A Stochastic Binary Model for the Regulation of Gene Expression to Investigate Responses to Gene Therapy.

In this manuscript, we use an exactly solvable stochastic binary model for the regulation of gene expression to analyze the dynamics of response to a treatment aiming to modulate the number of transcripts of a master regulatory switching gene. The challenge is to combine multiple processes with different time scales to control the treatment response by a switching gene in an unavoidable noisy environment. To establish biologically relevant timescales for the parameters of the model, we select the RKIP gene and two non-specific drugs already known for changing RKIP levels in cancer cells. We demonstrate the usefulness of our method simulating three treatment scenarios aiming to reestablish RKIP gene expression dynamics toward a pre-cancerous state: (1) to increase the promoter's ON state duration; (2) to increase the mRNAs' synthesis rate; and (3) to increase both rates. We show that the pre-treatment kinetic rates of ON and OFF promoter switching speeds and mRNA synthesis and degradation will affect the heterogeneity and time for treatment response. Hence, we present a strategy for reaching increased average mRNA levels with diminished heterogeneity while reducing drug dosage by simultaneously targeting multiple kinetic rates that effectively represent the chemical processes underlying the regulation of gene expression. The decrease in heterogeneity of treatment response by a target gene helps to lower the chances of emergence of resistance. Our approach may be useful for inferring kinetic constants related to the expression of antimetastatic genes or oncogenes and for the design of multi-drug therapeutic strategies targeting the processes underpinning the expression of master regulatory genes.

Polymorphisms in the p27kip-1 and prohibitin genes denote novel genes associated with melanoma risk in Brazil, a high ultraviolet index region.

Ultraviolet (UV) radiation is a major environmental risk factor to the development of cutaneous melanoma as it induces pyrimidine dimers in DNA. Genes that exert their function by arresting the cell cycle are critical to avoid carcinogenic mutations, allowing the processing of DNA repair systems. This study was carried out to evaluate the role of polymorphisms in cell cycle genes such as TP53, p27, CDKN2A, prohibitin, and GADD153 in melanoma risk as well as their influence on known risk factors in a high UV index region. A hospital-based case-control study was carried out in Brazil to evaluate the contribution of polymorphisms in cell cycle genes toward melanoma risk. The study comprised 202 melanoma patients and 210 controls. The polymorphisms analyzed were TP53 Arg72Pro, p27 Val109Gly, GADD153 Phe10Phe (rs697221), CDKN2A 3'UTR C540G, and prohibitin 3'UTR C1703T. As regards, p27 Val109Gly, both heterozygous and homozygous Gly genotypes were shown to be protective genotypes on calculating both crude and adjusted odds ratios (ORs) for age, sex, and educational level [OR 0.37; 95% confidence interval (CI) 0.16-0.87; P<0.05]. Similarly, the prohibitin TT genotype increased melanoma risk in the crude and adjusted analyses (OR 2.40; 95% CI 1.10-5.26; P<0.05). The p27 Gly protective genotype decreased the risk for melanoma in a stratified analysis of the known risk factors such as hair and eye color, sunburns, pigmented lesions, and European ancestry. The prohibitin TT genotype increased the risk of melanoma by such host factors. Our results showed for the first time that polymorphisms in p27 Val109Gly and in prohibitin 3'UTR C1703T genotypes modulate the risk to melanoma in a high UV index region.