Modern stem cell biology has achieved a transformation that was thought by many to be every bit as unattainable as the ancient alchemists' dream of transforming base metals into gold. Exciting opportunities arise from the process known as 'cellular reprogramming' in which cells can be reliably changed from one tissue type to another. This is enabling novel approaches to more deeply investigate the fundamental basis of cell identity. In addition, new opportunities have also been created to study (perhaps even to treat) human genetic and degenerative diseases. Specific cell types that are affected in inherited disease can now be generated from easily accessible cells from the patient and compared with equivalent cells from healthy donors. The differences in cellular phenotype between the two may then be identified, and assays developed to establish therapies that prevent the development or progression of disease symptoms. Cellular reprogramming also has the potential to create new cells to replace those whose death or dysfunction causes disease symptoms. For patients suffering from inherited cases of degenerative diseases like Parkinson's disease or amyotrophic lateral sclerosis (also known as motor neuron disease), the future realization of such cell-based therapies would truly be worth its weight in gold. However, before this enormous potential can become a reality, several significant biological and technical challenges must be overcome. Furthermore, to maintain the credibility of the scientific community with the general public, it is important that hope-inspiring advances are not over-hyped. The papers in this issue of the Philosophical Transactions of the Royal Society B: Biological Sciences cover many areas relevant to this topic. In this Introduction, we provide an overall context in which to consider these individual papers.
|Number of pages||15|
|Journal||Philosophical Transactions of the Royal Society B: Biological Sciences|
|Publication status||Published - 2011|
- stem cells
- regenerative medicine
- disease modelling
- transcription factors