Stool- and Blood-Associated Colorectal Cancer Biomarkers: A Systematic Review.

Background/Objectives: Colorectal cancer (CRC) is a major contributor to cancer-related deaths worldwide. While existing screening tools are effective, their high cost and limited availability restrict widespread adoption, particularly in low- and middle-income settings. The identification of affordable, non-invasive biomarkers is therefore critical to improve early CRC detection and survival outcomes. Methods: A systematic literature search was performed through PubMed, ScienceDirect, Medline, ISI Web of Knowledge, and Google Scholar to identify studies reporting stool- and blood-based biomarkers for CRC detection. Data were extracted using a standardized template, including study details, specimen type, detection method, and diagnostic performance parameters such as sensitivity and specificity. Results: DNA methylation biomarkers demonstrated high diagnostic potential. Syndecan 2 (SDC2) and Short Stature Homeobox 2 (SHOX2) achieved a combined stool sensitivity of 91.35%. Other methylation markers, including NDRG4, SEPT9, and BCAT1, showed a composite sensitivity of 82.7%. Plasma-based methylation markers such as GATA5, FOXE1, and SYNE1 reported sensitivities ranging from 18-47% and specificities of 93-99%. Hypermethylation of SFRP2 and WIF-1 achieved 81.3% sensitivity in CRC and precursor lesions. Matrix metalloproteinases (MMP-2 and MMP-9) were elevated in CRC patients, with stool MMP-9 yielding 72.2% sensitivity and 95% specificity. A stool gene panel (UBE2N, IMPDH1, DYNC1LI1, HRASLS2) reached 96.6% sensitivity and 89.7% specificity, while a methylation-based panel (ALX4, BMP3, NPTX2, RARB, SDC2, SEPT9, VIM) achieved 90.7% sensitivity. MicroRNAs (miR-21, miR-92a, miR-223, miR-182) showed excellent diagnostic performance, with sensitivities exceeding 96% and specificities above 75%. Conclusions: DNA methylation and microRNA biomarkers hold strong promises for non-invasive CRC screening. Multi-marker panels demonstrate superior diagnostic accuracy and may provide a cost-effective, scalable approach for early CRC detection in resource-limited settings.