controls. We found that the (phospho)proteome of malignant plasma cells are highly deregulated as compared with healthy plasma cells and is both defined by chromosomal alterations as well as posttranscriptional regulation. A prognostic protein signature was identified that is associated with aggressive disease independent of established risk factors in MM. Integration with functional genetics and single-cell RNA sequencing revealed general and genetic subtype-specific deregulated proteins and pathways in plasma cell malignancies that include potential targets for (immuno)therapies. Our study demonstrates the potential of proteogenomics in cancer and provides an easily accessible resource for investigating protein regulation and new therapeutic approaches in MM. Krönke and colleagues present a multiomic resource of plasma cell malignancies, including multiple myeloma, that comprises phosphoproteomics, RNA and DNA sequencing and provides insights into cancer type biology and candidate therapeutic targets.","PeriodicalId":18885,"journal":{"name":"Nature cancer","volume":null,"pages":null},"PeriodicalIF":23.5,"publicationDate":"2024-06-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.nature.com/articles/s43018-024-00784-3.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141469519","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 : 2024-06-27DOI: 10.1038/s43018-024-00788-z
C. van Dooijeweert, R. N. Flach, N. D. ter Hoeve, C. P. H. Vreuls, R. Goldschmeding, J. E. Freund, P. Pham, T. Q. Nguyen, E. van der Wall, G. W. J. Frederix, N. Stathonikos, P. J. van Diest
Pathologists’ assessment of sentinel lymph nodes (SNs) for breast cancer (BC) metastases is a treatment-guiding yet labor-intensive and costly task because of the performance of immunohistochemistry (IHC) in morphologically negative cases. This non-randomized, single-center clinical trial (International Standard Randomized Controlled Trial Number:14323711) assessed the efficacy of an artificial intelligence (AI)-assisted workflow for detecting BC metastases in SNs while maintaining diagnostic safety standards. From September 2022 to May 2023, 190 SN specimens were consecutively enrolled and allocated biweekly to the intervention arm (n = 100) or control arm (n = 90). In both arms, digital whole-slide images of hematoxylin–eosin sections of SN specimens were assessed by an expert pathologist, who was assisted by the ‘Metastasis Detection’ app (Visiopharm) in the intervention arm. Our primary endpoint showed a significantly reduced adjusted relative risk of IHC use (0.680, 95% confidence interval: 0.347–0.878) for AI-assisted pathologists, with subsequent cost savings of ~3,000 €. Secondary endpoints showed significant time reductions and up to 30% improved sensitivity for AI-assisted pathologists. This trial demonstrates the safety and potential for cost and time savings of AI assistance. Van Dooijeweert et al. conducted a prospective study on the clinical implementation of artificial-intelligence-assisted detection of sentinel lymph node metastasis in persons with breast cancer and report on its effects, including on time and cost.
{"title":"Clinical implementation of artificial-intelligence-assisted detection of breast cancer metastases in sentinel lymph nodes: the CONFIDENT-B single-center, non-randomized clinical trial","authors":"C. van Dooijeweert, R. N. Flach, N. D. ter Hoeve, C. P. H. Vreuls, R. Goldschmeding, J. E. Freund, P. Pham, T. Q. Nguyen, E. van der Wall, G. W. J. Frederix, N. Stathonikos, P. J. van Diest","doi":"10.1038/s43018-024-00788-z","DOIUrl":"10.1038/s43018-024-00788-z","url":null,"abstract":"Pathologists’ assessment of sentinel lymph nodes (SNs) for breast cancer (BC) metastases is a treatment-guiding yet labor-intensive and costly task because of the performance of immunohistochemistry (IHC) in morphologically negative cases. This non-randomized, single-center clinical trial (International Standard Randomized Controlled Trial Number:14323711) assessed the efficacy of an artificial intelligence (AI)-assisted workflow for detecting BC metastases in SNs while maintaining diagnostic safety standards. From September 2022 to May 2023, 190 SN specimens were consecutively enrolled and allocated biweekly to the intervention arm (n = 100) or control arm (n = 90). In both arms, digital whole-slide images of hematoxylin–eosin sections of SN specimens were assessed by an expert pathologist, who was assisted by the ‘Metastasis Detection’ app (Visiopharm) in the intervention arm. Our primary endpoint showed a significantly reduced adjusted relative risk of IHC use (0.680, 95% confidence interval: 0.347–0.878) for AI-assisted pathologists, with subsequent cost savings of ~3,000 €. Secondary endpoints showed significant time reductions and up to 30% improved sensitivity for AI-assisted pathologists. This trial demonstrates the safety and potential for cost and time savings of AI assistance. Van Dooijeweert et al. conducted a prospective study on the clinical implementation of artificial-intelligence-assisted detection of sentinel lymph node metastasis in persons with breast cancer and report on its effects, including on time and cost.","PeriodicalId":18885,"journal":{"name":"Nature cancer","volume":null,"pages":null},"PeriodicalIF":23.5,"publicationDate":"2024-06-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.nature.com/articles/s43018-024-00788-z.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141469518","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 : 2024-06-27DOI: 10.1038/s43018-024-00779-0
Darragh Flood, Cormac T. Taylor
Acute myeloid leukemia (AML) is an aggressive hematological cancer with limited treatment options. A study now provides compelling data and develops a therapeutic approach of targeting AML with a prolyl hydroxylase inhibitor, a strategy based on the sensitivity of myeloid cells to modulation of the transcription factor HIF.
