Nature Reviews Clinical Oncology最新文献_第4页

Osimertinib efficacious as maintenance therapy in patients with stage III NSCLC 奥希替尼作为III期NSCLC患者的维持疗法疗效显著

IF 81.1 1区医学

Nature Reviews Clinical Oncology Pub Date : 2024-06-17 DOI: 10.1038/s41571-024-00915-w

Peter Sidaway

引用次数: 0

Neoadjuvant ipilimumab–nivolumab superior to adjuvant nivolumab 新辅助治疗伊匹单抗-尼妥珠单抗优于辅助治疗尼妥珠单抗

IF 81.1 1区医学

Nature Reviews Clinical Oncology Pub Date : 2024-06-14 DOI: 10.1038/s41571-024-00916-9

Peter Sidaway

引用次数: 0

Towards equitable AI in oncology 在肿瘤学领域实现公平的人工智能

IF 81.1 1区医学

Nature Reviews Clinical Oncology Pub Date : 2024-06-07 DOI: 10.1038/s41571-024-00909-8

Vidya Sankar Viswanathan, Vani Parmar, Anant Madabhushi

{"title":"Towards equitable AI in oncology","authors":"Vidya Sankar Viswanathan, Vani Parmar, Anant Madabhushi","doi":"10.1038/s41571-024-00909-8","DOIUrl":"10.1038/s41571-024-00909-8","url":null,"abstract":"Artificial intelligence (AI) stands at the threshold of revolutionizing clinical oncology, with considerable potential to improve early cancer detection and risk assessment, and to enable more accurate personalized treatment recommendations. However, a notable imbalance exists in the distribution of the benefits of AI, which disproportionately favour those living in specific geographical locations and in specific populations. In this Perspective, we discuss the need to foster the development of equitable AI tools that are both accurate in and accessible to a diverse range of patient populations, including those in low-income to middle-income countries. We also discuss some of the challenges and potential solutions in attaining equitable AI, including addressing the historically limited representation of diverse populations in existing clinical datasets and the use of inadequate clinical validation methods. Additionally, we focus on extant sources of inequity including the type of model approach (such as deep learning, and feature engineering-based methods), the implications of dataset curation strategies, the need for rigorous validation across a variety of populations and settings, and the risk of introducing contextual bias that comes with developing tools predominantly in high-income countries. Artificial intelligence (AI) has the potential to dramatically change several aspects of oncology including diagnosis, early detection and treatment-related decision making. However, many of the underlying algorithms have been or are being trained on datasets that do not necessarily reflect the diversity of the target population. For this, and other reasons, many AI tools might not be suitable for application in less economically developed countries and/or in patients of certain ethnicities. In this Perspective, the authors discuss possible sources of inequity in AI development, and how to ensure the development and implementation of equitable AI tools for use in patients with cancer.","PeriodicalId":19079,"journal":{"name":"Nature Reviews Clinical Oncology","volume":null,"pages":null},"PeriodicalIF":81.1,"publicationDate":"2024-06-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141287147","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}

引用次数: 0

Exploiting bacteria for cancer immunotherapy 利用细菌进行癌症免疫疗法

IF 81.1 1区医学

Nature Reviews Clinical Oncology Pub Date : 2024-06-05 DOI: 10.1038/s41571-024-00908-9

Seong-Young Kwon, Hien Thi-Thu Ngo, Jinbae Son, Yeongjin Hong, Jung-Joon Min

{"title":"Exploiting bacteria for cancer immunotherapy","authors":"Seong-Young Kwon, Hien Thi-Thu Ngo, Jinbae Son, Yeongjin Hong, Jung-Joon Min","doi":"10.1038/s41571-024-00908-9","DOIUrl":"10.1038/s41571-024-00908-9","url":null,"abstract":"Immunotherapy has revolutionized the treatment of cancer but continues to be constrained by limited response rates, acquired resistance, toxicities and high costs, which necessitates the development of new, innovative strategies. The discovery of a connection between the human microbiota and cancer dates back 4,000 years, when local infection was observed to result in tumour eradication in some individuals. However, the true oncological relevance of the intratumoural microbiota was not recognized until the turn of the twentieth century. The intratumoural microbiota can have pivotal roles in both the pathogenesis and treatment of cancer. In particular, intratumoural bacteria can either promote or inhibit cancer growth via remodelling of the tumour microenvironment. Over the past two decades, remarkable progress has been made preclinically in engineering bacteria as agents for cancer immunotherapy; some of these bacterial products have successfully reached the clinical stages of development. In this Review, we discuss the characteristics of intratumoural bacteria and their intricate interactions with the tumour microenvironment. We also describe the many strategies used to engineer bacteria for use in the treatment of cancer, summarizing contemporary data from completed and ongoing clinical trials. The work described herein highlights the potential of bacteria to transform the landscape of cancer therapy, bridging ancient wisdom with modern scientific innovation. Increasing evidence indicates that intratumoural bacteria can have crucial roles in both the pathogenesis and treatment of cancer. In this Review, the authors discuss the characteristics of intratumoural bacteria and the emerging understanding of their tumour-promoting and antitumour activities. They also describe a range of innovative strategies that are being used to engineer bacteria for use in the treatment of cancer and summarize clinical trials of various bacteria-mediated cancer immunotherapies.","PeriodicalId":19079,"journal":{"name":"Nature Reviews Clinical Oncology","volume":null,"pages":null},"PeriodicalIF":81.1,"publicationDate":"2024-06-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.nature.com/articles/s41571-024-00908-9.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141251784","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}

