Faculty, Staff and Student Publications
Publication Date
4-24-2023
Journal
International Journal of Molecular Sciences
Abstract
The identification of biomarkers plays a crucial role in personalized medicine, both in the clinical and research settings. However, the contrast between predictive and prognostic biomarkers can be challenging due to the overlap between the two. A prognostic biomarker predicts the future outcome of cancer, regardless of treatment, and a predictive biomarker predicts the effectiveness of a therapeutic intervention. Misclassifying a prognostic biomarker as predictive (or vice versa) can have serious financial and personal consequences for patients. To address this issue, various statistical and machine learning approaches have been developed. The aim of this study is to present an in-depth analysis of recent advancements, trends, challenges, and future prospects in biomarker identification. A systematic search was conducted using PubMed to identify relevant studies published between 2017 and 2023. The selected studies were analyzed to better understand the concept of biomarker identification, evaluate machine learning methods, assess the level of research activity, and highlight the application of these methods in cancer research and treatment. Furthermore, existing obstacles and concerns are discussed to identify prospective research areas. We believe that this review will serve as a valuable resource for researchers, providing insights into the methods and approaches used in biomarker discovery and identifying future research opportunities.
Keywords
Humans, Biomarkers, Tumor, Prognosis, Prospective Studies, Biomarkers, Precision Medicine, Machine Learning, Neoplasms, biomarker discovery, deep learning, feature selection, machine learning, personalized medicine, predictive biomarker, prognostic biomarker, subgroup identification
DOI
10.3390/ijms24097781
PMID
37175487
PMCID
PMC10178491
PubMedCentral® Posted Date
4-24-2023
PubMedCentral® Full Text Version
Post-print
Published Open-Access
yes
Included in
Bioinformatics Commons, Biomedical Informatics Commons, Genetic Phenomena Commons, Medical Genetics Commons, Oncology Commons