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. 2025 Mar 13;25(1):455.
doi: 10.1186/s12885-025-13854-1.

Can circulating microRNAs predict colorectal cancer? Results from a nested case-control study of pre-diagnostic serum samples from two prospective biobanks

Eva Hofsli  1   2 , Pål Sætrom  1   3   4   5 , Eivind Ness-Jensen  6   7   8   9 , Helja-Marja Surcel  10   11 , Robin Mjelle  12   13
Affiliations

Can circulating microRNAs predict colorectal cancer? Results from a nested case-control study of pre-diagnostic serum samples from two prospective biobanks

Eva Hofsli et al. BMC Cancer. .

Abstract

Background: This study aimed to investigate the potential of circulating small RNAs (sRNAs) as predictive biomarkers for future colorectal cancer (CRC). The study analyzed serum samples from pre-diagnostic CRC patients in two prospective biobanks.

Methods: Serum samples from 142 pre-diagnostic CRC patients, from the Finnish Maternity Cohort (FMC) and The HUNT Study (HUNT2), were subjected to small RNA sequencing. The study compared sRNA expression in CRC cases with controls, considering diverse sRNA classes.

Results: Analysis revealed diverse miRNA expression patterns with notable variations in future metastatic cases. Specifically, miR-223-3p and miR-21-5p showed significant up-regulation in future metastatic cases in the FMC cohort. Consistent changes were observed across cohorts, with miR-584-5p, miR-30c-5p, miR-146a-5p, miR-10a-5p, and miR-1306-5p showing up-regulation in future metastatic cases.

Conclusions: The study identified potential serum miRNA biomarkers associated with metastatic CRC, though statistical significance varied. These findings contribute to the understanding of miRNA profiles in pre-diagnostic CRC patients, emphasizing the need for further exploration of non-invasive biomarkers in large prospective studies.

Keywords: Biomarkers; Colorectal Neoplasms; Diagnosis; MicroRNAs; Serum.

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Conflict of interest statement

Declarations. Ethics approval and consent to participate: The study was approved by “REK midt (REC central)”, Norwegian University of Science and Technology, Trondheim Norway, ( https://rekportalen.no/#omrek/REK ) with reference 2016/534. All participants provided informed consent as participants in the health surveys. Consent for publication: Not applicable. Competing interests: The authors declare no competing interests.

Figures

Fig. 1
Fig. 1
A Number of analyzed case and control samples stratified by TNM stage. Shown are the number of control samples, samples with localized disease (TNM I-II); metastatic disease (TNM III-IV); and samples with unknown stage. B Time from sample collection to cancer diagnosis (time-to-diagnosis) for all analyzed case samples, colored by TNM-stage. The mean time-to-diagnosis is indicated with a coloured vertical bar for each of the TNM-groups. C Principal component analysis of the miRNA expression data for the FMC and HUNT2 cohort, colored by sample group. D Significantly differentially expressed miRNAs in the FMC cohort. The boxplots compare the metastatic case samples to all controls and cases with localized disease. The p-values are the Benjamini-Hochberg-adjusted p-values from the limma-model in R
Fig. 2
Fig. 2
A-B MicroRNAs consistently up-regulated in metastatic cases vs all controls in the FMC and HUNT2 cohorts. Shown are the raw un-adjusted p-values (“p.raw”) and the Benjamini-Hochberg-adjusted p-values (“p.adj”) from the limma-model in R. C-D MicroRNAs consistently up-regulated in metastatic cases vs localized cases and all controls combined, in the FMC and HUNT2 cohorts. P-values as described in A) E) Expression of miR-1306-5p in all cases and all controls in FMC and HUNT2. P-values as described in A) F) Boxplot showing the expression of miRNAs within the miR-320 family in metastatic cases and all controls in the FMC- and HUNT2-cohorts. P-values as described in A)
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