Cancer Whole-Genome Sequencing

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Genome-wide comparisons of cancer vs matched normal DNA

Cancer whole-genome sequencing (WGS) with next-generation sequencing (NGS) provides a base-by-base view of the unique mutations present in cancer tissues. It enables the discovery of novel cancer-associated variants, including single nucleotide variants (SNVs), copy number changes, insertions/deletions (indels), and structural variants. Many cancer-associated variants have been discovered using cancer genome sequencing. WGS also provides a comprehensive view of genomic changes in cancer DNA samples compared to normal DNA.

Cancer genomes typically contain unpredictable numbers of point mutations, fusions, and other aberrations. Since many of these alterations may be novel and not reside in coding regions, cancer WGS offers the most comprehensive approach for variant identification. In contrast, targeted approaches like exome sequencing may miss specific variants, such as those outside coding regions.

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Benefits of WGS over targeted molecular panels in cancer research

  • Assesses the full genomic backbone of an organism or tissue for unbiased analysis and potential discovery of novel cancer-associated genes
  • Detects genomic signatures that may not yet be linked to cancer phenotypes
  • Discovers non-coding regions of the genome that may influence cancer progression
  • Uncovers genome-wide integration sites of oncogenic viruses

Learn more about whole-genome sequencing

Tumor-normal sequencing

Through tumor-normal whole-genome sequencing, researchers can compare tumor mutations to a matched normal sample. Tumor-normal comparisons are crucial for identifying the somatic variants that act as driver mutations in cancer progression.

Illumina offers push-button tools to facilitate analysis of tumor-normal WGS data.

Learn more about:

  • DRAGEN Secondary Analysis: Accurate, ultra-rapid analysis of WGS data and other NGS data, on-premise or in the cloud, with somatic, germline, and other app options
  • DRAGEN Somatic Pipeline: This pipeline includes tumor-only and tumor–normal modes, designed for detecting somatic variants in tumor samples. Both modes make no ploidy assumptions, enabling detection of low-frequency alleles.
  • BaseSpace Sequence Hub: An economical and powerful cloud computing environment to manage, analyze, and share NGS data.
Population-based metrics to stratify somatic variant calling performance

This research article outlines a method that empirically defines regions of the genome with systematically high or low quality in a cohort of samples and its application for cancer variant calling in WGS data.

Read article

Characterizing the non-coding cancer genome

This on-demand webinar discusses detecting mutations in non-coding regions and the effects of these alterations using functional genomics methods. This webinar also covers integration of DNA sequencing with other techniques, such as RNA sequencing and ATAC-seq, to evaluate transcriptomic and epigenomic features.

Watch on-demand webinar

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Related cancer research resources

Cancer Research Guide

The Cancer Research Guide is a 40+ page comprehensive resource covering cancer research topics, sequencing methods, solutions, and more.

NEJM study shows whole-genome sequencing improves molecular profiling

Side-by-side comparison shows WGS produced more accurate results in less time and at a similar cost than other standard techniques.

Shining a light on cancer of unknown primary

How whole-genome sequencing brings hope for awareness, education, and research on cancer of unknown primary (CUP).

Genomics and transcriptomics basics

Download the infographic to learn the basics of genome and transcriptome sequencing at a glance.

Sequencing DNA and RNA from the same sample

Watch the new in-lab quick start video to learn how to prepare high quality DNA and RNA samples for multiomic sequencing.

Advancing cancer research with multiomics

Learn how to link the causes and consequences of complex phenotypes through multiomics to enable discoveries that weren’t possible before.