A Brief Review of Cancer
C.S. Sureka, C. Armpilia in Radiation Biology for Medical Physicists, 2017
Cancer is caused by many factors, such as (1) chemicals, (2) radiations, (3) viruses, (4) chromosome replication errors, and (5) DNA misrepair. Mutants (carcinogenic agents), such as chemicals and radiations, alter the DNA by modifying nucleotide sequence of the genome. This process is known as mutation and it is the main source of genetic variation (refers to diversity in gene frequencies between individuals or populations) in addition to mechanisms such as sexual reproduction and genetic drift. The DNA altered by mutation produces error during DNA replication and in turn causes error in protein synthesis, which affects the normal cellular activities, such as cell growth, cell division, and cell aging. Several cancer viruses (human papilloma viruses—cervical cancer, hepatitis B virus—liver cancer etc.) can change cells by transferring their genetic material into the human cell DNA. These infected cells will be controlled by the viral genes, and then they function abnormally.
Including Genetic Variables in NTCP Models Where Are We? Where Are We Going?
Tiziana Rancati, Claudio Fiorino in Modelling Radiotherapy Side Effects, 2019
Radiotherapy schedules maximize tumour control probability (TCP) and minimize normal tissue control probability (NTCP), but are population-based. Radiation doses are limited so that less than ~5% of patients suffer with late side effects. Inclusion of biology in NTCP models would improve the therapeutic ratio and allow for improved biological precision to match developments in the physical precision of radiation delivery. An individual patient’s risk of developing side effects following radiotherapy depends on multiple factors. Radiation dose and the volume irradiated are the most important. It is also known that additional treatments (e.g., surgery, chemotherapy), patient factors (e.g., smoking, older age) and comorbidities (e.g., collagen vascular disease) can increase risk of side effects. Genetic variation is also important.
Pharmacology, Pharmacogenetics, and Pharmacoepidemiology: Three P’s of Individualized Therapy
Brian Leyland-Jones in Pharmacogenetics of Breast Cancer, 2020
Genetic variations include nucleotide repeats, insertions, deletions, and single nucleotide polymorphisms (SNPs). SNPs are the simplest and most commonly studied DNA polymorphism that occur once every 1900 base pairs in the 3 billion bases in the human genome (13) and account for more than 90% of the genetic variation observed. More than 1.4 million SNPs have been identified in the human genome. Of these more than 60,000 SNPs occur in the coding region of genes with some SNPs being associated with variations in drug metabolism and effects (13). When polymorphisms occur in the promoter region it can effect the transcription of the gene. When the polymorphism occurs in the exon (and intron) region or 3’UTR of the gene, it can affect translation and RNA stability, respectively, resulting in either reduced or enhanced activity of the encoded protein (3).
Genomic diversity and differentiation of Alu insertion polymorphisms in a native British and four South Asian migrant populations
Published in Annals of Human Biology, 2023
Rebekah Beaumont, Liz Akam, Puneetpal Singh, Jasvinder Singh Bhatti, Sarabjit Mastana
Genomic DNA samples from five different populations were collected to analyse the level of genetic variation. A native British population was analysed besides four South Asian populations; Indian Punjabi (Sikhs), Indian Gujarati, Bangladeshi, and Pakistani, occupying the East Midlands. According to the 2011 census, roughly 12% of the region’s non-white population were Indian, followed by Pakistani (4.4%) and Bangladeshi (3%) (England and Wales 2011 Census). Blood samples were collected from volunteered donations at various sites and local events in parallel with the genetic studies occurring in the East Midlands region at the time. The participants were between the ages of 18 and 60 and confirmed to be unrelated within three generations. Ethnic backgrounds were defined using a questionnaire concentrating on each of the participant’s four grandparents. The participants completed written consent before donating a blood sample. Institutional ethics and the NHS blood donation service approved the collection and analysis of the anonymous samples for genetic analyses. The final East Midlands Alu dataset contained samples from five different ethnic backgrounds; British White (n = 113), Indian Punjabi (n = 133), Indian Gujarati (n = 92), Bangladeshi (n = 100), and Pakistani (n = 105). We hypothesised that there would be a significant genetic variation at different Alu polymorphisms amongst the East Midlands populations based on different population and geographical origins, marriage, and migration patterns.
Experimental psychology meets behavioral ecology: what laboratory studies of learning polymorphisms mean for learning under natural conditions, and vice versa
Published in Journal of Neurogenetics, 2020
Brian H. Smith, Chelsea N. Cook
An important means for studying natural variation has been to evaluate animals that differ in performance on a specific learning task. The standard approach would be to then investigate in a more reductionistic way the neural and genetic determinants of this variation. In addition, it is important to study the role of this genetic variation in natural environments. This would involve testing animals of different, defined genotypes under semi-natural or natural conditions to establish what the genetic variation might do to enhance the actual fitness of individuals that exhibit different traits. Work on the fruit fly clock neurons under natural conditions, after having been first isolated and studied in the laboratory (Konopka & Benzer, 1971), is a classic example of this kind of approach (Menegazzi et al., 2013; Noreen, Pegoraro, Nouroz, Tauber, & Kyriacou, 2018; Sawyer et al., 1997).
Towards personalized treatment in atopic dermatitis
Published in Expert Opinion on Biological Therapy, 2019
Jorien van der Schaft, Judith L. Thijs, Floor M. Garritsen, D. Balak, Marjolein S. de Bruin-Weller
Implementation of pharmacogenetic biomarkers can be used to optimize the performance of current oral immunosuppressive drugs. Pharmacogenetic research explores the effect of pharmacokinetics, pharmacodynamics, efficacy, and safety of drug treatments in relation to genome variations [13]. The most common genetic variations that have been studied are single-nucleotide polymorphisms (SNPs), genetic copynumber variations (CNVs), and genomic insertions and deletions [14]. All of these genetic variations can influence the response of a patient to a specific drug. The goal of pharmacogenetic research is to predict this response (Figure 1). Pharmacogenetic testing provides a tool that can maximize therapeutic efficacy and safety of drug treatment, with the ultimate goal of creating personalized treatment strategies [13,14].
Related Knowledge Centers
- DNA
- DNA Sequencing
- Genetic Drift
- Mutation
- Nucleotide
- Phenotype
- Amino Acid
- Genetic Recombination
- Protein Primary Structure
- Natural Selection