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Harnessing citizen science through mobile phone technology to screen for immunohistochemical biomarkers in bladder cancer

Harnessing citizen science through mobile phone technology to screen for immunohistochemical biomarkers in bladder cancer
Harnessing citizen science through mobile phone technology to screen for immunohistochemical biomarkers in bladder cancer

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.

0007-0920
220-229
Smittenaar, Peter
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Walker, Alexandra K.
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McGill, Shaun
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Kartsonaki, Christiana
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Robinson-Vyas, Rupesh J.
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McQuillan, Janette P.
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Christie, Sarah
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Harris, Leslie
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Lawson, Jonathan
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Henderson, Elizabeth
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Howat, Will
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Hanby, Andrew
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Thomas, Gareth J.
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Bhattarai, Selina
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Browning, Lisa
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Kiltie, Anne E.
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Smittenaar, Peter
a625c8e0-3c59-4951-8d6e-ce822c25a5bb
Walker, Alexandra K.
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McGill, Shaun
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Kartsonaki, Christiana
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Robinson-Vyas, Rupesh J.
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McQuillan, Janette P.
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Christie, Sarah
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Harris, Leslie
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Lawson, Jonathan
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Henderson, Elizabeth
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Howat, Will
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Hanby, Andrew
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Thomas, Gareth J.
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Bhattarai, Selina
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Browning, Lisa
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Kiltie, Anne E.
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Smittenaar, Peter, Walker, Alexandra K., McGill, Shaun, Kartsonaki, Christiana, Robinson-Vyas, Rupesh J., McQuillan, Janette P., Christie, Sarah, Harris, Leslie, Lawson, Jonathan, Henderson, Elizabeth, Howat, Will, Hanby, Andrew, Thomas, Gareth J., Bhattarai, Selina, Browning, Lisa and Kiltie, Anne E. (2018) Harnessing citizen science through mobile phone technology to screen for immunohistochemical biomarkers in bladder cancer. British Journal of Cancer, 119 (2), 220-229. (doi:10.1038/s41416-018-0156-0).

Record type: Article

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.

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Accepted/In Press date: 31 May 2018
e-pub ahead of print date: 11 July 2018
Published date: 17 July 2018

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Local EPrints ID: 422594
URI: https://eprints.soton.ac.uk/id/eprint/422594
ISSN: 0007-0920
PURE UUID: 173e826d-a26f-4e8a-99a5-745cb4e60cb9

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Date deposited: 26 Jul 2018 16:30
Last modified: 13 Mar 2019 18:13

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Contributors

Author: Peter Smittenaar
Author: Alexandra K. Walker
Author: Shaun McGill
Author: Christiana Kartsonaki
Author: Rupesh J. Robinson-Vyas
Author: Janette P. McQuillan
Author: Sarah Christie
Author: Leslie Harris
Author: Jonathan Lawson
Author: Elizabeth Henderson
Author: Will Howat
Author: Andrew Hanby
Author: Selina Bhattarai
Author: Lisa Browning
Author: Anne E. Kiltie

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