Research

Continuing advances in high-throughput genomic technologies and tools provide researchers an increasingly more detailed view of the genetic alterations found in cancers.

CGCI researchers primarily use sequencing and, in some cases, other genome-based approaches to examine genomes and transcriptomes of tumors. With this type of in-depth analysis, they are able to detect cancer-associated alterations ranging from genomic rearrangements and gene expression variation to single nucleotide mutations. By uncovering the full spectrum of alterations in tumors, CGCI researchers may then help elucidate which physiological pathways are disrupted in cancer. Finding the underlying molecular causes of cancer will likely inform better treatment strategies.

Read below to learn about CGCI’s genomic approaches and the type of genetic information they provide:

  • Whole Genome Sequencing
    • Provides the DNA sequence of the entire genome
    • Helps identify structural alterations, such as translocations and inversions, as well as insertion and deletions (indels) and single point mutations
       
  • Whole Exome Sequencing (2nd generation)
    • Provides DNA sequence of the exome, almost all of the known protein-coding regions of the genome
    • Helps identify a variety of focused alterations, including indels and single point mutations, in genes
       
  • Transcriptome Sequencing (2nd generation)
    • Provides sequences from transcribed genes (mRNA-seq) and/or from small regulatory RNAs known as microRNAs (miRNA-seq)
    • Identifies mutations in the protein-coding regions of the genome and a variety of alterations, including novel gene fusions, alternatively spliced isoforms, and variations in gene expression
       
  • Gene Sequencing (Sanger)
    • Provides DNA sequences of genes
    • Helps identify various types of alterations in specific genes, which may be correlated to changes in gene expression
       
  • Gene Expression Profiling
    • Determines the pattern of gene expression by surveying mRNAs levels on high density microarrays
    • Helps identify variations in gene expression, which may be correlated to mutations identified through sequencing
       
  • Copy Number Analysis (SNP arrays)
    • Determines structural alterations of the genome that results in copy number variation, which includes the loss of heterozygosity
    • Helps identify copy number variation
Last updated: November 03, 2015