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Circulating miRNA Signature Predicts Cancer Incidence in Lynch Syndrome-A Pilot Study

  • 0Gerontology Research Center and Faculty of Sport and Health Sciences, University of Jyväskylä, Jyväskylä, Finland.
Cancer Prevention Research (philadelphia, Pa.) +

|

March 29, 2024

|

March 29, 2024

View abstract on PubMed

Summary

This summary is machine-generated.

A new circulating microRNA (c-miR) signature can predict Lynch syndrome (LS) cancer incidence within four years. This biomarker also correlates with body mass index (BMI), offering insights into cancer risk management.

Area Of Science

  • Oncology
  • Genetics
  • Biomarkers

Background

  • Lynch syndrome (LS) is an autosomal dominant cancer predisposition with high genetic risk.
  • Lifestyle factors significantly modify cancer risk in LS patients.
  • Effective cancer risk prediction models are crucial for improving LS patient survival.

Purpose Of The Study

  • To investigate a circulating microRNA (c-miR) signature for predicting LS cancer incidence.
  • To explore the correlation between the c-miR signature and lifestyle risk factors.
  • To develop and validate a predictive model for LS cancer risk.

Main Methods

  • Analysis of 110 c-miR samples from LS carriers over a 4-year prospective surveillance period.
  • Utilized Lasso regression to identify cancer-predicting c-miRs.
  • Developed a predictive model based on c-miR risk score and validated using 5-fold cross-validation.
  • Assessed correlations between c-miR risk score and lifestyle factors (physical activity, BMI, diet, NSAID usage).

Main Results

  • Identified five c-miRs (hsa-miR-10b-5p, hsa-miR-125b-5p, hsa-miR-200a-3p, hsa-miR-3613-5p, hsa-miR-3615) as cancer predictors.
  • The c-miR risk score significantly predicted LS cancer incidence (HR 2.72, C-index = 0.72), with cross-validation yielding an average C-index of 0.75.
  • The c-miR risk score showed a correlation with body mass index (BMI) (r = 0.23, P < 0.01).

Conclusions

  • A specific c-miR signature can predict Lynch syndrome cancer incidence within a 4-year timeframe.
  • The identified c-miR signature is associated with BMI, suggesting a link between lifestyle and molecular risk prediction.
  • This pilot study provides a novel serum miRNA-based risk prediction model for LS, warranting further validation.

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