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. Author manuscript; available in PMC: 2020 Jun 1.
Published in final edited form as: Cancer Res. 2017 Nov 1;77(21):e91–e100. doi: 10.1158/0008-5472.CAN-17-0313

Figure 2.

Figure 2.

Image features and eigengenes predict the survival outcomes of ccRCC patients. Both image features (A and B) and eigengenes (C) identify poor-prognosis subtypes with high percentage of stroma. Gene module 2 is enriched with extracellular matrix genes. RMean_bin10 (D) and eigengene3 (E) are the most significant variables for image features and eigengenes, respectively. Integrative analysis of histopathological images and genomic data using lasso-Cox can significantly improve the prognosis prediction power (F).