Special Issue "Personalized Medicine and Pharmacogenomics"

A special issue of Pharmaceutics (ISSN 1999-4923).

Deadline for manuscript submissions: closed (15 September 2016).

Special Issue Editor

Dr. Huixiao Hong
E-Mail
Guest Editor
National Center for Toxicological Research, U.S. Food and Drug Administration , 3900 NCTR Road, Building 5, Room 5C-109A, Jefferson, AR 72079, USA
Interests: pharmacogenomics; personalized medicine; toxicogenomics; bioinformatics; predictive toxicology
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Special Issue Information

Dear Colleagues,

Personalized medicine enhance healthcare by selecting treatments that are more efficient or induce less adverse responses in stratified cohorts with different genetic content. Pharmacogenomics is the key to identify personalized medicine biomarkers useful for efficacy and safety that can ultimately be clinically applied for diagnosis and prognosis and treatment selection. This Special Issue, “Personalized Medicine and Pharmacogenomics”, will deal with all aspects of personalized medicine and pharmacogenomics. The topics of papers in this Special Issue include genetics, genomics, proteomics and metabolomics biomarkers, emerging techniques, such as next-generation sequencing, diagnosis and prognosis of diseases, applications in drug development, and regulatory sciences. In addition, papers dealing with bio-banks, intellectual property rights, human subject issues, such as patient privacy and confidentiality in implementing personalized medicine, will also be considered.

Dr. Huixiao Hong
Guest Editor

Manuscript Submission Information

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Keywords

  • personalized medicine
  • pharmacogenomics
  • biomarkers
  • genetics
  • genomics
  • proteomics
  • metabolomics
  • diagnosis
  • prognosis
  • bio-banks
  • regulatory sciences
  • drug development

Published Papers (4 papers)

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Research

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Open AccessArticle
Microarray Analysis of Differentially-Expressed Genes Encoding CYP450 and Phase II Drug Metabolizing Enzymes in Psoriasis and Melanoma
Pharmaceutics 2016, 8(1), 4; https://doi.org/10.3390/pharmaceutics8010004 - 17 Feb 2016
Cited by 8
Abstract
Cytochrome P450 drug metabolizing enzymes are implicated in personalized medicine for two main reasons. First, inter-individual variability in CYP3A4 expression is a confounding factor during cancer treatment. Second, inhibition or induction of CYP3A4 can trigger adverse drug–drug interactions. However, inflammation can downregulate CYP3A4 [...] Read more.
Cytochrome P450 drug metabolizing enzymes are implicated in personalized medicine for two main reasons. First, inter-individual variability in CYP3A4 expression is a confounding factor during cancer treatment. Second, inhibition or induction of CYP3A4 can trigger adverse drug–drug interactions. However, inflammation can downregulate CYP3A4 and other drug metabolizing enzymes and lead to altered metabolism of drugs and essential vitamins and lipids. Little is known about effects of inflammation on expression of CYP450 genes controlling drug metabolism in the skin. Therefore, we analyzed seven published microarray datasets, and identified differentially-expressed genes in two inflammatory skin diseases (melanoma and psoriasis). We observed opposite patterns of expression of genes regulating metabolism of specific vitamins and lipids in psoriasis and melanoma samples. Thus, genes controlling the turnover of vitamin D (CYP27B1, CYP24A1), vitamin A (ALDH1A3, AKR1B10), and cholesterol (CYP7B1), were up-regulated in psoriasis, whereas melanomas showed downregulation of genes regulating turnover of vitamin A (AKR1C3), and cholesterol (CYP39A1). Genes controlling abnormal keratinocyte differentiation and epidermal barrier function (CYP4F22, SULT2B1) were up-regulated in psoriasis. The up-regulated CYP24A1, CYP4F22, SULT2B1, and CYP7B1 genes are potential drug targets in psoriatic skin. Both disease samples showed diminished drug metabolizing capacity due to downregulation of the CYP1B1 and CYP3A5 genes. However, melanomas showed greater loss of drug metabolizing capacity due to downregulation of the CYP3A4 gene. Full article
(This article belongs to the Special Issue Personalized Medicine and Pharmacogenomics)
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Review

