Proteomic approaches in lung cancer biomarker development

Abstract

Biomarker discovery is one of the newly emerging innovations in the diagnosis and treatment of cancer and many other diseases. Many research groups and large pharmaceutical companies are actively engaged in searching for novel biomarkers for malignant diseases, which will make molecular analysis and monitoring of disease possible. Many technologies, including genomics, proteomics and metabolomics, are used to identify biomarkers. Among the many types of cancers and diseases, lung cancer – owing to the difficulty in diagnosing the disease at an early stage – urgently needs development of novel biomarkers as tools for early diagnosis and detection, as well as disease monitoring. Several DNA and protein biomarkers have been identified, but most previously discovered biomarkers are correlated with the general process of carcinogenesis and immune responses. Therefore, many of these biomarkers are found in other types of cancers, and thus are not specific to lung cancer. Therefore, novel lung cancer biomarker discovery is still needed, and among the many possible types of samples, blood is thought to be ideal for this discovery as it can be collected easily in a minimally invasive manner. Therefore, many studies are now being conducted to find lung cancer biomarkers in the blood. With advances in methods and technology, together with the considerable efforts to find early and novel diagnostic lung cancer biomarkers, many candidates will be discovered; leading to early diagnosis, detection, monitoring and efficient treatment of lung cancers.

Keywords::

• biomarkers
• diagnosis
• lung cancer
• proteomics
• serum/plasma

Acknowledgements

Due to space constraints, we apologize for the inability to cite all relevant references.

Financial & competing interests disclosure

This work was supported by Grant No. FPR08A2–120 of the 21C Frontier Functional Proteomics Project and Grant No. M10649000184–08N4900–18410, both from the Korean Ministry of Education, Science and Technology (MEST), and also by Grant No. RT104–01–01 from the Regional Technology Innovation Program of the Ministry of Knowledge Economy. 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.

No writing assistance was utilized in the production of this manuscript.