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Integrated Omics Technology for Basic and Clinical Research
Published in Jyoti Ranjan Rout, Rout George Kerry, Abinash Dutta, Biotechnological Advances for Microbiology, Molecular Biology, and Nanotechnology, 2022
Kuldeep Giri, Vinod Singh Bisht, Sudipa Maity, Kiran Ambatipudi
The technologies used for sequencing are pilots for genomic medicine. The whole-genome sequencing (WGS) or whole-exome sequencing (WES), collectively known as NGS, analyzes a single nucleotide base of a genome/ exome, has gained momentum over the GWAS studies. The NGS approach parallelizes the process of sequencing by producing a huge (millions) sequence in a very rapid and profitable way. It allows the analysis of the whole genome and genetic bases for diseases in unprecedented ways (Behjati and Tarpey, 2013). By NGS approach massive production of short sequences with multiple DNA (mtDNA) fragments is generated in sufficient quantity to redundantly represent every base in the target genome. Researchers use WGS to identify CNVs, disease genes, small insertions and/or deletions, single nucleotide variants, and diseases related to structural chromosomal anomalies with higher sensitivity (McCarthy et al., 2013). The applications and workflow of NGS are shown in Figure 14.5.
From Single Level Analysis to Multi-Omics Integrative Approaches: A Powerful Strategy towards the Precision Oncology
Published in Shaker A. Mousa, Raj Bawa, Gerald F. Audette, The Road from Nanomedicine to Precision Medicine, 2020
Maria Eugenia Gallo Cantafio, Katia Grillone, Daniele Caracciolo, Francesca Scionti, Mariamena Arbitrio, Vito Barbieri, Licia Pensabene, Pietro Hiram Guzzi, Maria Teresa Di Martino
DNA sequencing technologies now allow targeted or whole exome sequencing (WES) and whole genome sequencing (WGS) of multiple tumors to identify genetic alterations. WES investigates the coding regions of the genome, whereas WGS focuses on the entire DNA sequence. In both, the tumor genome is compared with a patient’s germline sequence or a reference genome, thus parallel data capture and analysis is needed to classify variants as germline and somatic. Many reports demonstrate the power of massively parallel sequencing. For example, Wedge and colleagues [5] sequenced the whole genomes of 112 primary and metastatic prostate cancer samples. They identified 28 genes with an excess of coding driver mutations, five of which (TBL1XR1, ZMYM3, IL6ST, CASZ1, and TBX3) were previously unknown drivers in prostate cancer. They also reported loss of CHD1 and BRCA2 as early events in cancer development of ETS fusion-negative cancers and losses of CDH12 and ANTXR2 were associated with poorer recurrence-free survival. In addition, Miao and colleagues [6] analyzed the WES of 249 tumors and matched normal tissues from patients with clinically annotated outcomes to immune checkpoint therapy. They found that clonal driver alterations in PIK3CA and KRAS were enriched in patients with complete or partial response to treatment, while clonal driver mutations in EGFR were enriched in patients with progressive disease.
From Single Level Analysis to Multi-Omics Integrative Approaches: A Powerful Strategy towards the Precision Oncology
Published in Shaker A. Mousa, Raj Bawa, Gerald F. Audette, The Road from Nanomedicine to Precision Medicine, 2019
Maria Eugenia Gallo Cantafio, Katia Grillone, Daniele Caracciolo, Francesca Scionti, Mariamena Arbitrio, Vito Barbieri, Licia Pensabene, Pietro Hiram Guzzi, Maria Teresa Di Martino
DNA sequencing technologies now allow targeted or whole exome sequencing (WES) and whole genome sequencing (WGS) of multiple tumors to identify genetic alterations. WES investigates the coding regions of the genome, whereas WGS focuses on the entire DNA sequence. In both, the tumor genome is compared with a patient’s germline sequence or a reference genome, thus parallel data capture and analysis is needed to classify variants as germline and somatic. Many reports demonstrate the power of massively parallel sequencing. For example, Wedge and colleagues [5] sequenced the whole genomes of 112 primary and metastatic prostate cancer samples. They identified 28 genes with an excess of coding driver mutations, five of which (TBL1XR1, ZMYM3, IL6ST, CASZ1, and TBX3) were previously unknown drivers in prostate cancer. They also reported loss of CHD1 and BRCA2 as early events in cancer development of ETS fusion-negative cancers and losses of CDH12 and ANTXR2 were associated with poorer recurrence-free survival. In addition, Miao and colleagues [6] analyzed the WES of 249 tumors and matched normal tissues from patients with clinically annotated outcomes to immune checkpoint therapy. They found that clonal driver alterations in PIK3CA and KRAS were enriched in patients with complete or partial response to treatment, while clonal driver mutations in EGFR were enriched in patients with progressive disease.
Surveillance in Next-Generation Personalized Healthcare: Science and Ethics of Data Analytics in Healthcare
Published in The New Bioethics, 2021
Next-generation sequencing (NGS) has the potential to conduct several activities, including disease detection and the identification of pharmacogenetics markers that allow for treatment customization. Additionally, NGS has been used in the study of Mendelian monogenic disorders and the study of cancer, and cardiac diseases. NGS is the most preferred for the aforementioned conditions mainly due to its ability to test several genes over a relatively short period of time and with manageable cost (Morini et al. 2015). Several companies are also offering NGS solutions in the form of whole-genome sequencing and targeted NGS panels. Whole-genome sequencing involves the sequencing of the entire genome to determine the presence of genomic variants that inform the diagnosis of unique monogenic conditions. Targeted NGS panels, on the other hand, sequence a specific set of clinically relevant genes, which are associated with certain conditions (Milner et al. 2015). Today, studies that are investigating cancer are adopting this technology due to its ability to detect high number of variants associated with tumour heterogeneity (Martinez and Magnus 2019).
Discovery of genetic risk factors for disease
Published in Journal of the Royal Society of New Zealand, 2018
We have witnessed remarkable progress in genetic mapping methods over the last 25 years, with hundreds of diseases causing mutations and thousands of genomic regions contributing to risk for complex diseases identified. The discovery of highly polymorphic microsatellite markers in the 1980s enabled family-based linkage studies with power to discover genes and mutations responsible for Mendelian diseases. Linkage analysis using these markers became the primary tool for mapping Mendelian traits (Ott et al. 2015). The method continues to be useful now, employing whole genome sequencing to identify rare variants associated with disease (Ott et al. 2015). In contrast, genetic variants contributing to complex diseases confer a modest increase in susceptibility rather than the large increase in risk generally observed for mutations responsible for Mendelian diseases. Consequently, linkage mapping methods lack power to detect genetic factors influencing many common diseases.