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A review of predictive, prognostic and diagnostic biomarkers for non-small-cell lung cancer: towards personalised and targeted cancer therapy

Published online by Cambridge University Press:  25 November 2019

Ernest Osei Open the ORCID record for Ernest Osei [Opens in a new window] ,
Julia Lumini ,
Dinindu Gunasekara ,
Beverley Osei ,
Akua Asare  and
Raymond Laflamme
Ernest Osei*
Affiliation:
Grand River Regional Cancer Centre, Department of Medical Physics, Kitchener, ON, Canada Department of Physics and Astronomy Department of Systems Design Engineering, University of Waterloo, Waterloo, ON, Canada Department of Clinical Studies, Ontario Veterinary College, University of Guelph, Guelph, ON Canada
Julia Lumini
Affiliation:
Department of Biology, University of Waterloo, Waterloo, ON, Canada
Dinindu Gunasekara
Affiliation:
Department of Physics and Astronomy
Beverley Osei
Affiliation:
Department of Health Sciences, McMaster University, Hamilton, ON, Canada
Akua Asare
Affiliation:
Department of General Science, Brock University, St. Catherines, ON, Canada
Raymond Laflamme
Affiliation:
Institute for Quantum Computing, University of Waterloo, Waterloo, ON, Canada
*
Author for correspondence: Ernest Osei, Grand River Regional Cancer Centre, Department of Medical Physics, Kitchener, ON, Canada; Department of Physics and Astronomy, University of Waterloo, Department of Systems Design Engineering, University of Waterloo, Waterloo, ON, Canada; Department of Clinical Studies, Ontario Veterinary College, University of Guelph, Guelph, ON Canada. E-mail: [email protected]
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Abstract

Introduction:

Lung cancer has a high mortality rate mainly due to the lack of early detection or outward signs and symptoms, thereby often progressing to advanced stages (e.g., stage IV) before it is diagnosed. However, if lung cancers can be diagnosed at an early stage and also if clinicians can prospectively identify patients likely to respond to specific treatments, then there is a very high potential to increase patients’ survival. In recent years, several investigations have been conducted to identify cancer biomarkers for lung cancer risk assessment, early detection and diagnosis, the likelihood of identifying the group of patients who will benefit from a particular treatment and monitoring patient response to treatment.

Materials and Methods:

This paper reports on the review of 19 current clinical and emerging biomarkers used in risk assessment, screening for early detection and diagnosis and monitoring the response of treatment of non-small-cell lung cancers.

Conclusion:

The future holds promise for personalised and targeted medicine from prevention, diagnosis to treatment, which take into account individual patient’s variability, though it depends on the development of effective biomarkers interrogating the key aberrant pathways and potentially targetable with molecular targeted or immunologic therapies. Lung cancer biomarkers have the potential to guide clinical decision-making since they can potentially detect the disease early, measure the risk of developing the disease and the risk of progression, provide accurate information of patient response to a specific treatment and are capable of informing clinicians about the likely outcome of a cancer diagnosis independent of the treatment received. Moreover, lung cancer biomarkers are increasingly linked to specific molecular pathway deregulations and/or cancer pathogenesis and can be used to justify the application of certain therapeutic or interventional strategies.

Keywords

cancer therapychromosome aberrationgenes biomarkersnon-small-cell lung cancerprotein biomarkers
Type
Literature Review
Information
Journal of Radiotherapy in Practice , Volume 19 , Issue 4 , December 2020 , pp. 370 - 384
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Copyright
© Cambridge University Press 2019

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