A recent meta analysis of several literature sources reveals evidence linking polymorphisms of both the GSTM1 and GSTT1 enzymes, which are involved in kidney detoxification of carcinogens to the risk of developing of renal cell carcinoma (RCC).
2,3, to the risk of developing of renal cell carcinoma (RCC).
Emerging evidence suggests that polymorphisms in the genes of both these enzymes could result in a loss of activity, which may increase an individual's risk for developing RCC1and the toxicities, and effects, of treatment for the cancer2. This particular collection of meta-data by Wentao Huang, MD, Department of Urology, Third Affiliated Hospital, Sun Yat-sen University, Guangzhou, China, et al, focused on the deletion aspect, which causes the enzymes in an individual's to become inactive so they are longer able to process carcinogens.
Glutathione S-transferases (GSTs) are a super family of enzymes that are subdivided into 7 classes (α, μ, ω, π, σ, θ, ξ). These enzymes protect cells by facilitating the detoxification of electrophilic compounds through conjugation with glutathione.1This is an essential step of the detoxification process and facilitates their excretion from the body. Since the electrophilic compounds can potentially damage DNA, GSTs are important for maintaining genomic integrity.1
Two variants of GSTT1 can occur through substitution and deletion. The substitution polymorphism changes C-to-G at base position 534, resulting in a lysine-to-asparagine switch. This does not appear to affect the way the enzyme functions. The deletion variant, however, is a null genotype of GSTM1. This is more commonly studied than the substitution variant because it leads to the absence of GST-μ1 synthesis.1
Currently, there is not much data focused on the connection between GSTM1 and GSTT1 polymorphisms, and RCC. The few studies that have examined the connection have not had consistent conclusions. The study conducted by Huang, et al, focused on compiling all meta-analyses currently available to increase the statistical power of finding overall effects. Due to the small sample size and complexity of the relationship and all variables considered, a single case-control study may prove to be insufficient.1
Out of the 416 articles discovered in a search through PubMed, ISI, Wangfang, and CNKI databases, 10 were chosen for analysis. Ultimately, 8 studies were analyzed. Five out of the 8 were conducted in Europe, while the other 3 were conducted in America, Australia, and India.1
Eight studies described an association between GSTM1 and RCC by comparing RCC to a healthy control group. The groups were compiled of 1826 cases against 3377 controls. In the same eight studies, the association between GSTT1 and RCC was compared to healthy controls using 1831 cases against 3407 controls. Four of the 8 studies noted an association between the dual null genotype of GSTM1 and GSTT1 and risk of RCC, which included 1307 cases and 2057 controls.
Three studies, all conducted in Europe, assessed the association between GSTM1 or GSTT1 and RCC in patients exposed to pesticide or trichloroethene, which included 107 cases and 101 controls. Three studies, 2 of which took place in Europe and 1 in India, explored the association between GSTM1 and RCC staging, including 224 GSTM1 wild-type patients and 247 GSTM1 null patients. Additionally, four studies, 3 in Europe and 1 in India, explored the association between GSTT1 and RCC staging, including 335 GSTT1 wild-type patients and 251 GSTT1 null patients. The GSTM1 and GSTT1 polymorphisms were detected by PCR in all of the studies.1
The overall response (OR), with a 95% CI score, was used to link GSTM1 and GSTT1 polymorphisms and RCC based on the genotype frequencies in cases and controls. The study's authors collected data and performed a meta-analysis of three assessments:
For the GSTM1 wild-type polymorphism, the meta-analysis looked at the genetic susceptibility in the three conditions described above and compared the wild-type to the GSTM1 null genotype in a recessive model (present/present+ present/null versus null/null).
The same method was used to assess GSTT1. For the dichotomous outcomes, the Mantel-Haenszel method was used and assessed this meta-analysis by using the random-effects model instead of the fixed-effects model to avoiding heterogeneity. The included studies were also stratified according to ethnicity for the exploration of possible heterogeneity.