Center for Cancer Genome Discovery (DFCI)
Director: Van Hummelen, Paul, Ph.D.; Hahn, William, M.D., Ph.D.; Meyerson, Matthew L., M.D., Ph.D.
The mission of CCGD is to advance precision cancer medicine by developing new technologies for the analysis of cancer genomes and to provide access to these technologies to basic, translational, and clinical investigators. There are three main components:
Technology development: To develop new technologies for the analysis of cancer genomes
Collaborations: To provide access to these genomic technologies to basic, translational, and clinical investigators at DFCI and beyond
Translation: To translate technologies to the clinical setting
CCGD’s services are based on Next Generation Sequencing using the Illumina Hiseq3000, Hiseq2500, and Miseq. Our next-generation sequencing platforms allow for the detection of the full range of genomic alterations, including mutations, structural rearrangements, copy number, and expression changes.
Structure of the Center:
William Hahn, MD, PhD, CCGD Director, Associate Professor of Medicine, Harvard Medical School
Matthew Meyerson, MD, PhD, CCGD Director, Professor of Pathology, Harvard Medical School
Laura MacConaill, PhD, CCGD Scientific Director
Paul Van Hummelen, PhD, CCGD Associate Director
Director: Van Hummelen, Paul, Ph.D.
Director: Hahn, William, M.D., Ph.D.
Phone: (617) 632-2641
Director: Meyerson, Matthew L., M.D., Ph.D.
Phone: (617) 632-4768
Thorner, Aaron, Ph.D.
Role: Group Leader
Role: BioInformatics Group Leader
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- HiSeq 2500
- HiSeq 3000
- Amplicon sequencing
Amplicon-seq is a different targeted approach enabling detection of genetic variants, including somatic mutations, SNPs, and small insertions and deletions, in a selected set of amplicons in a rapid and efficient manner. It allows sequencing of a large number of samples for specific genes or exons of particular interest rather than whole genomes. Amplicon-seq is ideal for very small gene panels (~10 genes) and for fast turn-around-time.
Bioinformatics is a joint CCGD and PROFILE (www.dana-farber.org/Research/Featured-Research/Profile-Somatic-Genotyping-Study.aspx) team. The group consists of data analysts, software engineers, and computational biologists and has developed analytical pipelines to manage, store, annotate, and report on data produced by the Illumina sequencing platforms. We employ a combination of vendor, third-party, and in-house tools and databases to provide data quality metrics, integrated candidate reports, and relevant biological and clinical context for experimental platform data. We also develop new tools and strategies in a research setting that are then translated to the clinic. In addition to standard sequence analyses, the team is developing methods to analyze samples derived from PDX models, cell-free DNA, and single cell sequencing.
The bioinformatics team can provide help in:
* Variant detection
* Variant annotation
* Genome and transcriptome analysis
* Allele specific expression
* Analysis of PDX models, cell-free DNA, and single cell
* Sample QC evaluation and troubleshooting
* Customized analyses based on the specific needs of your project
- DNA sequencing
DNA can be sequenced on different scales. We can sequence the complete genome (WGS) or we can limit the space to only the expressed portion of the genome by sequencing the whole exome (WES) or any smaller set of genes (Targeted Seq).
The current WES baitset used at CCGD is the Whole Exome_v5 Agilent SureSelect hybrid capture kit covering ~55Mb. Our hybrid selection libraries typically meet or exceed 80% of targets at 30x and a mean target coverage >150x.
Targeted sequencing can be accomplished using our cancer research panel Oncopanel_version3 (OPv3), the PROFILE cancer panel (POPv2), or any custom gene panel.
* OPv3 is a new and improved targeted design that is capable of simultaneous detection of mutations, translocations, and copy-number variations in archival clinical tumor specimens. The baitset contains sequences complementary to exons of 559 genes and to 37 intronic regions frequently involved in rearrangements. In addition, baits were included that are complementary to common SNPs and for cancer risk factors determined by GWAS studies (www.genome.gov/gwastudies).
* POPv2 is the gene panel that is used in the clinic as part of the PROFILE effort. This panel contains 309 genes and regions frequently involved in rearrangements in 35 genes.
* Custom gene panel are often more affordable and can be tailored for your research.
DNA sequencing can provide information on:
* Somatic mutations and germline variants, including single nucleotide variants and small insertions and deletions.
* Copy number variants, gene deletions/amplifications, loss of heterozygosity
* Genomic rearrangements, including translocations, inversions, large deletions/insertions, and other complex rearrangements
* Sample identification and T/N matching via DNA Finger Printing
- Experimental design and sample handling
Before starting a project we will discuss the best sequencing strategies, experimental design, and analysis options with you. It is important that we understand the goals and scope of the project and that you appreciate the power and limitations of the technology and the expected outcome. CCGD will also organize follow-up meetings to transfer the data and discuss the results and conclusions. At that time, future experiments can be discussed if needed.
CCGD has expertise in handling and extracting DNA from challenging FFPE tissue. We have developed and optimized extraction protocols using the Qiagen QIAcube or the Covaris LE220 Focused-ultrasonicator. For specimens needing pathology review, we have ongoing collaborations with pathologists at Brigham and Women’s Hospital.
CCGD has optimized protocols on both the Illumina HiSeq and MiSeq to process and sequence from as little as 50-200 ng of DNA from fresh frozen, blood, or formalin-fixed paraffin embedded tissue (FFPE). CCGD’s major strength is on smaller, focused projects consisting of challenging or unique samples.
- RNA sequencing - Transcriptomics
RNA sequencing (RNAseq) is an approach for transcriptome profiling that uses deep-sequencing technologies. In conjunction with mutation detection it can functionally validate mutations found by DNA sequencing by monitoring the change in expression of the mutant allele or downstream genes in the pathway. Compared to expression microarrays, RNA sequencing is not limited by the microarray content, therefore allowing discovery of novel mutations and isoforms with greater accuracy. Similar to DNAseq we can sequence the whole transcriptome or focus on specific genes using Targeted RNAseq.
RNA sequencing can provide information on:
* Gene expression, including miRNA and non-coding RNA
* Allele-specific expression (preferential expression of mutant or WT transcript)
* Expression of splice variants
* Gene fusions
|Departmental Web Link(s):|