The tumor microenvironment (TME) considerably influences colorectal cancer (CRC) progression, therapeutic response and clinical outcome, but studies of interindividual heterogeneities of the TME in CRC are lacking. Here, by integrating human colorectal single-cell transcriptomic data from approximately 200 donors, we comprehensively characterized transcriptional remodeling in the TME compared to noncancer tissues and identified a rare tumor-specific subset of endothelial cells with T cell recruitment potential. The large sample size enabled us to stratify patients based on their TME heterogeneity, revealing divergent TME subtypes in which cancer cells exploit different immune evasion mechanisms. Additionally, by associating single-cell transcriptional profiling with risk genes identified by genome-wide association studies, we determined that stromal cells are major effector cell types in CRC genetic susceptibility. In summary, our results provide valuable insights into CRC pathogenesis and might help with the development of personalized immune therapies. Cheng and colleagues performed an integrative analysis of human colorectal cancer samples to characterize the tumor microenvironment (TME) and stratify patients according to their heterogeneous TMEs, which exploit different immune evasion mechanisms.
{"title":"Integrative single-cell analysis of human colorectal cancer reveals patient stratification with distinct immune evasion mechanisms","authors":"Xiaojing Chu, Xiangjie Li, Yu Zhang, Guohui Dang, Yuhui Miao, Wenbin Xu, Jinyu Wang, Zemin Zhang, Sijin Cheng","doi":"10.1038/s43018-024-00807-z","DOIUrl":"10.1038/s43018-024-00807-z","url":null,"abstract":"The tumor microenvironment (TME) considerably influences colorectal cancer (CRC) progression, therapeutic response and clinical outcome, but studies of interindividual heterogeneities of the TME in CRC are lacking. Here, by integrating human colorectal single-cell transcriptomic data from approximately 200 donors, we comprehensively characterized transcriptional remodeling in the TME compared to noncancer tissues and identified a rare tumor-specific subset of endothelial cells with T cell recruitment potential. The large sample size enabled us to stratify patients based on their TME heterogeneity, revealing divergent TME subtypes in which cancer cells exploit different immune evasion mechanisms. Additionally, by associating single-cell transcriptional profiling with risk genes identified by genome-wide association studies, we determined that stromal cells are major effector cell types in CRC genetic susceptibility. In summary, our results provide valuable insights into CRC pathogenesis and might help with the development of personalized immune therapies. Cheng and colleagues performed an integrative analysis of human colorectal cancer samples to characterize the tumor microenvironment (TME) and stratify patients according to their heterogeneous TMEs, which exploit different immune evasion mechanisms.","PeriodicalId":18885,"journal":{"name":"Nature cancer","volume":"5 9","pages":"1409-1426"},"PeriodicalIF":23.5,"publicationDate":"2024-08-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141988356","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 : 2024-08-12DOI: 10.1038/s43018-024-00802-4
Erik N. Bergstrom, Ludmil B. Alexandrov
Recent advancements in targeted immune checkpoint blockade (ICB) therapy have reshaped cancer treatment paradigms. However, many patients do not respond, highlighting the need for robust biomarkers. A study now introduces an approach using multi-omics data and machine learning to improve patient selection for ICB therapy, offering more effective treatment.
{"title":"Enhanced precision in immunotherapy","authors":"Erik N. Bergstrom, Ludmil B. Alexandrov","doi":"10.1038/s43018-024-00802-4","DOIUrl":"10.1038/s43018-024-00802-4","url":null,"abstract":"Recent advancements in targeted immune checkpoint blockade (ICB) therapy have reshaped cancer treatment paradigms. However, many patients do not respond, highlighting the need for robust biomarkers. A study now introduces an approach using multi-omics data and machine learning to improve patient selection for ICB therapy, offering more effective treatment.","PeriodicalId":18885,"journal":{"name":"Nature cancer","volume":"5 8","pages":"1136-1138"},"PeriodicalIF":23.5,"publicationDate":"2024-08-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141933565","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 : 2024-08-12DOI: 10.1038/s43018-024-00801-5
Combining SOS1 inhibitors with KRAS inhibitors improved the depth and durability of response in lung and colorectal cancer models. Restoration of response was observed in preclinical models rendered resistant to KRAS inhibitors. These results highlight the potential of SOS1 inhibitors to broaden the response to KRAS inhibitors in the clinic.
