Volume 19, Issue 21-22 1900109
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Addressing the Challenges of High-Throughput Cancer Tissue Proteomics for Clinical Application: ProCan

Brett Tully

Corresponding Author

Brett Tully

ProCan, Children's Medical Research Institute, Faculty of Medicine and Health, The University of Sydney, Westmead, NSW, 2145 Australia

B. Tully (E-mail: [email protected])Search for more papers by this author
Rosemary L. Balleine

Rosemary L. Balleine

ProCan, Children's Medical Research Institute, Faculty of Medicine and Health, The University of Sydney, Westmead, NSW, 2145 Australia

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Peter G. Hains

Peter G. Hains

ProCan, Children's Medical Research Institute, Faculty of Medicine and Health, The University of Sydney, Westmead, NSW, 2145 Australia

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Qing Zhong

Qing Zhong

ProCan, Children's Medical Research Institute, Faculty of Medicine and Health, The University of Sydney, Westmead, NSW, 2145 Australia

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Roger R. Reddel

Roger R. Reddel

ProCan, Children's Medical Research Institute, Faculty of Medicine and Health, The University of Sydney, Westmead, NSW, 2145 Australia

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Phillip J. Robinson

Phillip J. Robinson

ProCan, Children's Medical Research Institute, Faculty of Medicine and Health, The University of Sydney, Westmead, NSW, 2145 Australia

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First published: 18 July 2019
Citations: 22

Abstract

The cancer tissue proteome has enormous potential as a source of novel predictive biomarkers in oncology. Progress in the development of mass spectrometry (MS)-based tissue proteomics now presents an opportunity to exploit this by applying the strategies of comprehensive molecular profiling and big-data analytics that are refined in other fields of ‘omics research. ProCan (ProCan is a registered trademark) is a program aiming to generate high-quality tissue proteomic data across a broad spectrum of cancer types. It is based on data-independent acquisition–MS proteomic analysis of annotated tissue samples sourced through collaboration with expert clinical and cancer research groups. The practical requirements of a high-throughput translational research program have shaped the approach that ProCan is taking to address challenges in study design, sample preparation, raw data acquisition, and data analysis. The ultimate goal is to establish a large proteomics knowledge-base that, in combination with other cancer ‘omics data, will accelerate cancer research.

Conflict of Interest

The authors declare no conflict of interest.