Skip to main content
Dryad

Data from: Reinterpretation of prostate cancer pathology by Appl1, Sortilin and Syndecan-1 biomarkers

Logan, Jessica1; Martini, Carmela1; Sorvina, Alexandra1; Johnson, Ian1; Brooks, Robert1; Caruso, Maria1; Chelsea, Huzzell1; Courtney, Moore1; Karageorgos, Litsa1; Butler, Lisa2; Prerna, Tewari3; Prabhakaran, Sarita4; Hickey, Shane1; Klebe, Sonja4; Samaratunga, Hemamali5; Delahunt, Brett6; Moretti, Kim2; O'Leary, John3; Brooks, Doug1; Ung, Benjamin1

Published Jul 18, 2024 on Dryad. https://doi.org/10.5061/dryad.v9s4mw749

Data files

Jul 18, 2024 version files 269.61 GB

Select up to 11 GB of files for download

Abstract

The diagnosis of prostate cancer using histopathology is reliant on the accurate interpretation of stained or labelled tissue sections. Current standards rely on assessment following Haematoxylin and Eosin (H&E) staining, which is often difficult to interpret and introduces inter-observer variability. Here, we present a digital pathology atlas for prostate cancer tissue, using micrographs of both H&E and our novel set of three biomarkers as an interactive tool, where clinicians and scientists can explore high resolution histopathology from various case studies. The digital pathology prostate cancer atlas when used in conjunction with the biomarkers, will greatly assist pathologists to accurately grade prostate cancer tissue samples.

This repository also contains the original image dataset used to generate the case studies for the digital pathology atlas. The data consist of a benign case and cases of ISUP grades from 1 to 5, where initial grading was performed on the hematoxylin and eosin (H&E) stained tissue section, along with three serial sections from the same tissue block, labeled with our biomarker panel - Appl1, Sortilin, and Syndecan-1. This biomarker panel was then used to assist the initial H&E grading, providing a more accurate diagnosis and prognosis from the retrospective patient dataset.