{"title":"SOS1 inhibitor combinations overcome KRAS inhibitor resistance","authors":"","doi":"10.1038/s43018-024-00801-5","DOIUrl":"10.1038/s43018-024-00801-5","url":null,"abstract":"Combining SOS1 inhibitors with KRAS inhibitors improved the depth and durability of response in lung and colorectal cancer models. Restoration of response was observed in preclinical models rendered resistant to KRAS inhibitors. These results highlight the potential of SOS1 inhibitors to broaden the response to KRAS inhibitors in the clinic.","PeriodicalId":18885,"journal":{"name":"Nature cancer","volume":"5 9","pages":"1294-1295"},"PeriodicalIF":23.5,"publicationDate":"2024-08-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141933568","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 : 2024-08-05DOI: 10.1038/s43018-024-00800-6
Venu Thatikonda, Hengyu Lyu, Sabine Jurado, Kaja Kostyrko, Christopher A. Bristow, Christoph Albrecht, Donat Alpar, Heribert Arnhof, Oliver Bergner, Karin Bosch, Ningping Feng, Sisi Gao, Daniel Gerlach, Michael Gmachl, Melanie Hinkel, Simone Lieb, Astrid Jeschko, Annette A. Machado, Thomas Madensky, Ethan D. Marszalek, Mikhila Mahendra, Gabriella Melo-Zainzinger, Jessica M. Molkentine, Philipp A. Jaeger, David H. Peng, Robyn L. Schenk, Alexey Sorokin, Sandra Strauss, Francesca Trapani, Scott Kopetz, Christopher P. Vellano, Mark Petronczki, Norbert Kraut, Timothy P. Heffernan, Joseph R. Marszalek, Mark Pearson, Irene C. Waizenegger, Marco H. Hofmann
Combination approaches are needed to strengthen and extend the clinical response to KRASG12C inhibitors (KRASG12Ci). Here, we assessed the antitumor responses of KRASG12C mutant lung and colorectal cancer models to combination treatment with a SOS1 inhibitor (SOS1i), BI-3406, plus the KRASG12C inhibitor, adagrasib. We found that responses to BI-3406 plus adagrasib were stronger than to adagrasib alone, comparable to adagrasib with SHP2 (SHP2i) or EGFR inhibitors and correlated with stronger suppression of RAS-MAPK signaling. BI-3406 plus adagrasib treatment also delayed the emergence of acquired resistance and elicited antitumor responses from adagrasib-resistant models. Resistance to KRASG12Ci seemed to be driven by upregulation of MRAS activity, which both SOS1i and SHP2i were found to potently inhibit. Knockdown of SHOC2, a MRAS complex partner, partially restored response to KRASG12Ci treatment. These results suggest KRASG12C plus SOS1i to be a promising strategy for treating both KRASG12Ci naive and relapsed KRASG12C-mutant tumors. Hofmann and colleagues describe the mechanism underlying the therapeutic benefit of combinatorial use of SOS1 and KRAS-G12C inhibitors in the context of KRAS-G12C mutant-driven lung and colorectal cancer.
