Making sense of intratumor genetic heterogeneity: altered frequency of androgen receptor CAG repeat length variants in breast cancer tissues

Next-Generation Sequencing: An Emerging Tool for Drug Designing

BACKGROUND

With the outbreak of high throughput next-generation sequencing (NGS), the biological research of drug discovery has been directed towards the oncology and infectious disease therapeutic areas, with extensive use in biopharmaceutical development and vaccine production.

METHOD

In this review, an effort was made to address the basic background of NGS technologies, potential applications of NGS in drug designing. Our purpose is also to provide a brief introduction of various Nextgeneration sequencing techniques.

DISCUSSIONS

The high-throughput methods execute Large-scale Unbiased Sequencing (LUS) which comprises of Massively Parallel Sequencing (MPS) or NGS technologies. The Next geneinvolved necessarily executes Largescale Unbiased Sequencing (LUS) which comprises of MPS or NGS technologies. These are related terms that describe a DNA sequencing technology which has revolutionized genomic research. Using NGS, an entire human genome can be sequenced within a single day.

CONCLUSION

Analysis of NGS data unravels important clues in the quest for the treatment of various lifethreatening diseases and other related scientific problems related to human welfare.

Explaining cancer type specific mutations with transcriptomic and epigenomic features in normal tissues

Most cancer driver genes are involved in generic cellular processes such as DNA repair, cell proliferation and cell adhesion, yet their mutations are often confined to specific cancer types. To resolve this paradox, we explained mutation frequencies of selected genes across tumor types with four features in the corresponding normal tissues from cancer-free subjects: mRNA expression and chromatin accessibility of mutated genes, mRNA expressions of their neighbors in curated pathways and the protein-protein interaction network. Encouragingly, these transcriptomic/epigenomic features in normal tissues were closely associated with mutational/functional characteristics in tumors. First, chromatin accessibility was a necessary but not sufficient condition for frequent mutations. Second, variations of mutation frequencies in selected genes across tissue types were significantly associated with all four features. Third, the genes possessing significant associations between mutation frequency variations and pathway gene expression were enriched with documented cancer genes. We further proposed a novel bivariate gene set enrichment analysis and confirmed that the pathway gene expression was the dominant factor in cancer gene enrichment. These findings shed lights on the functional roles of genes in normal tissues in shaping the mutational landscape during tumor genome evolution.

CAG repeat polymorphisms in the androgen receptor and breast cancer risk in women: a meta-analysis of 17 studies

The association between polymorphic CAG repeats in the androgen receptor gene in women and breast cancer susceptibility has been studied extensively. However, the conclusions regarding this relationship remain conflicting. The purpose of this meta-analysis was to identify whether androgen receptor CAG repeat lengths were related to breast cancer susceptibility. The MEDLINE, PubMed, and EMBASE databases were searched through to December 2014 to identify eligible studies. Data and study quality were rigorously assessed by two investigators according to the Newcastle-Ottawa Quality Assessment Scale. The publication bias was assessed by the Begg’s test. Seventeen eligible studies were included in this meta-analysis. The overall analysis suggested no association between CAG polymorphisms and breast cancer risk (odds ratio [OR] 1.031, 95% confidence interval [CI] 0.855–1.245). However, in the subgroup analysis, we observed that long CAG repeats significantly increased the risk of breast cancer in the Caucasian population (OR 1.447, 95% CI 1.089–1.992). Additionally, the risk was significantly increased in Caucasian women carrying two alleles with CAG repeats ≥22 units compared with those with two shorter alleles (OR 1.315, 95% CI 1.014–1.707). These findings suggest that long CAG repeats increase the risk of breast cancer in Caucasian women. However, larger scale case-control studies are needed to validate our results.

Trinucleotide repeat expansions in human breast cancer-susceptibility genes: relevant targets for aspirin chemoprevention?

PURPOSE

Defining novel molecular mechanisms pertinent to aspirin chemoprevention of breast cancer (BC) and to explain controversial epidemiological results in this regard.

METHODS

Literature search in relevant databases with the following key words; aspirin, nucleotide repeat expansions, breast cancer. Human genome contains nucleotide repeat expansions and exon-1 of the androgen receptor gene AR contains a CAG string with an average of 20 repeats. Longer AR CAG repeats associate with lower AR protein functioning leading relatively higher estrogen receptor signals and higher risk of hormone receptor-positive BC. Nucleotide repeat expansions also exist in E2F4 and POLG genes in BC. In cell culture models, aspirin reduces CAG.CTG expansions in kidney cells and restores myogenic differentiation in cells obtained from tissues with myotonic dystrophy, a disorder caused by large CTG expansions.

CONCLUSIONS

We hypothesize that aspirin reduction of trinucleotide repeat expansions in breast cancer-susceptibility genes may be one of the relevant mechanisms of its chemopreventive effects.

Clinical applications of next generation sequencing in cancer: from panels, to exomes, to genomes

This article will review recent impact of massively parallel next-generation sequencing (NGS) in our understanding and treatment of cancer. While whole exome sequencing (WES) remains popular and effective as a method of genetically profiling different cancers, advances in sequencing technology has enabled an increasing number of whole-genome based studies. Clinically, NGS has been used or is being developed for genetic screening, diagnostics, and clinical assessment. Though challenges remain, clinicians are in the early stages of using genetic data to make treatment decisions for cancer patients. As the integration of NGS in the study and treatment of cancer continues to mature, we believe that the field of cancer genomics will need to move toward more complete 100% genome sequencing. Current technologies and methods are largely limited to coding regions of the genome. A number of recent studies have demonstrated that mutations in non-coding regions may have direct tumorigenic effects or lead to genetic instability. Non-coding regions represent an important frontier in cancer genomics.

Changing genetic paradigms: creating next-generation genetic databases as tools to understand the emerging complexities of genotype/phenotype relationships

Understanding genotype/phenotype relationships has become more complicated as increasing amounts of inter- and intra-tissue genetic heterogeneity have been revealed through next-generation sequencing and evidence showing that factors such as epigenetic modifications, non-coding RNAs and RNA editing can play an important role in determining phenotype. Such findings have challenged a number of classic genetic assumptions including (i) analysis of genomic sequence obtained from blood is an accurate reflection of the genotype responsible for phenotype expression in an individual; (ii) that significant genetic alterations will be found only in diseased individuals, in germline tissues in inherited diseases, or in specific diseased tissues in somatic diseases such as cancer; and (iii) that mutation rates in putative disease-associated genes solely determine disease phenotypes. With the breakdown of our traditional understanding of genotype to phenotype relationships, it is becoming increasingly apparent that new analytical tools will be required to determine the relationship between genotype and phenotypic expression. To this end, we are proposing that next-generation genetic database (NGDB) platforms be created that include new bioinformatics tools based on algorithms that can evaluate genetic heterogeneity, as well as powerful systems biology analysis tools to actively process and evaluate the vast amounts of both genomic and genomic-modifying information required to reveal the true relationships between genotype and phenotype.