Open Journal Systems

LETTERS TO THE EDITOR

Comment on “Genomics in medicine”

Víctor Manuel Valdespino-Gómez^a

^aDepartamento de Atención a la Salud, División de Ciencias Biológicas y de la Salud, Universidad Autónoma Metropolitana, Unidad Xochimilco, Distrito Federal, México

Email: vvaldespinog@yahoo.com.mx

I would like to make some comments regarding the article “La genómica en la medicina” ("The genome in medicine") published in the Rev Med Inst Mex Seguro Soc 2014;52(5):566-73.

Dr. Ruiz Esparza-Garrido et al. analyze in a simple and didactic way the major changes that have occurred in recent decades in the study of the genome oriented to applied medicine; for this, omic technologies are used to structurally and functionally examine the human genome. In particular, a brief description was made of the massive sequencing, microarrays, some aspects of proteomics, such as networks or pathways for intracellular signaling, metabolomics, and the utility of bioinformatic support to analyze and interpret the large amount of data produced in these studies. This commentary is intended to highlight some of the latest and most outstanding developments published in this area, which will lead us to a modernized medical practice.

It should be noted that the last decade has seen the complexity of the components and the genomic mechanisms involved in the process of cell balance (in health) and imbalance (in disease), thanks to the results of different genomic research studies that have used various omic technologies. Thus, for example in cancer, a large number of genetic and genomic alterations are involved that encode driver and passenger oncogenic proteins for the processes of initiation and progression. Moreover, added to the recognition of the structural and functional genomic alterations, we have begun to identify that different epigenetic alterations, corresponding to minor biochemical changes in regulatory regions such as promoters, enhancers, and exons, are involved in regulating the expression of coding genes. And that quality, quantity, location, together with posttranslational changes of the encoded proteins, are factors that modify the physiological intracellular signaling pathways.

The final phenotype of a cell / tissue / organ is exercised by the functional integration of the genome, the translatome, and the functional anatomy.¹ It has also been identified that in different types of disease, some recognized patterns of molecular alterations predominate. However, in analogy to what happens in normal functional human genomic variability, which is due to an immense variety of single nucleotide polymorphisms (SNP) and copy number variations (CNV), in the development of a specific disease there is also higher variability of polygenic alterations and pathophysiological mechanisms.² The identification of the individualized molecular components and mechanisms in a patient with a particular disease is the key to increasing our understanding of it, as well as designing or using molecular strategies against it to supplement, block, or produce the compensatory or homeostatic effect required to complete the sequence of biochemical reactions that modify cellular phenotype. Under these principles personalized medicine has emerged, a medicine that helps to identify a more accurate pathophysiological diagnosis (molecular resolution) and select a more rational therapeutic plan (preferably using drugs that are approved or are being studied in clinical trials).³

The comprehensive modern study of the human genome is done using whole exome or genome sequencing technology, which expands the coverage and resolution of the genomic study. Currently, these technologies are the basis of molecular testing in clinical application; recently the Food and Drug Administration (FDA) has authorized the use of a second-generation sequencer (MiSeqDx system) in the feasible study of the human genome to support clinical diagnosis.^4,5 Exercising personalized or precision medicine predominantly involves three steps:

1. Studying the genome of the affected cell clones (together with the germline DNA) identifying driver genes for the pathophysiological process.
2. Filtering genomic data in the search for therapeutic molecular targets, and 3. making a rigorous analysis of clinical and genomic data using support tools. The application of these three steps often requires the cooperation of bioinformatics specialists able to manage specific software and databases for the analysis of genomic data for specific disease models.
3. The use of specific computer algorithms.^6,7

A final breakthrough that I will discuss is the development of a system of genetic engineering that is beginning to revolutionize many areas of biology, including that of human gene therapy. This genomic engineering system, called CRISPR-Cas,9 is formed by an endonuclease, which is guided by an RNA duplex to recognize and bind to specific DNA nucleotide sequences. With the CRISPR system it may be possible to correct the mutations responsible for different genetic diseases, and in addition the system has many other biomedicine and biotechnology applications.⁸

References

1. Kitchen RR, Rozowsky JS, Gerstein MB, Nairn AC. Decoding neuroproteomics: integrating the genome, translatome and functional anatomy. Nature Neurosci. 2014;17:1491-9.
2. Wang E, Zaman N, McGee S, Milanese JS, Masoudi-Nejad A, O’Connor-McCourt M. Predictive genomics: A cancer hallmark network framework for predicting tumor clinical phenotypes using genome sequencing data. Sem Cancer Biol. 2014;Apr 18 (Epub ahead of print).
3. Garray LA, Verweij J. Precision oncology: an overview. J Clin Oncol. 2014;31:1803-5.
4. [No authors listed.] FDA-approved next-generation sequencing system could expand clinical genomic testing: experts predict MiSeqDX system will make genetic testing more affordable for smaller labs. Am J Med Genet A. 2014;164A:x-xi.
5. Collins FS, Hamburg MA. First FDA authorization for next-generation sequencer. N Engl J Med. 2013;369:2369-71.
6. Huser V, Sincan M, Cimino JJ. Developing genomic knowledge bases and databases to support clinical management: current perspectives. Pharmacogenomics Pers Med. 2014;7:275-83.
7. Van Allen EM, Wagle N, Levy MA. Clinical analysis and interpretation of cancer genome data. J Clin Oncol. 2013;31:1825-33.
8. Doudna J, Charpentier E. The new frontier of genome engineering with CRISPR-Cas9. Science. 2014;346:1258096.

Enlaces refback

• No hay ningún enlace refback.