{"title":"Co-targeting SOS1 enhances the antitumor effects of KRASG12C inhibitors by addressing intrinsic and acquired resistance","authors":"Venu Thatikonda, Hengyu Lyu, Sabine Jurado, Kaja Kostyrko, Christopher A. Bristow, Christoph Albrecht, Donat Alpar, Heribert Arnhof, Oliver Bergner, Karin Bosch, Ningping Feng, Sisi Gao, Daniel Gerlach, Michael Gmachl, Melanie Hinkel, Simone Lieb, Astrid Jeschko, Annette A. Machado, Thomas Madensky, Ethan D. Marszalek, Mikhila Mahendra, Gabriella Melo-Zainzinger, Jessica M. Molkentine, Philipp A. Jaeger, David H. Peng, Robyn L. Schenk, Alexey Sorokin, Sandra Strauss, Francesca Trapani, Scott Kopetz, Christopher P. Vellano, Mark Petronczki, Norbert Kraut, Timothy P. Heffernan, Joseph R. Marszalek, Mark Pearson, Irene C. Waizenegger, Marco H. Hofmann","doi":"10.1038/s43018-024-00800-6","DOIUrl":"10.1038/s43018-024-00800-6","url":null,"abstract":"Combination approaches are needed to strengthen and extend the clinical response to KRASG12C inhibitors (KRASG12Ci). Here, we assessed the antitumor responses of KRASG12C mutant lung and colorectal cancer models to combination treatment with a SOS1 inhibitor (SOS1i), BI-3406, plus the KRASG12C inhibitor, adagrasib. We found that responses to BI-3406 plus adagrasib were stronger than to adagrasib alone, comparable to adagrasib with SHP2 (SHP2i) or EGFR inhibitors and correlated with stronger suppression of RAS-MAPK signaling. BI-3406 plus adagrasib treatment also delayed the emergence of acquired resistance and elicited antitumor responses from adagrasib-resistant models. Resistance to KRASG12Ci seemed to be driven by upregulation of MRAS activity, which both SOS1i and SHP2i were found to potently inhibit. Knockdown of SHOC2, a MRAS complex partner, partially restored response to KRASG12Ci treatment. These results suggest KRASG12C plus SOS1i to be a promising strategy for treating both KRASG12Ci naive and relapsed KRASG12C-mutant tumors. Hofmann and colleagues describe the mechanism underlying the therapeutic benefit of combinatorial use of SOS1 and KRAS-G12C inhibitors in the context of KRAS-G12C mutant-driven lung and colorectal cancer.","PeriodicalId":18885,"journal":{"name":"Nature cancer","volume":"5 9","pages":"1352-1370"},"PeriodicalIF":23.5,"publicationDate":"2024-08-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.nature.com/articles/s43018-024-00800-6.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141893812","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 : 2024-07-26DOI: 10.1038/s43018-024-00798-x
Marcel Arias-Badia, Ryan Chang, Lawrence Fong
While the effector cells that mediate anti-tumor immunity have historically been attributed to αβ T cells and natural killer cells, γδ T cells are now being recognized as a complementary mechanism mediating tumor rejection. γδ T cells possess a host of functions ranging from antigen presentation to regulatory function and, importantly, have critical roles in eliciting anti-tumor responses where other immune effectors may be rendered ineffective. Recent discoveries have elucidated how these differing functions are mediated by γδ T cells with specific T cell receptors and spatial distribution. Their relative resistance to mechanisms of dysfunction like T cell exhaustion has spurred the development of therapeutic approaches exploiting γδ T cells, and an improved understanding of these cells should enable more effective immunotherapies. Fong and colleagues provide a Review on γδ T cells as mediators of anti-tumor immunity, discuss their role in the tumor microenvironment and reflect on therapeutic approaches to exploit γδ T cells.
