Spatially Structured Regression for Non-conformable Spaces: Integrating Pathology Imaging and Genomics Data in Cancer

The spatial composition and cellular heterogeneity of the tumor microenvironment plays a critical role in cancer development and progression. High-definition pathology imaging of tumor biopsies provide a high-resolution view of the spatial organization of different types of cells. This allows for systematic assessment of intra- and inter-patient spatial cellular interactions and heterogeneity by integrating accompanying patient-level genomics data. However, joint modeling across tumor biopsies presents unique challenges due to non-conformability (lack of a common spatial domain across biopsies) as well as high-dimensionality. To address this problem, we propose the Dual random effect and main effect selection model for Spatially structured regression model (DreameSpase). DreameSpase employs a Bayesian variable selection framework that facilitates the assessment of spatial heterogeneity with respect to covariates both within (through fixed effects) and between spaces (through spatial random effects) for non-conformable spatial domains. We demonstrate the efficacy of DreameSpase via simulations and integrative analyses of pathology imaging and gene expression data obtained from $335$ melanoma biopsies. Our findings confirm several existing relationships, e.g. neutrophil genes being associated with both inter- and intra-patient spatial heterogeneity, as well as discovering novel associations. We also provide freely available and computationally efficient software for implementing DreameSpase.

肿瘤微环境的空间组成和细胞异质性在癌症的发生和发展中起着关键作用。肿瘤活检的高清病理成像为不同类型细胞的空间组织提供了高分辨率的视角。通过整合伴随的患者层面的基因组数据，这使得能够对患者内和患者间的空间细胞相互作用及异质性进行系统评估。然而，由于不一致性（活检之间缺乏共同的空间域）以及高维度，跨肿瘤活检的联合建模带来了独特的挑战。为了解决这个问题，我们提出了用于空间结构回归模型的双重随机效应和主效应选择模型（DreameSpase）。DreameSpase采用贝叶斯变量选择框架，该框架有助于针对不一致空间域，就协变量在空间内（通过固定效应）和空间之间（通过空间随机效应）评估空间异质性。我们通过模拟以及对从335例黑色素瘤活检中获得的病理成像和基因表达数据的综合分析，证明了DreameSpase的有效性。我们的研究结果证实了一些现有的关系，例如中性粒细胞基因与患者间和患者内的空间异质性均相关，同时还发现了新的关联。我们还提供了可免费获取且计算高效的用于实现DreameSpase的软件。