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Open AccessReview
Challenges, Solutions, and Quality Metrics of Personal Genome Assembly in Advancing Precision Medicine
Pharmaceutics 2016, 8(2), 15; https://doi.org/10.3390/pharmaceutics8020015 - 22 Apr 2016
Cited by 6
Abstract
Even though each of us shares more than 99% of the DNA sequences in our genome, there are millions of sequence codes or structure in small regions that differ between individuals, giving us different characteristics of appearance or responsiveness to medical treatments. Currently, [...] Read more.
Even though each of us shares more than 99% of the DNA sequences in our genome, there are millions of sequence codes or structure in small regions that differ between individuals, giving us different characteristics of appearance or responsiveness to medical treatments. Currently, genetic variants in diseased tissues, such as tumors, are uncovered by exploring the differences between the reference genome and the sequences detected in the diseased tissue. However, the public reference genome was derived with the DNA from multiple individuals. As a result of this, the reference genome is incomplete and may misrepresent the sequence variants of the general population. The more reliable solution is to compare sequences of diseased tissue with its own genome sequence derived from tissue in a normal state. As the price to sequence the human genome has dropped dramatically to around $1000, it shows a promising future of documenting the personal genome for every individual. However, de novo assembly of individual genomes at an affordable cost is still challenging. Thus, till now, only a few human genomes have been fully assembled. In this review, we introduce the history of human genome sequencing and the evolution of sequencing platforms, from Sanger sequencing to emerging “third generation sequencing” technologies. We present the currently available de novo assembly and post-assembly software packages for human genome assembly and their requirements for computational infrastructures. We recommend that a combined hybrid assembly with long and short reads would be a promising way to generate good quality human genome assemblies and specify parameters for the quality assessment of assembly outcomes. We provide a perspective view of the benefit of using personal genomes as references and suggestions for obtaining a quality personal genome. Finally, we discuss the usage of the personal genome in aiding vaccine design and development, monitoring host immune-response, tailoring drug therapy and detecting tumors. We believe the precision medicine would largely benefit from bioinformatics solutions, particularly for personal genome assembly. Full article
(This article belongs to the Special Issue Personalized Medicine and Pharmacogenomics)
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Open AccessReview
Genomic Discoveries and Personalized Medicine in Neurological Diseases
Pharmaceutics 2015, 7(4), 542-553; https://doi.org/10.3390/pharmaceutics7040542 - 07 Dec 2015
Cited by 4
Abstract
In the past decades, we have witnessed dramatic changes in clinical diagnoses and treatments due to the revolutions of genomics and personalized medicine. Undoubtedly we also met many challenges when we use those advanced technologies in drug discovery and development. In this review, [...] Read more.
In the past decades, we have witnessed dramatic changes in clinical diagnoses and treatments due to the revolutions of genomics and personalized medicine. Undoubtedly we also met many challenges when we use those advanced technologies in drug discovery and development. In this review, we describe when genomic information is applied in personal healthcare in general. We illustrate some case examples of genomic discoveries and promising personalized medicine applications in the area of neurological disease particular. Available data suggest that individual genomics can be applied to better treat patients in the near future. Full article
(This article belongs to the Special Issue Personalized Medicine and Pharmacogenomics)
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Open AccessReview
Alignment of Short Reads: A Crucial Step for Application of Next-Generation Sequencing Data in Precision Medicine
Pharmaceutics 2015, 7(4), 523-541; https://doi.org/10.3390/pharmaceutics7040523 - 23 Nov 2015
Cited by 11
Abstract
Precision medicine or personalized medicine has been proposed as a modernized and promising medical strategy. Genetic variants of patients are the key information for implementation of precision medicine. Next-generation sequencing (NGS) is an emerging technology for deciphering genetic variants. Alignment of raw reads [...] Read more.
Precision medicine or personalized medicine has been proposed as a modernized and promising medical strategy. Genetic variants of patients are the key information for implementation of precision medicine. Next-generation sequencing (NGS) is an emerging technology for deciphering genetic variants. Alignment of raw reads to a reference genome is one of the key steps in NGS data analysis. Many algorithms have been developed for alignment of short read sequences since 2008. Users have to make a decision on which alignment algorithm to use in their studies. Selection of the right alignment algorithm determines not only the alignment algorithm but also the set of suitable parameters to be used by the algorithm. Understanding these algorithms helps in selecting the appropriate alignment algorithm for different applications in precision medicine. Here, we review current available algorithms and their major strategies such as seed-and-extend and q-gram filter. We also discuss the challenges in current alignment algorithms, including alignment in multiple repeated regions, long reads alignment and alignment facilitated with known genetic variants. Full article
(This article belongs to the Special Issue Personalized Medicine and Pharmacogenomics)
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