Identification of the Minimum Combination of Serum microRNAs to Predict the Recurrence of Colorectal Cancer Cases

Ann Surg Oncol. 2023 Jan;30(1):233-243. doi: 10.1245/s10434-022-12355-w. Epub 2022 Sep 29.

Abstract

Background: Serum microRNAs (miRNAs) have been recognized as potential stable biomarkers for various types of cancer. Considering the clinical applications, there are certain critical requirements, such as minimizing the number of miRNAs, reproducibility in a longitudinal clinical course, and superiority to conventional tumor markers, such as carcinoembryonic antigen (CEA) and carbohydrate antigen 19-9. This study aimed to identify serum miRNAs that indicate the recurrence of colorectal cancer (CRC), surpassing inter-tumor heterogeneity.

Methods: We conducted an analysis of 434 serum samples from 91 patients with CRC and 71 healthy subjects. miRNAs were obtained from Toray Co., Ltd, and miRNA profiles were analyzed using a three-step approach. miRNAs that were highly expressed in patients with CRC than in the healthy controls in the screening phase, and those that were highly expressed in the preoperative samples than in the 1-month postoperative samples in the discovery phase, were extracted. In the validation phase, the extracted miRNAs were evaluated in 323 perioperative samples, in chronological order.

Results: A total of 12 miRNAs (miR-25-3p, miR-451a, miR-1246, miR-1268b, miR-2392, miR-4480, miR-4648, miR-4732-5p, miR-4736, miR-6131, miR-6776-5p, and miR-6851-5p) were significantly concordant with the clinical findings of tumor recurrence, however their ability to function as biomarkers was comparable with CEA. In contrast, the combination of miR-1246, miR-1268b, and miR-4648 demonstrated a higher area under the curve (AUC) than CEA. These three miRNAs were upregulated in primary CRC tissues.

Conclusion: We identified ideal combinatorial miRNAs to predict CRC recurrence.

MeSH terms

  • Colorectal Neoplasms* / genetics
  • Colorectal Neoplasms* / surgery
  • Humans
  • MicroRNAs* / genetics
  • Reproducibility of Results

Substances

  • MicroRNAs