{"title":"Targeting HIF-1 to treat AML","authors":"Darragh Flood, Cormac T. Taylor","doi":"10.1038/s43018-024-00779-0","DOIUrl":"10.1038/s43018-024-00779-0","url":null,"abstract":"Acute myeloid leukemia (AML) is an aggressive hematological cancer with limited treatment options. A study now provides compelling data and develops a therapeutic approach of targeting AML with a prolyl hydroxylase inhibitor, a strategy based on the sensitivity of myeloid cells to modulation of the transcription factor HIF.","PeriodicalId":18885,"journal":{"name":"Nature cancer","volume":null,"pages":null},"PeriodicalIF":23.5,"publicationDate":"2024-06-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141469521","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 : 2024-06-27DOI: 10.1038/s43018-024-00777-2
Nathaniel W. Mabe, Jennifer A. Perry, Clare F. Malone, Kimberly Stegmaier
Epigenetic dysregulation is increasingly appreciated as a hallmark of cancer, including disease initiation, maintenance and therapy resistance. As a result, there have been advances in the development and evaluation of epigenetic therapies for cancer, revealing substantial promise but also challenges. Three epigenetic inhibitor classes are approved in the USA, and many more are currently undergoing clinical investigation. In this Review, we discuss recent developments for each epigenetic drug class and their implications for therapy, as well as highlight new insights into the role of epigenetics in cancer. Stegmaier and colleagues provide a review on the latest development in targeting the cancer epigenome, give an overview of distinct drug classes, and discuss therapeutic possibilities and challenges.
{"title":"Pharmacological targeting of the cancer epigenome","authors":"Nathaniel W. Mabe, Jennifer A. Perry, Clare F. Malone, Kimberly Stegmaier","doi":"10.1038/s43018-024-00777-2","DOIUrl":"10.1038/s43018-024-00777-2","url":null,"abstract":"Epigenetic dysregulation is increasingly appreciated as a hallmark of cancer, including disease initiation, maintenance and therapy resistance. As a result, there have been advances in the development and evaluation of epigenetic therapies for cancer, revealing substantial promise but also challenges. Three epigenetic inhibitor classes are approved in the USA, and many more are currently undergoing clinical investigation. In this Review, we discuss recent developments for each epigenetic drug class and their implications for therapy, as well as highlight new insights into the role of epigenetics in cancer. Stegmaier and colleagues provide a review on the latest development in targeting the cancer epigenome, give an overview of distinct drug classes, and discuss therapeutic possibilities and challenges.","PeriodicalId":18885,"journal":{"name":"Nature cancer","volume":null,"pages":null},"PeriodicalIF":23.5,"publicationDate":"2024-06-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141469520","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 : 2024-06-25DOI: 10.1038/s43018-024-00780-7
Michele De Palma, Douglas Hanahan
Research into the mechanisms and manifestations of solid tumor vascularization was launched more than 50 years ago with the proposition and experimental demonstrations that angiogenesis is instrumental for tumor growth and was, therefore, a promising therapeutic target. The biological knowledge and therapeutic insights forthcoming have been remarkable, punctuated by new concepts, many of which were not foreseen in the early decades. This article presents a perspective on tumor vascularization and its therapeutic targeting but does not portray a historical timeline. Rather, we highlight eight conceptual milestones, integrating initial discoveries and recent progress and posing open questions for the future. De Palma and Hanahan outline advances in understanding tumor angiogenesis and discuss the therapeutic opportunities of targeting tumor vascularization.
