Recent insights into human bronchial proteomics – how are we progressing and what is next?

ABSTRACT

Introduction: The human respiratory system is highly prone to diseases and complications. Many lung diseases, including lung cancer (LC), tuberculosis (TB), and chronic obstructive pulmonary disease (COPD) have been among the most common causes of death worldwide. Cystic fibrosis (CF), the most common genetic disease in Caucasians, has adverse impacts on the lungs. Bronchial proteomics plays a significant role in understanding the underlying mechanisms and pathogenicity of lung diseases and provides insights for biomarker and therapeutic target discoveries.

Areas covered: We overview the recent achievements and discoveries in human bronchial proteomics by outlining how some of the different proteomic techniques/strategies are developed and applied in LC, TB, COPD, and CF. Also, the future roles of bronchial proteomics in predictive proteomics and precision medicine are discussed.

Expert commentary: Much progress has been made in bronchial proteomics. Owing to the advances in proteomics, we now have better ability to isolate proteins from desired cellular compartments, greater protein separation methods, more powerful protein detection technologies, and more sophisticated bioinformatic techniques. These all contributed to our further understanding of lung diseases and for biomarker and therapeutic target discoveries.

KEYWORDS:

• Lung cancer
• COPD
• tuberculosis
• cystic fibrosis
• mass spectrometry
• predictive proteomics
• precision medicine

Acknowledgements

We would like to thank members of the Lau And Xu laboratory and James E. Young for critical reading of this manuscript. The authors have declared no conflict of interest.

Declaration of interest

The authors have no other relevant affiliations or financial involvement with any organization or entity with a financial interest in or financial conflict with the subject matter or materials discussed in the manuscript apart from those disclosed.

Additional information

Funding

This work was supported by the grants from the National Natural Science Foundation of China (Nos. 31771582 and 31271445), the Science and Technology Planning Project of Guangdong Province of China (No. 2016A020215144), the Guangdong Natural Science Foundation of China (Nos. 2017A030313131 and S2012030006289), the ‘Thousand, Hundred, and Ten’ project of the Department of Education of Guangdong Province of China (No. 124), the Department of Education, Guangdong Government under the Top-tier University Development Scheme for Research and Control of Infectious Diseases, the Colleges and Universities Innovation Project of Guangdong Province of China (Nos. 2016KTSCX041 and 2016KTSCX042), and the ‘Yang Fan’ Project of Guangdong Province of China (Andy T. Y. Lau-2016; Yan-Ming Xu-2015).