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Molecular characterization and biomarker identification in colorectal cancer: Toward realization of the precision

Gaurav Goel1

  • 1Division of Hematology-Oncology, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA, ggoel.uky@gmail.com.

Cancer Management and Research
|December 5, 2018
PubMed

Insights

Molecular biomarkers like KRAS and NRAS mutations help predict treatment response in metastatic colorectal cancer (mCRC). Identifying new biomarkers through advanced sequencing and omics approaches is crucial for improving patient survival.

Area of Science:

  • Oncology
  • Molecular Diagnostics
  • Genetics

Background:

  • Colorectal cancer (CRC) presents a significant global health challenge.
  • Advances in treating metastatic CRC (mCRC) have been substantial over the last two decades.
  • Biomarker development is key to personalizing anti-EGFR therapy for mCRC patients.

Purpose of the Study:

  • To review recent progress in molecular stratification for CRC.
  • To discuss the role of current and emerging biomarkers in mCRC treatment.
  • To highlight the impact of genetic mutations on therapeutic outcomes.

Main Methods:

  • Review of recent advancements in molecular diagnostics for CRC.
  • Analysis of the predictive value of genetic mutations (e.g., KRAS, NRAS) in mCRC.
  • Exploration of next-generation sequencing and omics-based strategies.

Main Results:

  • Activating mutations in KRAS and NRAS genes are established predictors of resistance to anti-EGFR therapy in mCRC.
  • Molecular stratification is essential for optimizing treatment selection.
  • Advanced technologies offer new avenues for biomarker discovery.

Conclusions:

  • KRAS and NRAS mutations are critical for guiding anti-EGFR therapy decisions in mCRC.
  • Further survival improvements in mCRC necessitate the discovery and validation of novel predictive biomarkers.
  • Innovative clinical trials and omics approaches are vital for future biomarker development.
Keywords:
biomarkerscirculating tumor DNAcolorectal cancernext-generation sequencingomicspersonalized medicine

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