{"title":"Milestones in tumor vascularization and its therapeutic targeting","authors":"Michele De Palma, Douglas Hanahan","doi":"10.1038/s43018-024-00780-7","DOIUrl":"10.1038/s43018-024-00780-7","url":null,"abstract":"Research into the mechanisms and manifestations of solid tumor vascularization was launched more than 50 years ago with the proposition and experimental demonstrations that angiogenesis is instrumental for tumor growth and was, therefore, a promising therapeutic target. The biological knowledge and therapeutic insights forthcoming have been remarkable, punctuated by new concepts, many of which were not foreseen in the early decades. This article presents a perspective on tumor vascularization and its therapeutic targeting but does not portray a historical timeline. Rather, we highlight eight conceptual milestones, integrating initial discoveries and recent progress and posing open questions for the future. De Palma and Hanahan outline advances in understanding tumor angiogenesis and discuss the therapeutic opportunities of targeting tumor vascularization.","PeriodicalId":18885,"journal":{"name":"Nature cancer","volume":null,"pages":null},"PeriodicalIF":23.5,"publicationDate":"2024-06-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141450855","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 : 2024-06-20DOI: 10.1038/s43018-024-00785-2
Kevin P. Letscher, Sai T. Reddy
At present, six CAR-T therapies are FDA approved to treat hematological cancers, but not all patients respond. A new study has developed a multidimensional functional profiling method to screen CAR-T cells from patients with large B cell lymphomas in clinical trials and identified a T cell subset associated with successful clinical response.
{"title":"Multidimensional analysis reveals predictive markers for CAR-T efficacy","authors":"Kevin P. Letscher, Sai T. Reddy","doi":"10.1038/s43018-024-00785-2","DOIUrl":"10.1038/s43018-024-00785-2","url":null,"abstract":"At present, six CAR-T therapies are FDA approved to treat hematological cancers, but not all patients respond. A new study has developed a multidimensional functional profiling method to screen CAR-T cells from patients with large B cell lymphomas in clinical trials and identified a T cell subset associated with successful clinical response.","PeriodicalId":18885,"journal":{"name":"Nature cancer","volume":null,"pages":null},"PeriodicalIF":23.5,"publicationDate":"2024-06-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141432277","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 : 2024-06-17DOI: 10.1038/s43018-024-00797-y
Emilie A. Chapeau, Laurent Sansregret, Giorgio G. Galli, Patrick Chène, Markus Wartmann, Thanos P. Mourikis, Patricia Jaaks, Sabrina Baltschukat, Ines A. M. Barbosa, Daniel Bauer, Saskia M. Brachmann, Clara Delaunay, Claire Estadieu, Jason E. Faris, Pascal Furet, Stefanie Harlfinger, Andreas Hueber, Eloísa Jiménez Núñez, David P. Kodack, Emeline Mandon, Typhaine Martin, Yannick Mesrouze, Vincent Romanet, Clemens Scheufler, Holger Sellner, Christelle Stamm, Dario Sterker, Luca Tordella, Francesco Hofmann, Nicolas Soldermann, Tobias Schmelzle
{"title":"Author Correction: Direct and selective pharmacological disruption of the YAP–TEAD interface by IAG933 inhibits Hippo-dependent and RAS–MAPK-altered cancers","authors":"Emilie A. Chapeau, Laurent Sansregret, Giorgio G. Galli, Patrick Chène, Markus Wartmann, Thanos P. Mourikis, Patricia Jaaks, Sabrina Baltschukat, Ines A. M. Barbosa, Daniel Bauer, Saskia M. Brachmann, Clara Delaunay, Claire Estadieu, Jason E. Faris, Pascal Furet, Stefanie Harlfinger, Andreas Hueber, Eloísa Jiménez Núñez, David P. Kodack, Emeline Mandon, Typhaine Martin, Yannick Mesrouze, Vincent Romanet, Clemens Scheufler, Holger Sellner, Christelle Stamm, Dario Sterker, Luca Tordella, Francesco Hofmann, Nicolas Soldermann, Tobias Schmelzle","doi":"10.1038/s43018-024-00797-y","DOIUrl":"10.1038/s43018-024-00797-y","url":null,"abstract":"","PeriodicalId":18885,"journal":{"name":"Nature cancer","volume":null,"pages":null},"PeriodicalIF":23.5,"publicationDate":"2024-06-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11286518/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141419845","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 : 2024-06-06DOI: 10.1038/s43018-024-00771-8
