Suppr超能文献

组织工程化患者来源骨肉瘤模型解析肿瘤-骨相互作用。

Tissue-engineered patient-derived osteosarcoma models dissecting tumour-bone interactions.

机构信息

Department of Orthopaedics and Trauma Surgery, Musculoskeletal University Center Munich (MUM), LMU University Hospital, LMU Munich, Marchioninistr. 15, 81377, Munich, Germany.

Department of Orthopaedics and Trauma Surgery, Orthopaedic Oncology, Musculoskeletal University Center Munich (MUM), LMU University Hospital, LMU Munich, Marchioninistr. 15, 81377, Munich, Germany.

出版信息

Cancer Metastasis Rev. 2024 Nov 27;44(1):8. doi: 10.1007/s10555-024-10218-2.

Abstract

Osteosarcoma is the most common malignant bone tumor, primarily affecting children and young adults. For these young patients, the current treatment options for osteosarcoma impose considerable constraints on daily life with significant morbidity and a low survival rate. Despite ongoing research efforts, the 5-year survival rate of first-diagnosed patients without metastases has not changed in the past four decades. The demand for novel treatments is currently still unmet, in particular for effective second-line therapy. Therefore, there is an urgent need for advanced preclinical models and drug-testing platforms that take into account the complex disease characteristics, the high heterogeneity of the tumour and the interactions with the bone microenvironment. In this review, we provide a comprehensive overview about state-of-the-art tissue-engineered and patient-specific models for osteosarcoma. These sophisticated platforms for advanced therapy trials aim to improve treatment outcomes for future patients by modelling the patient's disease state in a more accurate and complex way, thus improving the quality of preclinical research studies.

摘要

骨肉瘤是最常见的恶性骨肿瘤,主要影响儿童和青少年。对于这些年轻患者,骨肉瘤的当前治疗选择对日常生活造成了相当大的限制,具有较高的发病率和较低的生存率。尽管进行了持续的研究努力,但过去四十年中,无转移的初诊患者的 5 年生存率没有改变。目前仍然需要新的治疗方法,特别是有效的二线治疗方法。因此,迫切需要先进的临床前模型和药物测试平台,这些平台需要考虑到复杂的疾病特征、肿瘤的高度异质性以及与骨微环境的相互作用。在这篇综述中,我们全面介绍了用于骨肉瘤的最先进的组织工程和患者特异性模型。这些用于高级治疗试验的复杂平台旨在通过更准确和复杂的方式模拟患者的疾病状态,从而改善未来患者的治疗效果,提高临床前研究的质量。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b3de/11599440/2c7633608302/10555_2024_10218_Fig1_HTML.jpg

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验