Smittenaar, P, Walker, AK, McGill, S et al. (13 more authors) (2018) Harnessing citizen science through mobile phone technology to screen for immunohistochemical biomarkers in bladder cancer. British Journal of Cancer, 119 (2). pp. 220-229. ISSN 0007-0920
Abstract
Background: Immunohistochemistry (IHC) is often used in personalisation of cancer treatments. Analysis of large data sets to uncover predictive biomarkers by specialists can be enormously time-consuming. Here we investigated crowdsourcing as a means of reliably analysing immunostained cancer samples to discover biomarkers predictive of cancer survival.
Methods: We crowdsourced the analysis of bladder cancer TMA core samples through the smartphone app ‘Reverse the Odds’. Scores from members of the public were pooled and compared to a gold standard set scored by appropriate specialists. We also used crowdsourced scores to assess associations with disease-specific survival.
Results: Data were collected over 721 days, with 4,744,339 classifications performed. The average time per classification was approximately 15 s, with approximately 20,000 h total non-gaming time contributed. The correlation between crowdsourced and expert H-scores (staining intensity × proportion) varied from 0.65 to 0.92 across the markers tested, with six of 10 correlation coefficients at least 0.80. At least two markers (MRE11 and CK20) were significantly associated with survival in patients with bladder cancer, and a further three markers showed results warranting expert follow-up.
Conclusions: Crowdsourcing through a smartphone app has the potential to accurately screen IHC data and greatly increase the speed of biomarker discovery.
Metadata
Item Type: | Article |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © The Author(s) 2018. This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/. |
Dates: |
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Institution: | The University of Leeds |
Academic Units: | The University of Leeds > Faculty of Medicine and Health (Leeds) > School of Medicine (Leeds) > Leeds Institute of Cancer and Pathology (LICAP) > Pathology & Tumour Biology (Leeds) |
Depositing User: | Symplectic Publications |
Date Deposited: | 19 Jun 2018 14:52 |
Last Modified: | 22 Aug 2020 17:14 |
Status: | Published |
Publisher: | Cancer Research UK |
Identification Number: | 10.1038/s41416-018-0156-0 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:132163 |