Cancer Genetics and Epigenetics 2024, Vol.12, No.4, 194-209 http://medscipublisher.com/index.php/cge 207 The integration of non-invasive biomarkers into clinical practice can significantly improve colon cancer diagnosis and management. These biomarkers offer a less invasive alternative to traditional methods like colonoscopy, reducing patient discomfort and increasing compliance with screening programs. For example, serum-based miRNA signatures have demonstrated high diagnostic performance for early-stage colon cancer, providing a sensitive and specific method for early detection. Furthermore, these biomarkers can be used to monitor disease progression and response to treatment in real-time, allowing for more personalized and adaptive therapeutic strategies. Looking ahead, the future of non-invasive biomarker research in colon cancer is promising, with several key areas warranting further exploration. The integration of multi-omics data, combining genomic, proteomic, and metabolomic information, is expected to yield more comprehensive biomarker profiles, enhancing diagnostic precision and personalized treatment approaches. Advances in single-cell analysis will continue to uncover the heterogeneity within tumors, providing insights into the molecular mechanisms driving cancer progression and resistance to therapy. The role of artificial intelligence (AI) and machine learning (ML) in biomarker discovery and validation is expected to grow, enabling the analysis of large datasets and the identification of complex patterns that may be missed by traditional methods. These technologies can also aid in the development of predictive models for treatment response and disease progression, facilitating more personalized and effective treatment strategies. Ensuring the cost-effectiveness and accessibility of these advanced biomarker tests is crucial for their widespread adoption in clinical practice. Continued efforts to standardize assays, streamline regulatory approval processes, and conduct large-scale validation studies will be essential to translate these promising biomarkers from research to routine clinical use. Acknowledgments The authors would like to thank the two anonymous peer reviewers for their suggested revisions to the initial draft of this study. Funding This work was supported by mandatory project of Heilongjiang Provincial Education Department (Grant number 2022-KYYWF-0825). Conflict of Interest Disclosure The authors affirm that this research was conducted without any commercial or financial relationships that could be construed as a potential conflict of interest. References Baassiri A., Nassar F., Mukherji D., Shamseddine A., Nasr R., and Temraz S., 2020, Exosomal non coding RNA in liquid biopsies as a promising biomarker for colorectal cancer, International Journal of Molecular Sciences, 21(4): 1398. https://doi.org/10.3390/ijms21041398 Bhardwaj M., Weigl K., Tikk K., Benner A., Schrotz-King P., and Brenner H., 2020, Multiplex quantitation of 270 plasma protein markers to identify a signature for early detection of colorectal cancer, European Journal of Cancer, 127, 30-40. https://doi.org/10.1016/j.ejca.2019.11.021 Chen H., Qian J., Werner S., Ćuk K., Knebel P., and Brenner H., 2017, Development and validation of a panel of five proteins as blood biomarkers for early detection of colorectal cancer, Clinical Epidemiology, 517-526. https://doi.org/10.2147/CLEP.S144171 Chen M., Fan M., Yang J., and Lang J., 2020, Identification of potential oncogenic long non-coding RNA set as a biomarker associated with colon cancer prognosis, Journal of Environmental Pathology, Toxicology and Oncology, 39(1): 39-49. https://doi.org/10.1615/JEnvironPatholToxicolOncol.2020032351 Dalerba P., Sahoo D., Paik S., Guo X., Yothers G., Song N., and Clarke M., 2016, CDX2 as a prognostic biomarker in stage II and stage III colon cancer, New England Journal of Medicine, 374(3): 211-222. https://doi.org/10.1056/NEJMoa1506597 Das V., Kalita J., and Pal M., 2017, Predictive and prognostic biomarkers in colorectal cancer: A systematic review of recent advances and challenges, Biomedicine and Pharmacotherapy, 87: 8-19. https://doi.org/10.1016/j.biopha.2016.12.064 Deng H., Wang J., Li M., Tang R., Tang K., Su Y., Hou Y., and Zhang J., 2017, Long non-coding RNAs: new biomarkers for prognosis and diagnosis of colon cancer, Tumor Biology, 39(6): 1010428317706332. https://doi.org/10.1177/1010428317706332
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