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Colon Cancer Biomarkers: Implications for Personalized Medicine

Overview
Journal J Pers Med
Date 2020 Oct 17
PMID 33066312
Citations 3
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Abstract

The heterogeneity of colon cancers and their reactions presents both a challenge and promise for personalized medicine. The challenge is to develop effective biologically personalized therapeutics guided by predictive and prognostic biomarkers. Presently, there are several classes of candidate biomarkers, including genomic probes, inhibitory RNAs, assays for immunity dysfunction and, not to be forgotten, specific histopathologic and histochemical features. To develop effective therapeutics, candidate biomarkers must be qualified and validated in comparable independent cohorts, no small undertaking. This process and subsequent deployment in clinical practice involves not only the strong association of the biomarker with the treatment but also careful attention to the prosaic aspects of representative tumor site selection, obtaining a fully adequate sample which is preserved and prepared to optimize high quality analysis. In the future, the clinical utility of biomarker analytical results will benefit from associated clinical and basic science data with the assistance of artificial intelligence techniques. By application of an individualized, selected suite of biomarkers, comprehensively interpreted, individualized, more effective and less toxic therapy for colon cancer will be enabled, thereby fulfilling the promise of personalized medicine.

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References
1.
Sanchez-Ibarra H, Jiang X, Gallegos-Gonzalez E, Cavazos-Gonzalez A, Chen Y, Morcos F . KRAS, NRAS, and BRAF mutation prevalence, clinicopathological association, and their application in a predictive model in Mexican patients with metastatic colorectal cancer: A retrospective cohort study. PLoS One. 2020; 15(7):e0235490. PMC: 7337295. DOI: 10.1371/journal.pone.0235490. View

2.
Kaz A, Wong C, Dzieciatkowski S, Luo Y, Schoen R, Grady W . Patterns of DNA methylation in the normal colon vary by anatomical location, gender, and age. Epigenetics. 2014; 9(4):492-502. PMC: 4121360. DOI: 10.4161/epi.27650. View

3.
Molnar B, Toth K, Bartak B, Tulassay Z . Plasma methylated septin 9: a colorectal cancer screening marker. Expert Rev Mol Diagn. 2014; 15(2):171-84. DOI: 10.1586/14737159.2015.975212. View

4.
Monzon F, Ogino S, Hammond M, Halling K, Bloom K, Nikiforova M . The role of KRAS mutation testing in the management of patients with metastatic colorectal cancer. Arch Pathol Lab Med. 2009; 133(10):1600-6. DOI: 10.5858/133.10.1600. View

5.
Jahanafrooz Z, Mosafer J, Akbari M, Hashemzaei M, Mokhtarzadeh A, Baradaran B . Colon cancer therapy by focusing on colon cancer stem cells and their tumor microenvironment. J Cell Physiol. 2019; 235(5):4153-4166. DOI: 10.1002/jcp.29337. View