School of Biomedical Engineering, Medical School, Shenzhen University, Shenzhen 518000, China.
Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, SE 17177 Stockholm, Sweden.
Sensors (Basel). 2023 Jan 28;23(3):1432. doi: 10.3390/s23031432.
The expression abundance of transcripts in nondiseased breast tissue varies among individuals. The association study of genotypes and imaging phenotypes may help us to understand this individual variation. Since existing reports mainly focus on tumors or lesion areas, the heterogeneity of pathological image features and their correlations with RNA expression profiles for nondiseased tissue are not clear. The aim of this study is to discover the association between the nucleus features and the transcriptome-wide RNAs. We analyzed both microscopic histology images and RNA-sequencing data of 456 breast tissues from the Genotype-Tissue Expression (GTEx) project and constructed an automatic computational framework. We classified all samples into four clusters based on their nucleus morphological features and discovered feature-specific gene sets. The biological pathway analysis was performed on each gene set. The proposed framework evaluates the morphological characteristics of the cell nucleus quantitatively and identifies the associated genes. We found image features that capture population variation in breast tissue associated with RNA expressions, suggesting that the variation in expression pattern affects population variation in the morphological traits of breast tissue. This study provides a comprehensive transcriptome-wide view of imaging-feature-specific RNA expression for healthy breast tissue. Such a framework could also be used for understanding the connection between RNA expression and morphology in other tissues and organs. Pathway analysis indicated that the gene sets we identified were involved in specific biological processes, such as immune processes.
非病变乳腺组织中转录本的表达丰度在个体间存在差异。基因型与影像学表型的关联研究可能有助于我们理解这种个体差异。由于现有报道主要集中在肿瘤或病变区域，因此非病变组织的病理图像特征的异质性及其与 RNA 表达谱的相关性尚不清楚。本研究旨在发现核特征与全转录组 RNA 之间的关联。我们分析了来自 Genotype-Tissue Expression (GTEx) 项目的 456 个乳腺组织的微观组织学图像和 RNA 测序数据，并构建了一个自动计算框架。我们根据细胞核形态特征将所有样本分为四个簇，并发现了具有特征的基因集。对每个基因集进行了生物通路分析。该框架定量评估细胞核的形态特征，并识别相关基因。我们发现了可以捕获乳腺组织中与 RNA 表达相关的群体变异的图像特征，这表明表达模式的变化会影响乳腺组织形态特征的群体变异。本研究为健康乳腺组织的影像学特征特异性 RNA 表达提供了全面的全转录组视角。这种框架也可用于理解其他组织和器官中 RNA 表达与形态之间的联系。通路分析表明，我们鉴定的基因集参与了特定的生物学过程，如免疫过程。