介导抗肿瘤免疫的效应细胞历来被认为是 αβ T 细胞和自然杀伤细胞，而 γδ T 细胞现在被认为是介导肿瘤排斥反应的补充机制。γδT细胞具有从抗原递呈到调节功能的一系列功能，重要的是，在其他免疫效应因子可能失效的情况下，γδT细胞在激发抗肿瘤反应方面发挥着关键作用。最新发现阐明了具有特定 T 细胞受体和空间分布的 γδ T 细胞是如何介导这些不同功能的。γδT细胞对T细胞衰竭等功能障碍机制具有相对抵抗力，这推动了利用γδT细胞的治疗方法的发展。
{"title":"γδ T cells as critical anti-tumor immune effectors","authors":"Marcel Arias-Badia, Ryan Chang, Lawrence Fong","doi":"10.1038/s43018-024-00798-x","DOIUrl":"10.1038/s43018-024-00798-x","url":null,"abstract":"While the effector cells that mediate anti-tumor immunity have historically been attributed to αβ T cells and natural killer cells, γδ T cells are now being recognized as a complementary mechanism mediating tumor rejection. γδ T cells possess a host of functions ranging from antigen presentation to regulatory function and, importantly, have critical roles in eliciting anti-tumor responses where other immune effectors may be rendered ineffective. Recent discoveries have elucidated how these differing functions are mediated by γδ T cells with specific T cell receptors and spatial distribution. Their relative resistance to mechanisms of dysfunction like T cell exhaustion has spurred the development of therapeutic approaches exploiting γδ T cells, and an improved understanding of these cells should enable more effective immunotherapies. Fong and colleagues provide a Review on γδ T cells as mediators of anti-tumor immunity, discuss their role in the tumor microenvironment and reflect on therapeutic approaches to exploit γδ T cells.","PeriodicalId":18885,"journal":{"name":"Nature cancer","volume":"5 8","pages":"1145-1157"},"PeriodicalIF":23.5,"publicationDate":"2024-07-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141766741","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 : 2024-07-24DOI: 10.1038/s43018-024-00791-4
Aaron J. Stonestrom, Ross L. Levine
The mainly hematologic expression profile of phosphatidylinositol-3-kinase-γ (PI3Kγ) makes it an attractive therapeutic target. Recent work from three independent groups shows that inhibiting PI3Kγ impairs the metabolism and growth of acute myeloid leukemia cells — a finding that justifies further mechanistic and clinical exploration.
{"title":"Inhibiting PI3Kγ in acute myeloid leukemia","authors":"Aaron J. Stonestrom, Ross L. Levine","doi":"10.1038/s43018-024-00791-4","DOIUrl":"10.1038/s43018-024-00791-4","url":null,"abstract":"The mainly hematologic expression profile of phosphatidylinositol-3-kinase-γ (PI3Kγ) makes it an attractive therapeutic target. Recent work from three independent groups shows that inhibiting PI3Kγ impairs the metabolism and growth of acute myeloid leukemia cells — a finding that justifies further mechanistic and clinical exploration.","PeriodicalId":18885,"journal":{"name":"Nature cancer","volume":"5 7","pages":"958-959"},"PeriodicalIF":23.5,"publicationDate":"2024-07-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141759878","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 : 2024-07-24DOI: 10.1038/s43018-024-00795-0
Our non-randomized single-center clinical trial demonstrates the safety, cost-saving and time-saving potential of artificial intelligence (AI) assistance in the detection of breast cancer metastases in sentinel lymph nodes. AI assistance shows important benefits for pathologists and the laboratory workflow, which are needed as cancer incidence and diagnostics continue to rise.
{"title":"AI-assisted detection of lymph node metastases safely reduces costs and time","authors":"","doi":"10.1038/s43018-024-00795-0","DOIUrl":"10.1038/s43018-024-00795-0","url":null,"abstract":"Our non-randomized single-center clinical trial demonstrates the safety, cost-saving and time-saving potential of artificial intelligence (AI) assistance in the detection of breast cancer metastases in sentinel lymph nodes. AI assistance shows important benefits for pathologists and the laboratory workflow, which are needed as cancer incidence and diagnostics continue to rise.","PeriodicalId":18885,"journal":{"name":"Nature cancer","volume":"5 8","pages":"1139-1140"},"PeriodicalIF":23.5,"publicationDate":"2024-07-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141759877","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 : 2024-07-23DOI: 10.1038/s43018-024-00790-5
Cancer dependency maps have accelerated the discovery of essential genes and potential drug targets. Here we used machine learning to build translational dependency maps of patients’ tumors and normal tissue biopsies, which identified oncogenes and synthetic lethalities that are predictive of drug responses and patients’ outcomes.