引用次数: 0

Bispecific and multispecific antibodies in oncology: opportunities and challenges 肿瘤学中的双特异性和多特异性抗体：机遇与挑战。

IF 81.1 1区医学

Nature Reviews Clinical Oncology Pub Date : 2024-05-31 DOI: 10.1038/s41571-024-00905-y

Maria-Elisabeth Goebeler, Gernot Stuhler, Ralf Bargou

{"title":"Bispecific and multispecific antibodies in oncology: opportunities and challenges","authors":"Maria-Elisabeth Goebeler, Gernot Stuhler, Ralf Bargou","doi":"10.1038/s41571-024-00905-y","DOIUrl":"10.1038/s41571-024-00905-y","url":null,"abstract":"Research into bispecific antibodies, which are designed to simultaneously bind two antigens or epitopes, has advanced enormously over the past two decades. Owing to advances in protein engineering technologies and considerable preclinical research efforts, bispecific antibodies are constantly being developed and optimized to improve their efficacy and to mitigate toxicity. To date, >200 of these agents, the majority of which are bispecific immune cell engagers, are in either preclinical or clinical evaluation. In this Review, we discuss the role of bispecific antibodies in patients with cancer, including history and development, as well as innovative targeting strategies, clinical applications, and adverse events. We also discuss novel alternative bispecific antibody constructs, such as those targeting two antigens expressed by tumour cells or cells located in the tumour microenvironment. Finally, we consider future research directions in this rapidly evolving field, including innovative antibody engineering strategies, which might enable more effective delivery, overcome resistance, and thus optimize clinical outcomes. Following the introduction of blinatumomab in 2014, the past 4 years have seen the approval of a further ten bispecific antibodies, reflecting substantial research effort and clinical interest in these agents. In this Review, the authors describe the developments leading to the approval of these novel agents and highlight important future research directions, including clinical optimization as well as innovative antibody engineering approaches.","PeriodicalId":19079,"journal":{"name":"Nature Reviews Clinical Oncology","volume":null,"pages":null},"PeriodicalIF":81.1,"publicationDate":"2024-05-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141184402","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}

引用次数: 0

RADICALS-HD sheds light on the role of ADT addition to post-operative radiotherapy RADICALS-HD揭示了在术后放疗中添加ADT的作用

IF 81.1 1区医学

Nature Reviews Clinical Oncology Pub Date : 2024-05-30 DOI: 10.1038/s41571-024-00912-z

Diana Romero

引用次数: 0

Ponatinib superior to imatinib in Ph+ ALL 在 Ph+ ALL 中，泊纳替尼优于伊马替尼。

IF 81.1 1区医学

Nature Reviews Clinical Oncology Pub Date : 2024-05-28 DOI: 10.1038/s41571-024-00911-0

Peter Sidaway

引用次数: 0

Adding ibrutinib to frontline therapy improves outcomes in transplant-eligible patients with MCL 在一线治疗中加入伊布替尼能改善符合移植条件的MCL患者的治疗效果。

IF 81.1 1区医学

Nature Reviews Clinical Oncology Pub Date : 2024-05-24 DOI: 10.1038/s41571-024-00910-1

David Killock

引用次数: 0

Gaining ground in personalized breast cancer therapy: lesson learned from PHERGain 在个性化乳腺癌治疗方面取得进展：PHERGain 的经验教训

IF 81.1 1区医学

Nature Reviews Clinical Oncology Pub Date : 2024-05-22 DOI: 10.1038/s41571-024-00907-w

Maria Vittoria Dieci, Valentina Guarneri

引用次数: 0

Predicting tumour origin with cytology-based deep learning: hype or hope? 利用基于细胞学的深度学习预测肿瘤来源：炒作还是希望？

IF 81.1 1区医学

Nature Reviews Clinical Oncology Pub Date : 2024-05-21 DOI: 10.1038/s41571-024-00906-x

Elie Rassy, Nicholas Pavlidis

引用次数: 0