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. 2021 Jan 20;10:586292. doi: 10.3389/fonc.2020.586292

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Copyright © 2021 Zormpas-Petridis, Noguera, Ivankovic, Roxanis, Jamin and Yuan

This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

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Quantification of clinically relevant features with SuperHistopath. (A, B) show associations between survival outcomes and SuperHistopath-defined risk groups in the Cancer Genome Atlas (TCGA) cohorts of patients with melanoma. (A) Kaplan-Meier Survival curves for patients in the high-risk group (blue) and low risk group (red) classified by stromal cells ratio derived from SuperHistopath and (B) Kaplan-Meier Survival curves for patients in the high-risk group (blue) and low risk group (red) classified by immune infiltrate based on lymphocytes cluster ratio derived from SuperHistopath. (C, D) show the SuperHistopath-based quantification of tumor phenotype in genetically-engineered mouse model of high-risk neuroblastoma. (C) Representative SuperHistopath-segmented whole-slide images (5x) and pie chart showing the Super-CNN quantified mean composition of the tumors arising in Th-MYCN (n=6) and Th-ALK^F1174L/MYCN (n=7) mouse models of high-risk neuroblastoma. Note the marked difference of phenotype induced by the expression of the ALK^F1174L mutation characterized by (D) a significantly increased neuroblastoma differentiation neuroblasts and the total abrogation of the characteristic hemorrhagic phenotype of Th-MYCN tumors.