Goals of the Initiative
TARGET researchers use various sequencing and array-based methods to examine the genomes, transcriptomes, and for some diseases epigenomes of select childhood cancers. This “multi-omic” approach generates a comprehensive profile of molecular alterations for each cancer type. Alterations are changes in DNA or RNA, such as rearrangements in chromosome structure or variations in gene expression, respectively. Through computational analyses and assays to validate biological function, TARGET researchers predict which alterations disrupt the function of a gene or pathway and promote cancer growth, progression, and/or survival. Researchers identify candidate therapeutic targets and/or prognostic markers from the cancer-associated alterations.
To learn about individual sequencing and array-based methods used in TARGET research, visit Methods below.
TARGET project teams have characterized “discovery” cohorts of patient cases to identify molecular alterations of the transcriptome, genome, and epigenome in various pediatric cancer subtypes. Each project team independently selected their patient cohorts based upon characteristics of the disease or cancer subtype*. A comprehensive genomic profile of each patient case was generated using nucleic acids from tumor tissue taken at the time of diagnosis and case-matched “normal” tissue. Whenever available, case-matched tissues from relapsed or treatment-resistant tumors were also characterized by the same methods. Robust clinical data were obtained for each case studied in TARGET. All tissues used meet strict scientific, technical, and ethical requirements.
TARGET project teams employed multiple technologies to confirm the presence of mutations found in tumor tissue. The use of diverse sequencing approaches (e.g. mRNA-seq, whole exome or whole genome sequencing) to analyze discovery samples provided confirmation of somatic mutation(s) observed in a patient case and affirmed the quality of each data type generated. Individual project teams also analyzed a subset of their discovery cases using the method(s) employed for validation*.
TARGET project teams used a separate sequencing method applied to an independent cohort of patients to validate at the gene level most candidate mutations found in the TARGET discovery data. Validation confirmed the population prevalence of mutations. Within each disease, characterizing a separate cohort more broadly representative of the disease population further allowed the project teams to estimate the frequency of somatic variants in a given cancer subtype.
*Note: Users can find details regarding discovery, verification, and validation by clicking on the project page for the disease of interest and reading the ‘experimental approaches’ section.
Each project team uses a large subset of the methods below. Visit the TARGET Project Experimental Methods page for detailed protocols and to learn which methods apply for each individual project.
- Gene expression profiling: determines patterns of all genes transcribedOpens in a New Tab
- Copy number analysis: determines structural changes of chromosomes, such as copy number alterations (chromosome region gains and losses) including the loss of heterozygosityOpens in a New Tab and translocations
- DNA methylation status: determines patterns of DNA (cytosine) methylationOpens in a New Tab on chromosomes
- miRNA profiling: determines expression patterns of small regulatory molecules called microRNAsOpens in a New Tab (miRNAs)
- Targeted Sequencing: DNA sequencing of specific genes or areas of the genome
- Kinome Sequencing: DNA sequencing of genes encoding kinases
- Whole Genome Sequencing: provides the DNA sequence of the genomeOpens in a New Tab
- Whole Exome Sequencing: provides DNA sequences of exonsOpens in a New Tab
- Transcriptome Sequencing (RNA-seq): provides sequences from transcribed RNAs
- Bisulfite sequencing: identifies pattern of methylation of individual cytosines in DNA within a defined area of the genome (i.e. epigenome)
- ChIP sequencing: identifies protein interactions with DNA of the genome