Combined RAS and SMAD4 Mutations and Microsatellite Instability Predict Outcomes in Colorectal Lung Metastases

Tao Xu1,2,3, Xuancheng Xie4, Xinyue Gu5

  • 1Department of Radiology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.

Abstract

Insights

Combined RAS/SMAD4 mutations and microsatellite instability (MSI) predict outcomes for colorectal cancer lung metastases (CRLM) treated with image-guided thermal ablation (IGTA). High-risk patients identified by these biomarkers may benefit from personalized treatment strategies.

Area of Science:

  • Oncology
  • Molecular Biology
  • Interventional Radiology

Background:

  • Image-guided thermal ablation (IGTA) offers a minimally invasive treatment for colorectal cancer lung metastases (CRLM).
  • Predictive biomarkers for IGTA outcomes in CRLM are debated.
  • This study investigates the combined prognostic value of RAS/SMAD4 mutational status and microsatellite instability (MSI).

Purpose of the Study:

  • To evaluate if combined RAS/SMAD4 mutational status and MSI predict outcomes after IGTA in CRLM patients.
  • To address the controversy surrounding prognostic biomarkers in CRLM treatment.

Main Methods:

  • A multicenter retrospective study of 412 CRLM patients undergoing CT-guided IGTA.
  • Patients stratified by microsatellite status (MSS vs. MSI) and RAS/SMAD4 genotype.
  • Primary endpoints: local tumor progression (LTP), progression-free survival (PFS), and overall survival (OS).

Main Results:

  • Poorer OS independently predicted by lesion size ≥20 mm, ≥3 lesions, synchronous metastases, MSI, and RAS mutation.
  • Shorter PFS predicted by RAS and SMAD4 mutations.
  • In MSI tumors, concurrent RAS/SMAD4 mutations worsened OS/PFS (p < 0.05). In MSS tumors, single RAS/SMAD4 mutations also reduced survival.
  • MSI status independently associated with higher mortality risk (HR 1.67, p = 0.005).

Conclusions:

  • Concurrent RAS/SMAD4 alterations and MSI status identify high-risk CRLM patients post-IGTA.
  • Integrating these molecular markers can enhance risk stratification.
  • Personalized treatment strategies can be guided by these biomarkers.

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