An Integrative Approach for In Silico Glioma Research
An Integrative Approach for In Silico Glioma Research
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DOI：
10.1109/tbme.2010.2060338
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发表时间：
2010-10-01
影响因子：
4.6
通讯作者：
Saltz, Joel H.
中科院分区：
文献类型：
--
作者：
Cooper, Lee A. D.;Kong, Jun;Saltz, Joel H.
成像和基因组数据的整合对于更好地理解疾病至关重要。大型公共数据集，如癌症基因组图谱，提供了一个独特的机会来整合这些互补的数据类型，用于计算机科学研究。在这封信中，我们专注于病理学图像分析方面，并说明了与分析和整合大规模图像数据集与分子表征相关的挑战。我们提出了一个弥漫性胶质瘤脑肿瘤的例子研究，其中8100万个细胞核的形态学分析与胶质母细胞瘤肿瘤的临床相关转录组学和基因组学特征相结合。初步结果表明，结合形态和分子表征在硅片研究的潜力。
The integration of imaging and genomic data is critical to forming a better understanding of disease. Large public datasets, such as The Cancer Genome Atlas, present a unique opportunity to integrate these complementary data types for in silico scientific research. In this letter, we focus on the aspect of pathology image analysis and illustrate the challenges associated with analyzing and integrating large-scale image datasets with molecular characterizations. We present an example study of diffuse glioma brain tumors, where the morphometric analysis of 81 million nuclei is integrated with clinically relevant transcriptomic and genomic characterizations of glioblastoma tumors. The preliminary results demonstrate the potential of combining morphometric and molecular characterizations for in silico research.