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Cancer‐specific risk prediction with a serum microRNA signature.
- Source :
- Cancer Science; Jun2024, Vol. 115 Issue 6, p2049-2058, 10p
- Publication Year :
- 2024
-
Abstract
- We recently derived and validated a serum‐based microRNA risk score (miR‐score) that predicted colorectal cancer (CRC) occurrence with very high accuracy within 14 years of follow‐up in a population‐based cohort study from Germany (ESTHER cohort). Here, we aimed to evaluate associations of the CRC‐specific miR‐score with the risk of developing other common cancers, including female breast cancer (BC), lung cancer (LC), and prostate cancer (PC), in the ESTHER cohort. MicroRNAs (miRNAs) were profiled by quantitative real‐time PCR in serum samples collected at baseline from randomly selected incident cases of BC (n = 90), LC (n = 88), and PC (n = 93) and participants without diagnosis of CRC, LC, BC, or PC (controls, n = 181) until the end of the 17‐year follow‐up. Multivariate logistic regression models were used to evaluate the associations of the miR‐score with BC, LC, and PC incidence. The miR‐score showed strong inverse associations with BC and LC incidence [odds ratio per 1 standard deviation increase: 0.60 (95% confidence interval [CI] 0.43–0.82), p = 0.0017, and 0.64 (95% CI 0.48–0.84),p = 0.0015, respectively]. Associations with PC were not statistically significant but pointed in the positive direction. Our study highlights the potential of serum‐based miRNA biomarkers for cancer‐specific risk prediction. Further large cohort studies aiming to investigate, validate, and optimize the use of circulating miRNA signatures for cancer risk assessment are warranted. Circulating microRNAs (miRNAs) could improve cancer risk prediction. Our findings demonstrate that miRNA profiles associated with tumor progression differ across cancer types and could be useful for developing personalized cancer prevention strategies. [ABSTRACT FROM AUTHOR]
Details
- Language :
- English
- ISSN :
- 13479032
- Volume :
- 115
- Issue :
- 6
- Database :
- Complementary Index
- Journal :
- Cancer Science
- Publication Type :
- Academic Journal
- Accession number :
- 177627635
- Full Text :
- https://doi.org/10.1111/cas.16135