Advances and Challenges in KRAS Mutation Detection and Clinical Implications

Maryam Sadat Mirlohi1,2, Tooba Yousefi1, Javad Razaviyan1

  • 1Department of Clinical Biochemistry, School of Medicine, Shahid Beheshti University of Medical Sciences, Tehran 1985717413, Iran.

Cancers
|January 10, 2026
PubMed

Insights

KRAS mutations drive cancer by activating signaling pathways. New detection methods are crucial for developing targeted therapies and improving patient outcomes.

Area of Science:

  • Oncology
  • Molecular Biology
  • Genetics

Background:

  • Aberrant RAS signaling pathway activation is a hallmark of many cancers, often driven by RAS gene mutations.
  • Specific codon mutations in RAS genes significantly impact cancer patient outcomes.
  • KRAS was historically considered undruggable, but novel inhibitors are emerging.

Purpose of the Study:

  • To provide a comprehensive overview of KRAS mutation detection methods.
  • To critically evaluate existing methods for accuracy, sensitivity, cost, and clinical applicability.
  • To guide researchers and clinicians in selecting appropriate diagnostic tools.

Main Methods:

  • Review of various KRAS mutation detection techniques, from research-use-only to in vitro diagnostics.
  • Critical evaluation of published results based on key performance metrics.
  • Analysis of suitability for different sample types and clinical settings.

Main Results:

  • Numerous methods for KRAS mutation detection have been developed, aiming for robustness, speed, sensitivity, accuracy, and cost-effectiveness.
  • These methods range from basic research tools to certified clinical diagnostic tests.
  • Published data on method performance varies, necessitating careful evaluation.

Conclusions:

  • Accurate KRAS mutation identification is essential for personalized cancer treatment strategies.
  • The development of effective KRAS inhibitors highlights the importance of reliable detection methods.
  • This review serves as a resource for understanding the landscape of KRAS mutation detection technologies.