Gallivanone Francesca, Bertoli Gloria, Porro Danilo
Institute of Molecular Bioimaging and Physiology (IBFM-CNR), Via F.lli Cervi 93, 20054 Milan, Italy.
Methods Protoc. 2022 Oct 3;5(5):78. doi: 10.3390/mps5050078.
Breast cancer (BC) is a heterogeneous disease, affecting millions of women every year. Early diagnosis is crucial to increasing survival. The clinical workup of BC diagnosis involves diagnostic imaging and bioptic characterization. In recent years, technical advances in image processing allowed for the application of advanced image analysis (radiomics) to clinical data. Furthermore, -omics technologies showed their potential in the characterization of BC. Combining information provided by radiomics with -omics data can be important to personalize diagnostic and therapeutic work up in a clinical context for the benefit of the patient. In this review, we analyzed the recent literature, highlighting innovative approaches to combine imaging and biochemical/biological data, with the aim of identifying recent advances in radiogenomics applied to BC. The results of radiogenomic studies are encouraging approaches in a clinical setting. Despite this, as radiogenomics is an emerging area, the optimal approach has to face technical limitations and needs to be applied to large cohorts including all the expression profiles currently available for BC subtypes (e.g., besides markers from transcriptomics, proteomics and miRNomics, also other non-coding RNA profiles).
乳腺癌(BC)是一种异质性疾病,每年影响数百万女性。早期诊断对于提高生存率至关重要。BC诊断的临床检查包括诊断性成像和活检特征分析。近年来,图像处理技术的进步使得先进的图像分析(放射组学)能够应用于临床数据。此外,“组学”技术在BC特征分析中显示出了潜力。将放射组学提供的信息与“组学”数据相结合,对于在临床环境中个性化诊断和治疗方案以造福患者可能具有重要意义。在本综述中,我们分析了近期文献,突出了将成像与生化/生物学数据相结合的创新方法,旨在确定应用于BC的放射基因组学的最新进展。放射基因组学研究的结果在临床环境中是令人鼓舞的方法。尽管如此,由于放射基因组学是一个新兴领域,最佳方法必须面对技术限制,并且需要应用于包括目前可用于BC亚型的所有表达谱的大型队列(例如,除了转录组学、蛋白质组学和微小RNA组学的标志物外,还有其他非编码RNA谱)。