Xusheng Wang

TL;DR: An integrative genomics framework for constructing a prognostic model for clear cell renal cell carcinoma is presented, extracting hundreds of cellular morphologic features from digitized whole-slide images and eigengenes from functional genomics data to predict patient outcome.

TL;DR: Wang et al. as discussed by the authors proposed a novel bioimage informatics pipeline for automatically characterizing the topological organization of different cell patterns in the tumor microenvironment, and applied this pipeline to the only publicly available large histopathology image dataset for a cohort of 190 patients with papillary renal cell carcinoma.

TL;DR: A novel bioimage informatics pipeline for automatically characterizing the topological organization of different cell patterns in the tumor microenvironment is proposed and can be integrated with genomic data in future studies to develop new integrative biomarkers.

TL;DR: In this article, the authors presented an integrative genomics framework for constructing a prognostic model for clear cell renal cell carcinoma, extracting hundreds of cellular morphologic features from digitized whole-slide images and eigengenes from functional genomics data to predict patient outcome.

TL;DR: In this paper , a new Ferroptosis-related genetic mutation risk (FerrGR) model was proposed to predict the prognosis of skin cutaneous melanoma (SKCM) patients.