Whole Genome Analysis With the advent of next-generation sequencing, the genome-wide sequencing analyses have been made more accessible to thoroughly understand the genetics of each patient's cancer. Genetic material from tumour biopsies can be analyzed by two genome-wide approaches: whole exome sequencing (WES) and whole genome sequencing (WGS). By developing tools to analyze these extensive sequence data, scientists have begun to comprehend how diseases, including cancer, can be attributed by genes and intergenic variants such as single nucleotide polymorphisms (SNPs) and copy number variants (CNVs). Although more expensive than WES, whole genome sequencing allows clinical scientists to understand how cancer can be caused by alterations in a genome including single nucleotide variants (SNVs), SNPs and CNVs. Since WES samples only the exome (the collection of known coding regions of the genome) alterations in the non-coding region of the genome will not be detected by WES. Non-coding regions, including untranslated regions, introns, promoters, regulatory elements, non-coding functional RNA, repetitive regions, and mitochondrial genomes, make up 98% of the human genome, the function of most regions remains unexplored. Although these methods are useful in finding shorter variants, they are limited by read lengths of sequencing technology and are unable to detect large indels and structural variants. Though variants in a non-coding region are not uncovered by WES, both approaches identify all mutations that are known to cause cancer in a given patient and have been helpful in identifying low frequency and rare pathogenic (disease-causing) variants. However, the challenge remains in analyzing all the genetic variations in a genome for the clinical significance (whether a mutation is disease-causing as not all mutations are harmful) as much of the genome is not thoroughly understood, and new variants are still being discovered. To better understand the pathogenicity of all possible<unk> variants to interpret WES/WGS data, researchers are systematically studying genome-wide sequencing data across many tumour genomes. Whole exome sequencing has been the conventional data used by international cancer genome research programs such as The Cancer Genome Atlas (TCGA) and The International Cancer Genome Consortium (ICGC). These studies have accumulated WES data for all types of human tumours and have been an open resource for clinical scientists. Systematically analyzing more than 50,000 tumour genomes has elucidated new cancer genes and pathways, opening up new pursuits for pharmaceutical companies. Researchers have also discovered general trends on different types of cancer that may inform public education on proactive preventative measures. For example, more somatic mutations in coding regions are found in carcinogen-exposed cancers than in pediatric tumours and leukemia. Although these systematic studies provide extensive mutational data on coding regions, information is limited on somatic mutations in non-coding regions. Researchers have only recently started to be illuminated on how cancer may be caused by variants in the non-coding regions of the genome. In 2018, Zhang and colleagues analyzed 930 tumour whole genomes with associated transcriptomes (collection of mRNA transcripts) to show mutations in 193 non-coding sequences disrupt normal gene expression. Notably, they repetitively found noncoding mutations affected DAAM1, MTG2, and HYI transcription wherein DAAM1 expression initiate invasive cell migration in the tumour. Since the core somatic gene expression network is defective in 88% tumours, Zhang et al. suggested that noncoding mutation may have a widespread impact in cancer. As the cost of sequencing decreases and sequence analytic pipeline optimizes, researchers are looking to expand cancer<unk> knowledge with WGS. Nonetheless, WES may remain effective for clinical diagnosis in the next few years as WES results are obtained faster.
Personalized onco-genomics
Predictive medicine
Individualized cancer immunotherapy
Cancer systems biology
Neoadjuvant therapy
Regenerative medicine
Stem cell tourism
Personal genomics