Gene Array Technology and the Search for Cosmeceutical Actives

Introduction

The number of cosmeceutical products on the market which claim a variety of beneficial effects on skin structure and function is growing rapidly with new product introductions occurring almost daily. Products which claim effectiveness in stimulating collagen and elastin production, blocking activity of matrix metalloproteinases (MMPs), and slowing down the aging process are widely available and most advertise that ‘scientific research’ is behind their development. In reality, few ingredients in cosmetic products have been shown, by rigorous laboratory analysis, to have specific antiaging effects. Noteworthy exceptions are retinoic acid and its derivatives, vitamin C, and Matrixyl (palmitoyl- l -lysyl- l -threonyl- l -threonyl- l -lysyl- l -serine), which are three compounds for which credible scientific data exist to support antiaging claims. The development of truly efficacious cosmeceuticals involves:

• 1.

  The use of a rigorous cell and molecular biology-based screening program to identify active compounds with the desired biologic activity (e.g. collagen I, III, or VII gene stimulation).

• 2.

  The application of this screening program to determine that the identified ‘active’ ingredient does not also produce undesirable biologic effects on skin cells (e.g. MMP-1 gene activity).

• 3.

  The development of topical formulations which can be shown by skin percutaneous absorption analysis to deliver sufficient amounts of the ‘active’ ingredient across the stratum corneum and down to the target cells to achieve the required biologic effect.

• 4.

  The use of double-blind, placebo-controlled clinical studies with a sufficient number of patients to generate statistically significant data on product efficacy.

Since the first step in developing an effective cosmeceutical product is to demonstrate that the putative ‘active’ ingredient not only produces the desired biologic action but also does not have any deleterious effect on skin structure or function, it would be advantageous to have access to a single biologic screening tool that could accomplish both needs simultaneously. Such a screening method would allow one to predict a compound's efficacy prior to undertaking any laborious formulation development and before conducting expensive clinical studies. The use of gene array technology fulfills these requirements.

Basic principles of gene array analysis

All cells in the body continuously produce a specific set of proteins that defines the structure and function of that particular cell type. For example, liver cells produce unique hormone receptors for glucagon and insulin, while kidney cells produce proteins for the vasopressin receptor and for those involved in ion transport. These proteins are coded for by genes that produce unique mRNAs and, thus, each cell type expresses a unique ‘footprint’ of these mRNAs. Under certain conditions, such as ultraviolet (UV) radiation, hormone influence, and aging, this profile of mRNA expression changes as do the proteins coded for by these ‘messengers’. Thus, for example, in young skin, dermal fibroblasts express mRNA for the proteins collagen I, III, and VII, whereas in aged skin the fibroblasts produce less mRNA for the collagens but more mRNA for the enzyme MMP-1 (matrix metalloproteinase 1; collagenase 1) which destroys collagen. With the advent of modern molecular biology gene arrays, it is now possible to isolate a ‘pool’ of mRNA from cells expressing different phenotypes (e.g. young and old human fibroblasts) and, from an analysis of these mRNAs, determine which genes are being expressed or repressed in different cell types or in cells exposed to different conditions.

Gene arrays are filters or glass slides to which are bound small pieces of known and unknown (EST – expressed sequence tags) human genes. Typical nylon gene array filters may contain over 5000 different gene sequences on a single filter and some arrays have been designed with specific tissues or diseases in mind. For example, a gene filter has been designed to which over 4000 ‘skin specific’ genes have been bound, allowing one to assess the effects of biologic modifiers, such as hormones, cytokines, and UV radiation, on the expression of genes important in skin.

The sequence of steps involved in a gene array analysis is shown in Figure 28.1 . The first step involves isolating mRNA from cells that represent the ‘control’ group, and from cells exposed to some experimental condition, such as UV radiation (‘experimental’ group). The mRNA preparation from each group is then reverse transcribed into ‘complementary DNA’ (cDNA), which is more stable and hybridizes better to DNA than mRNA. This cDNA is then labeled with either a radioisotope or a fluorescent tag so that each unique cDNA can be detected and identified at the conclusion of the experiment. Once the cDNAs have been tagged, they are incubated with the gene array filter (e.g. the ‘skin specific’ array) so that hybridization between a given cDNA and its complementary DNA on the array can occur. Once hybridization is complete, any unbound cDNA is washed away and the hybridized cDNA is detected and quantified. Since the location and identity of each gene on the filter is known, by comparing the quantified spots on the array produced from the ‘control’ group to those spots that are produced in the ‘experimental’ array, one can determine if a particular gene in the experimental group is upregulated or downregulated relative to the control group. Given the complexity of gene arrays, a computer software program is used to aid in the quantification and analysis of the large amount of data that is obtained. The software produces an ‘overlay’ image of both gene array filters, calculates the difference in expression level for each gene between the control and experimental groups, and then converts this relative expression data into a color image. Typically, a gene that is upregulated in the experimental group relative to the control group is shown as a green spot on the computer-generated image while genes that are downregulated are shown in red. An example of the use of this technology in the identification of a novel antiaging and anti-inflammatory active is discussed below.