Background:
Precision medicine puts forward customized healthcare for cancer
patients. An important way to accomplish this task is to stratify patients into those who may
respond to a treatment and those who may not. For this purpose, diagnostic and prognostic
biomarkers have been pursued.
Objective:
This review focuses on novel approaches and concepts of exploring biomarker discovery
under the circumstances that technologies are developed, and data are accumulated for
precision medicine.
Results:
The traditional mechanism-driven functional biomarkers have the advantage of actionable
insights, while data-driven computational biomarkers can fulfill more needs, especially
with tremendous data on the molecules of different layers (e.g. genetic mutation,
mRNA, protein etc.) which are accumulated based on a plenty of technologies. Besides, the
technology-driven liquid biopsy biomarker is very promising to improve patients’ survival.
The developments of biomarker discovery on these aspects are promoting the understanding
of cancer, helping the stratification of patients and improving patients’ survival.
Conclusion:
Current developments on mechanisms-, data- and technology-driven biomarker
discovery are achieving the aim of precision medicine and promoting the clinical application
of biomarkers. Meanwhile, the complexity of cancer requires more effective biomarkers,
which could be accomplished by a comprehensive integration of multiple types of biomarkers
together with a deep understanding of cancer.
A systematic review of the clinical application of data-driven population segmentation analysis
