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Crowdsourcing the General Public for Large Scale Molecular Pathology Studies in Cancer.

Abstract：

BACKGROUND:Citizen science, scientific research conducted by non-specialists, has the potential to facilitate biomedical research using available large-scale data, however validating the results is challenging. The Cell Slider is a citizen science project that intends to share images from tumors with the general public, enabling them to score tumor markers independently through an internet-based interface. METHODS:From October 2012 to June 2014, 98,293 Citizen Scientists accessed the Cell Slider web page and scored 180,172 sub-images derived from images of 12,326 tissue microarray cores labeled for estrogen receptor (ER). We evaluated the accuracy of Citizen Scientist's ER classification, and the association between ER status and prognosis by comparing their test performance against trained pathologists. FINDINGS:The area under ROC curve was 0.95 (95% CI 0.94 to 0.96) for cancer cell identification and 0.97 (95% CI 0.96 to 0.97) for ER status. ER positive tumors scored by Citizen Scientists were associated with survival in a similar way to that scored by trained pathologists. Survival probability at 15 years were 0.78 (95% CI 0.76 to 0.80) for ER-positive and 0.72 (95% CI 0.68 to 0.77) for ER-negative tumors based on Citizen Scientists classification. Based on pathologist classification, survival probability was 0.79 (95% CI 0.77 to 0.81) for ER-positive and 0.71 (95% CI 0.67 to 0.74) for ER-negative tumors. The hazard ratio for death was 0.26 (95% CI 0.18 to 0.37) at diagnosis and became greater than one after 6.5 years of follow-up for ER scored by Citizen Scientists, and 0.24 (95% CI 0.18 to 0.33) at diagnosis increasing thereafter to one after 6.7 (95% CI 4.1 to 10.9) years of follow-up for ER scored by pathologists. INTERPRETATION:Crowdsourcing of the general public to classify cancer pathology data for research is viable, engages the public and provides accurate ER data. Crowdsourced classification of research data may offer a valid solution to problems of throughput requiring human input.

journal_name

EBioMedicine

journal_title

EBioMedicine

authors

Candido Dos Reis FJ,Lynn S,Ali HR,Eccles D,Hanby A,Provenzano E,Caldas C,Howat WJ,McDuffus LA,Liu B,Daley F,Coulson P,Vyas RJ,Harris LM,Owens JM,Carton AF,McQuillan JP,Paterson AM,Hirji Z,Christie SK,Holmes AR,S

doi

10.1016/j.ebiom.2015.05.009

subject

Has Abstract

pub_date

2015-05-09 00:00:00

pages

681-9

issue

issn

2352-3964

pii

S2352-3964(15)30016-5

journal_volume

pub_type

杂志文章

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Crowdsourcing the General Public for Large Scale Molecular Pathology Studies in Cancer.