Department of Dermatology, FAU Erlangen-Nürnberg, Universitätsklinikum Erlangen, Comprehensive Cancer Center Erlangen and Deutsches Zentrum Immuntherapie (DZI), 91054 Erlangen, Germany.
Department of Systems Biology and Bioinformatics, Institute of Computer Science, University of Rostock, Rostock 18051, Germany.
Brief Bioinform. 2022 Nov 19;23(6). doi: 10.1093/bib/bbac433.
We live in an unprecedented time in oncology. We have accumulated samples and cases in cohorts larger and more complex than ever before. New technologies are available for quantifying solid or liquid samples at the molecular level. At the same time, we are now equipped with the computational power necessary to handle this enormous amount of quantitative data. Computational models are widely used helping us to substantiate and interpret data. Under the label of systems and precision medicine, we are putting all these developments together to improve and personalize the therapy of cancer. In this review, we use melanoma as a paradigm to present the successful application of these technologies but also to discuss possible future developments in patient care linked to them. Melanoma is a paradigmatic case for disruptive improvements in therapies, with a considerable number of metastatic melanoma patients benefiting from novel therapies. Nevertheless, a large proportion of patients does not respond to therapy or suffers from adverse events. Melanoma is an ideal case study to deploy advanced technologies not only due to the medical need but also to some intrinsic features of melanoma as a disease and the skin as an organ. From the perspective of data acquisition, the skin is the ideal organ due to its accessibility and suitability for many kinds of advanced imaging techniques. We put special emphasis on the necessity of computational strategies to integrate multiple sources of quantitative data describing the tumour at different scales and levels.
我们生活在肿瘤学的空前时代。我们积累的样本和病例比以往任何时候都更大、更复杂。新技术可用于在分子水平上定量分析固体或液体样本。与此同时，我们现在拥有处理这些大量定量数据所需的计算能力。计算模型被广泛用于帮助我们证实和解释数据。在系统和精准医学的标签下，我们将所有这些发展结合起来，以改善和个性化癌症治疗。在这篇综述中，我们使用黑色素瘤作为范例，展示了这些技术的成功应用，但也讨论了与之相关的患者护理的可能未来发展。黑色素瘤是治疗方法具有颠覆性改进的典范，相当数量的转移性黑色素瘤患者受益于新型疗法。然而，很大一部分患者对治疗没有反应或遭受不良反应。黑色素瘤是部署先进技术的理想案例研究，不仅因为有医疗需求，还因为黑色素瘤作为一种疾病和皮肤作为一种器官的一些内在特征。从数据采集的角度来看，皮肤是理想的器官，因为它易于接近，适合多种先进的成像技术。我们特别强调了计算策略的必要性，以整合描述肿瘤在不同尺度和水平的多种定量数据来源。
