Cancer whole-genome sequencing (WGS) with next-generation sequencing (NGS) provides a base-by-base view of the unique mutations present in cancer tissue. It enables 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 changes to a specific tumor DNA sample compared to normal DNA. As a hypothesis-free approach, cancer WGS is well-suited for comparing tumor vs. matched normal samples and discovering novel cancer driver mutations.
Cancer genomes typically contain unpredictable numbers of point mutations, fusions, and other aberrations. Since many of these alterations may be novel, and may not reside in coding regions, cancer WGS offers the most comprehensive approach for variant identification. In contrast, targeted approaches like exome sequencing may miss certain variants such as those outside coding regions.
WGS provides base-pair resolution of an entire cancer genome in a single run. The method offers a comprehensive view of the unique mutations and genomic alterations in cancer tissue, including those contributed by surrounding normal tissue and tumor clonality.
Researchers in India use whole-genome sequencing and other methods to uncover somatic and germline variants that may influence a deadly oral cancer.
WGS allows researchers to examine nucleosome patterns and infer the gene expression status of cancer driver genes in cell-free DNA.
Cancer researchers utilize WGS and other NGS methods to identify cancer-associated variants in exosomal DNA and RNA.
Researchers from Washington University in St. Louis found that using WGS to assess samples from acute myeloid leukemia and myelodysplastic syndrome patients produced more accurate results, in less time, than karyotyping or fluorescence in situ hybridization (FISH), two prevalent standard-of-care techniques.
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.
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Learn how to analyze and visualize large tumor-normal whole-genome sequencing data sets, and see data analysis examples.
This tutorial describes how to log into BaseSpace Sequence Hub to access tumor sequencing data. It also describes the data contained within each section.View Tutorial
This tutorial reviews the findings in the Somatic Summary Report produced by the BaseSpace Tumor-Normal Sequencing App.View Tutorial
This tutorial demonstrates how to load tumor-normal sequencing data into the BaseSpace Integrative Genomics Viewer app.View Tutorial
This tutorial shows how to visualize variants identified between tumor and normal samples. This example highlights an indel in TP53 and a translocation between chromosomes 1 and 8.View Tutorial
Visit BaseSpace Sequence Hub Data Central and use the tumor-normal filter to see example data. Note that access to this data requires a login. Register for an account.View Sample Data
Learn how to visualize tumor-normal sequencing data in BaseSpace Sequence Hub.Read Technical Note
Dr Torsten Haferlach of Munich Leukemia Laboratory discusses research plans to perform whole-genome sequencing of 5,000 samples from individuals with different kinds of leukemias and lymphomas. Their goal is to gain a better understanding of cancer subtypes and discover potential new therapeutic pathways.
Illumina offers several library preparation, sequencing, and data analysis options for cancer whole-genome sequencing and tumor-normal comparisons. Streamlined library prep workflows and flexible kit configurations accommodate multiple study designs.
Approximately 90% of the world’s sequencing data are generated using Illumina sequencing by synthesis (SBS) chemistry*. Push-button tools simplify data analysis, so you can spend less time analyzing data and more time focusing on the next breakthrough.
Click on the below to view products for each workflow step.
A fast, integrated workflow for a wide range of applications, from human whole-genome sequencing to amplicons, plasmids, and microbial species.TruSeq DNA PCR-Free Library Prep Kit
Provides high genomic coverage even in challenging regions.
Enables efficient interrogation of samples with limited available DNA.
A high-performing, fast, and integrated workflow for sensitive applications such as tumor-normal variant identification or human whole-genome sequencing.
Scalable throughput and flexibility for virtually any genome, sequencing method, and scale of project.
Compare sequencers by application and specification. Find tools and guides to help you choose the right instrument.
Rapidly identifies somatic variants from tumor-normal pairs or tumor-only samples.BaseSpace Tumor-Normal Sequencing App
Designed to detect somatic variants from tumor and matched normal sample pairs.Illumina DRAGEN Bio-IT Platform
Accurate, ultra-rapid analysis of NGS data from whole genomes, with apps for germline and somatic data. Available on-premise or in BaseSpace Sequence Hub.
The Illumina genomics computing environment for NGS data analysis and management.BaseSpace Correlation Engine
A growing library of curated genomic data to support researchers in identifying disease mechanisms, drug targets, and prognostic or predictive biomarkers.
While placing its 1,000th NovaSeq 6000 System, Illumina announced another historic milestone: the $600 genome. This achievement helps make deeper discoveries more accessible than ever.
CRISPR-Cas9 genome editing allows scientists to mutate, silence, induce, or replace genes and genetic elements. This technology enables a broad range of applications, including cancer-related studies such as interrogating tumor suppressor gene, oncogene, and immune response checkpoint gene function. Whole-genome and targeted sequencing can be used to check off-target effects and confirm specificity.Learn More
Collaborative efforts to characterize mutations and other genomic abnormalities in cancer include:
*Data calculations on file. Illumina, Inc., 2015