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Detection of a Circulating MicroRNA Custom Panel in Patients with Metastatic Colorectal Cancer
Published on: March 14, 2019
Potential biomarkers for anti-EGFR therapy in metastatic colorectal cancer
Jiao Yang1, Shuting Li1, Biyuan Wang1
1Department of Medical Oncology, The First Affiliated Hospital of Xi'an Jiaotong University, 277 Yanta West Road, Xi'an, 710061, Shaanxi Province, China.
Abstract:
Anti-epidermal growth factor receptor (EGFR) therapy has established efficacy in metastatic colorectal cancer, but a significant number of patients do not respond to such treatment. Recently, various biomarkers were reported to be useful in predicting resistance to anti-EGFR. All the potential biomarkers predicting resistance to anti-EGFR are reviewed herein from five aspects. First, upstream molecules, including epiregulin (EREG) and amphiregulin (AREG), might play different roles according to their abnormal levels in tumor tissue and serum. Second, the EGFR amplification and distinct polymorphisms may have roles in identifying patients for initial anti-EGFR mAbs therapy, while rare EGFR mutations have limited predictive values. Third, among the downstream molecularly related factors, rat sarcoma viral oncogene (Ras) has been identified as a successful predictor, while B-Raf proto-oncogene (BRAF) is considered as a prognostic factor rather than a predictor. Fourth, among the molecular bypass pathway components, phosphatidylinositol 3-kinase (PI3K) and phosphatase and tensin homolog (PTEN) may be potential biomarkers in the future, while activation of hepatocyte growth factor (HGF)/c-Met signaling confers resistance to anti-EGFR therapy. Fifth, many microRNAs and additional molecular biomarkers are promising in predicting the efficacy of anti-EGFR therapy. Applications of multiple biomarkers are more effective than the use of a single biomarker in selecting patients who might benefit from cetuximab- or panitumumab-based treatments. Comprehensive molecular analyses of the EGFR signaling pathways should be considered in the future. Subsequent prospective trials will be required to further confirm the clinical utility of these biomarkers.
Insights
Predicting resistance to anti-epidermal growth factor receptor (EGFR) therapy in colorectal cancer is crucial. Biomarkers like Ras, EREG, AREG, and microRNAs show promise in identifying non-responders for better treatment selection.
Area of Science:
- Oncology
- Molecular Biology
- Genetics
Background:
- Anti-epidermal growth factor receptor (EGFR) therapy is effective for metastatic colorectal cancer.
- A significant portion of patients exhibit primary or acquired resistance to anti-EGFR treatments.
- Identifying predictive biomarkers is essential for optimizing patient selection and treatment strategies.
Purpose of the Study:
- To comprehensively review potential biomarkers predicting resistance to anti-EGFR therapy in colorectal cancer.
- To analyze biomarkers from five key aspects: upstream molecules, EGFR alterations, downstream factors, bypass pathways, and microRNAs.
- To evaluate the utility of single versus multiple biomarkers in predicting treatment response.
Main Methods:
- Literature review and analysis of existing studies on biomarkers related to anti-EGFR therapy resistance.
- Categorization of biomarkers based on their position within the EGFR signaling pathway and related molecular mechanisms.
- Assessment of the predictive and prognostic value of various molecular alterations and signaling pathways.
Main Results:
- Upstream molecules like epiregulin (EREG) and amphiregulin (AREG) show potential, with levels in tumor tissue and serum being significant.
- EGFR amplification and polymorphisms may aid initial therapy selection, but rare EGFR mutations have limited predictive value.
- Downstream factors like Ras are successful predictors, while BRAF is more prognostic. Phosphatidylinositol 3-kinase (PI3K), phosphatase and tensin homolog (PTEN), and HGF/c-Met signaling activation are implicated in resistance.
- MicroRNAs and other molecular biomarkers show promise, and combined biomarker approaches are more effective than single markers.
Conclusions:
- Multiple biomarkers, analyzed comprehensively within EGFR signaling pathways, are more effective for predicting response to anti-EGFR therapies like cetuximab and panitumumab.
- Prospective trials are necessary to validate the clinical utility of these identified biomarkers.
- Future research should focus on integrated molecular analyses for personalized anti-EGFR treatment strategies.
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