{"title":"Using machine learning to translate tumor dependencies","authors":"","doi":"10.1038/s43018-024-00790-5","DOIUrl":"10.1038/s43018-024-00790-5","url":null,"abstract":"Cancer dependency maps have accelerated the discovery of essential genes and potential drug targets. Here we used machine learning to build translational dependency maps of patients’ tumors and normal tissue biopsies, which identified oncogenes and synthetic lethalities that are predictive of drug responses and patients’ outcomes.","PeriodicalId":18885,"journal":{"name":"Nature cancer","volume":"5 8","pages":"1141-1142"},"PeriodicalIF":23.5,"publicationDate":"2024-07-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141752145","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 : 2024-07-23DOI: 10.1038/s43018-024-00792-3
Current prostate cancer risk predictors are not able to fully capture a patient’s risk of recurrence at the time of diagnosis. Evolutionary metrics of tumor diversity, based on low-cost sequencing and digital pathology, might provide a new dimension of information to close the gap between prediction and outcome.
{"title":"Predicting the risk of prostate cancer recurrence through the lens of evolution","authors":"","doi":"10.1038/s43018-024-00792-3","DOIUrl":"10.1038/s43018-024-00792-3","url":null,"abstract":"Current prostate cancer risk predictors are not able to fully capture a patient’s risk of recurrence at the time of diagnosis. Evolutionary metrics of tumor diversity, based on low-cost sequencing and digital pathology, might provide a new dimension of information to close the gap between prediction and outcome.","PeriodicalId":18885,"journal":{"name":"Nature cancer","volume":"5 9","pages":"1296-1297"},"PeriodicalIF":23.5,"publicationDate":"2024-07-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141752144","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 : 2024-07-17DOI: 10.1038/s43018-024-00794-1
Bailey M. Robertson, Mitchell E. Fane, Ashani T. Weeraratna, Vito W. Rebecca
Metastatic melanoma is among the most enigmatic advanced cancers to clinically manage despite immense progress in the way of available therapeutic options and historic decreases in the melanoma mortality rate. Most patients with metastatic melanoma treated with modern targeted therapies (for example, BRAFV600E/K inhibitors) and/or immune checkpoint blockade (for example, anti-programmed death 1 therapy) will progress, owing to profound tumor cell plasticity fueled by genetic and nongenetic mechanisms and dichotomous host microenvironmental influences. Here we discuss the determinants of tumor heterogeneity, mechanisms of therapy resistance and effective therapy regimens that hold curative promise. Rebecca and colleagues discuss the complex biology of metastatic melanoma, as well as determinants of resistance to therapy and existing and promising therapy strategies.
{"title":"Determinants of resistance and response to melanoma therapy","authors":"Bailey M. Robertson, Mitchell E. Fane, Ashani T. Weeraratna, Vito W. Rebecca","doi":"10.1038/s43018-024-00794-1","DOIUrl":"10.1038/s43018-024-00794-1","url":null,"abstract":"Metastatic melanoma is among the most enigmatic advanced cancers to clinically manage despite immense progress in the way of available therapeutic options and historic decreases in the melanoma mortality rate. Most patients with metastatic melanoma treated with modern targeted therapies (for example, BRAFV600E/K inhibitors) and/or immune checkpoint blockade (for example, anti-programmed death 1 therapy) will progress, owing to profound tumor cell plasticity fueled by genetic and nongenetic mechanisms and dichotomous host microenvironmental influences. Here we discuss the determinants of tumor heterogeneity, mechanisms of therapy resistance and effective therapy regimens that hold curative promise. Rebecca and colleagues discuss the complex biology of metastatic melanoma, as well as determinants of resistance to therapy and existing and promising therapy strategies.","PeriodicalId":18885,"journal":{"name":"Nature cancer","volume":"5 7","pages":"964-982"},"PeriodicalIF":23.5,"publicationDate":"2024-07-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141633979","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}
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