Advanced tumours are often heterogeneous, consisting of subclones with various genetic alterations and functional roles. The precise molecular features that characterize the contributions of multiscale intratumour heterogeneity to malignant progression, metastasis, and poor survival are largely unknown. Here, we address these challenges in breast cancer by defining the landscape of heterogeneous tumour subclones and their biological functions using radiogenomic signatures. Molecular heterogeneity is identified by a fully unsupervised deconvolution of gene expression data. Relative prevalence of two subclones associated with cell cycle and primary immunodeficiency pathways identifies patients with significantly different survival outcomes. Radiogenomic signatures of imaging scale heterogeneity are extracted and used to classify patients into groups with distinct subclone compositions. Prognostic value is confirmed by survival analysis accounting for clinical variables. These findings provide insight into how a radiogenomic analysis can identify the biological activities of specific subclones that predict prognosis in a noninvasive and clinically relevant manner.

晚期肿瘤通常是异质的，由具有各种遗传改变和功能作用的亚克隆组成。表征多尺度肿瘤内异质性对恶性进展、转移和不良生存的贡献的精确分子特征在很大程度上是未知的。在这里，我们通过使用放射基因组学特征定义异质肿瘤亚克隆的景观及其生物学功能来解决乳腺癌中的这些挑战。分子异质性通过基因表达数据的完全无监督解卷积来确定。与细胞周期和主要免疫缺陷途径相关的两个亚克隆的相对流行率确定了具有显着不同生存结果的患者。提取成像规模异质性的放射基因组特征，并用于将患者分为具有不同亚克隆组成的组。通过考虑临床变量的生存分析确认预后价值。这些发现提供了对放射基因组分析如何识别特定亚克隆的生物学活性的见解，这些亚克隆以非侵入性和临床相关的方式预测预后。