Tommaso Scolaro, Marta Manco, Mathieu Pecqueux, Ricardo Amorim, Rosa Trotta, Heleen H. Van Acker, Matthias Van Haele, Niranjan Shirgaonkar, Stefan Naulaerts, Jan Daniluk, Fran Prenen, Chiara Varamo, Donatella Ponti, Ginevra Doglioni, Ana Margarida Ferreira Campos, Juan Fernandez Garcia, Silvia Radenkovic, Pegah Rouhi, Aleksandar Beatovic, Liwei Wang, Yu Wang, Amalia Tzoumpa, Asier Antoranz, Ara Sargsian, Mario Di Matteo, Emanuele Berardi, Jermaine Goveia, Bart Ghesquière, Tania Roskams, Stefaan Soenen, Thomas Voets, Bella Manshian, Sarah-Maria Fendt, Peter Carmeliet, Abhishek D. Garg, Ramanuj DasGupta, Baki Topal, Massimiliano Mazzone
Many individuals with cancer are resistant to immunotherapies. Here, we identify the gene encoding the pyrimidine salvage pathway enzyme cytidine deaminase (CDA) among the top upregulated metabolic genes in several immunotherapy-resistant tumors. We show that CDA in cancer cells contributes to the uridine diphosphate (UDP) pool. Extracellular UDP hijacks immunosuppressive tumor-associated macrophages (TAMs) through its receptor P2Y6. Pharmacologic or genetic inhibition of CDA in cancer cells (or P2Y6 in TAMs) disrupts TAM-mediated immunosuppression, promoting cytotoxic T cell entry and susceptibility to anti-programmed cell death protein 1 (anti-PD-1) treatment in resistant pancreatic ductal adenocarcinoma (PDAC) and melanoma models. Conversely, CDA overexpression in CDA-depleted PDACs or anti-PD-1-responsive colorectal tumors or systemic UDP administration (re)establishes resistance. In individuals with PDAC, high CDA levels in cancer cells correlate with increased TAMs, lower cytotoxic T cells and possibly anti-PD-1 resistance. In a pan-cancer single-cell atlas, CDAhigh cancer cells match with T cell cytotoxicity dysfunction and P2RY6high TAMs. Overall, we suggest CDA and P2Y6 as potential targets for cancer immunotherapy. Scolaro et al. identify the enzyme cytidine deaminase (CDA) as upregulated in immunotherapy-resistant tumors and find it contributes to the UDP pool, which in turn modulates tumor-associated macrophages to instruct an immune-evasive TME.
{"title":"Nucleotide metabolism in cancer cells fuels a UDP-driven macrophage cross-talk, promoting immunosuppression and immunotherapy resistance","authors":"Tommaso Scolaro, Marta Manco, Mathieu Pecqueux, Ricardo Amorim, Rosa Trotta, Heleen H. Van Acker, Matthias Van Haele, Niranjan Shirgaonkar, Stefan Naulaerts, Jan Daniluk, Fran Prenen, Chiara Varamo, Donatella Ponti, Ginevra Doglioni, Ana Margarida Ferreira Campos, Juan Fernandez Garcia, Silvia Radenkovic, Pegah Rouhi, Aleksandar Beatovic, Liwei Wang, Yu Wang, Amalia Tzoumpa, Asier Antoranz, Ara Sargsian, Mario Di Matteo, Emanuele Berardi, Jermaine Goveia, Bart Ghesquière, Tania Roskams, Stefaan Soenen, Thomas Voets, Bella Manshian, Sarah-Maria Fendt, Peter Carmeliet, Abhishek D. Garg, Ramanuj DasGupta, Baki Topal, Massimiliano Mazzone","doi":"10.1038/s43018-024-00771-8","DOIUrl":"10.1038/s43018-024-00771-8","url":null,"abstract":"Many individuals with cancer are resistant to immunotherapies. Here, we identify the gene encoding the pyrimidine salvage pathway enzyme cytidine deaminase (CDA) among the top upregulated metabolic genes in several immunotherapy-resistant tumors. We show that CDA in cancer cells contributes to the uridine diphosphate (UDP) pool. Extracellular UDP hijacks immunosuppressive tumor-associated macrophages (TAMs) through its receptor P2Y6. Pharmacologic or genetic inhibition of CDA in cancer cells (or P2Y6 in TAMs) disrupts TAM-mediated immunosuppression, promoting cytotoxic T cell entry and susceptibility to anti-programmed cell death protein 1 (anti-PD-1) treatment in resistant pancreatic ductal adenocarcinoma (PDAC) and melanoma models. Conversely, CDA overexpression in CDA-depleted PDACs or anti-PD-1-responsive colorectal tumors or systemic UDP administration (re)establishes resistance. In individuals with PDAC, high CDA levels in cancer cells correlate with increased TAMs, lower cytotoxic T cells and possibly anti-PD-1 resistance. In a pan-cancer single-cell atlas, CDAhigh cancer cells match with T cell cytotoxicity dysfunction and P2RY6high TAMs. Overall, we suggest CDA and P2Y6 as potential targets for cancer immunotherapy. Scolaro et al. identify the enzyme cytidine deaminase (CDA) as upregulated in immunotherapy-resistant tumors and find it contributes to the UDP pool, which in turn modulates tumor-associated macrophages to instruct an immune-evasive TME.","PeriodicalId":18885,"journal":{"name":"Nature cancer","volume":null,"pages":null},"PeriodicalIF":23.5,"publicationDate":"2024-06-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.nature.com/articles/s43018-024-00771-8.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141284214","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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