Pharmacogenomics and metastatic colorectal cancer: current knowledge and perspectives

LGR5 rs17109924 is a predictive genetic biomarker for time to recurrence in patients with colon cancer treated with 5-fluorouracil-based adjuvant chemotherapy

We recently found variants in cancer stem cell genes (CD44, ALCAM and LGR5) significantly associated with increased time to recurrence (TTR) in patients with stage III and high-risk stage II colon cancer treated with 5-fluorouracil (5-FU)-based chemotherapy. In this study, we validated these genetic biomarkers in a large and independent patient cohort (n=599). Patients who received 5-FU-based adjuvant chemotherapy (n=391) carrying at least one C allele in LGR5 rs17109924 had a significantly increased TTR compared with patients carrying the homozygous T/T variant (HR 0.38, 95%CI 0.19–0.79; P=0.006). In patients treated with surgery alone (n=208), no association between LGR rs17109924 and TTR was found (P=0.728). In the multivariate Cox-analysis, LGR5 rs17109924 remained statistically significant (HR 0.38, 95%CI 0.18–0.78; P=0.008) for patients who received adjuvant chemotherapy. We confirmed in a large and independent study cohort that LGR5 rs17109924 is a predictive genetic biomarker for TTR in patients with colon cancer treated with 5-FU-based adjuvant chemotherapy.

Multiple regression analysis of mRNA-miRNA associations in colorectal cancer pathway

BACKGROUND

MicroRNA (miRNA) is a short and endogenous RNA molecule that regulates posttranscriptional gene expression. It is an important factor for tumorigenesis of colorectal cancer (CRC), and a potential biomarker for diagnosis, prognosis, and therapy of CRC. Our objective is to identify the related miRNAs and their associations with genes frequently involved in CRC microsatellite instability (MSI) and chromosomal instability (CIN) signaling pathways.

RESULTS

A regression model was adopted to identify the significantly associated miRNAs targeting a set of candidate genes frequently involved in colorectal cancer MSI and CIN pathways. Multiple linear regression analysis was used to construct the model and find the significant mRNA-miRNA associations. We identified three significantly associated mRNA-miRNA pairs: BCL2 was positively associated with miR-16 and SMAD4 was positively associated with miR-567 in the CRC tissue, while MSH6 was positively associated with miR-142-5p in the normal tissue. As for the whole model, BCL2 and SMAD4 models were not significant, and MSH6 model was significant. The significant associations were different in the normal and the CRC tissues.

CONCLUSION

Our results have laid down a solid foundation in exploration of novel CRC mechanisms, and identification of miRNA roles as oncomirs or tumor suppressor mirs in CRC.

Gender-specific profiling in SCN1A polymorphisms and time-to-recurrence in patients with stage II/III colorectal cancer treated with adjuvant 5-fluoruracil chemotherapy

This study was designed to analyze the gender-related association between SCN1A polymorphisms (voltage-gated sodium channels; α-subunit) and time-to-recurrence (TTR) in patients with colorectal cancer (CRC) treated with 5-fluoruracil (5-FU)-based adjuvant chemotherapy. We enrolled from a prospective database patients with stage II and III CRC treated with adjuvant 5-FU-based chemotherapy. Genotypes for SCN1A rs3812718 and rs229877 were determined by direct DNA sequencing. One hundred twenty-seven males and 107 females were included in the study. In the univariate and multivariate analysis, the shortest TTR was associated with female patients carrying the rs3812718-TT genotype (hazard ratio (HR): 2.26 (95% confidence interval (CI): 0.89, 5.70), P=0.039) but with male patients carrying the rs3812718-CC genotype (HR: 0.49 (95% CI: 0.18, 1.38), P=0.048). For rs229877 the CT genotype was associated with a trend for shorter TTR in both gender populations. The study validated gender-dependent association between genomic SCN1A rs3812718 polymorphism and TTR in CRC patients treated with adjuvant 5-FU-based chemotherapy. This study confirms that voltage-gated Na+ channels may be a potential therapeutic target and a useful predictive biomarker before 5-FU infusion.

Metabolomics as a tool for personalizing medicine: 2012 update

Numerous factors in conjunction with an individual’s genetic make up will determine predisposition to disease, adverse or beneficial effects of drug treatment or therapy, and disease progression. A major limitation of current clinical measures is that the disease phenotype, which is comprised of the genotype and other environmental factors, is underestimated. Rather, each disease is treated similarly even though the disease process is highly complex. Methods that evaluate the interaction of genotype and environmental factors would likely be a better indicator of patients’ response to medical treatments. The omics technologies, specifically metabolomics, will play a major role in the movement towards personalized medicine. Metabolomics is phenotype driven and should provide better clinical biomarkers. Furthermore, recent studies have shown that associations between genetic variants and downstream metabolite changes can provide a unique description of an individual’s genotype and phenotype, which will further enhance the movement towards personalized medicine.