title: Integrative Analysis of Cellular Morphometric Context Reveals Clinically Relevant Signatures in Lower Grade Glioma.
abstract: Integrative analysis based on quantitative representation of whole slide images (WSIs) in a large histology cohort may provide predictive models of clinical outcome. On one hand, the efficiency and effectiveness of such representation is hindered as a result of large technical variations (e.g., fixation, staining) and biological heterogeneities (e.g., cell type, cell state) that are always present in a large cohort. On the other hand, perceptual interpretation/validation of important multivariate phenotypic signatures are often difficult due to the loss of visual information during feature transformation in hyperspace. To address these issues, we propose a novel approach for integrative analysis based on cellular morphometric context, which is a robust representation of WSI, with the emphasis on tumor architecture and tumor heterogeneity, built upon cellular level morphometric features within the spatial pyramid matching (SPM) framework. The proposed approach is applied to The Cancer Genome Atlas (TCGA) lower grade glioma (LGG) cohort, where experimental results (i) reveal several clinically relevant cellular morphometric types, which enables both perceptual interpretation/validation and further investigation through gene set enrichment analysis; and (ii) indicate the significantly increased survival rates in one of the cellular morphometric context subtypes derived from the cellular morphometric context.
authors.affiliation: Lawrence Berkeley National Laboratory, Berkeley, California, U.S.A; Department of Electrical and Biomedical Engineering, University of Nevada, Reno, U.S.A.
authors.forename: Ju
authors.initials: J
authors.lastname: Han
authors.affiliation: Lawrence Berkeley National Laboratory, Berkeley, California, U.S.A; Department of Neurology, Taihe Hospital, Hubei University of Medicine, Hubei, China.
authors.forename: Yunfu
authors.initials: Y
authors.lastname: Wang
authors.affiliation: School of Information Technologies, University of Sydney, Sydney, NSW, Australia.
authors.forename: Weidong
authors.initials: W
authors.lastname: Cai
authors.affiliation: Center for Comparative Medicine, University of California, Davis, California, U.S.A.
authors.forename: Alexander
authors.initials: A
authors.lastname: Borowsky
authors.affiliation: Lawrence Berkeley National Laboratory, Berkeley, California, U.S.A; Department of Electrical and Biomedical Engineering, University of Nevada, Reno, U.S.A.
authors.forename: Bahram
authors.initials: B
authors.lastname: Parvin
authors.affiliation: Lawrence Berkeley National Laboratory, Berkeley, California, U.S.A; Department of Electrical and Biomedical Engineering, University of Nevada, Reno, U.S.A.
authors.forename: Hang
authors.initials: H
authors.lastname: Chang
keywords: cellular morphometric context; cellular morphometric type; consensus clustering; gene set enrichment analysis; lower grade glioma; spatial pyramid matching; survival analysis