page_title: Cancer genome sequencing
section_title: Data Analysis
hierarchical_section_title: Cancer genome sequencing / Data Analysis
caption_attribution_description: English: A figure illustrating the process of sequencing the genome of a tumor for the purposes of developing a rational therepy.
context_page_description: Cancer genome sequencing is the whole genome sequencing of a single, homogeneous or heterogeneous group of cancer cells. It is a biochemical laboratory method for the characterization and identification of the DNA or RNA sequences of cancer cell.
  Unlike whole genome sequencing which is typically from blood cells, such as J. Craig Venter's and James D. Watson’s WG sequencing projects, saliva, epithelial cells or bone - cancer genome sequencing involves direct sequencing of primary tumor tissue, adjacent or distal normal tissue, the tumor micro environment such as fibroblast/stromal cells, or metastatic tumor sites.
  Similar to whole genome sequencing, the information generated from this technique include: identification of nucleotide bases, copy number and sequence variants, mutation status, and structural changes such as chromosomal translocations and fusion genes.
  Cancer genome sequencing is not limited to WG sequencing and can also include exome, transcriptome, micronome sequencing, and end-sequence profiling. These methods can be used to quantify gene expression, miRNA expression, and identify alternative splicing events in addition to sequence data.
context_section_description: As with any genome sequencing project, the reads must be assembled to form a representation of the chromosomes being sequenced. With cancer genomes, this is usually done by aligning the reads to the human reference genome.
  Since even non-cancerous cells accumulate somatic mutations, it is necessary to compare sequence of the tumor to a matched normal tissue in order to discover which mutations are unique to the cancer. In some cancers, such as leukemia, it is not practical to match the cancer sample to a normal tissue, so a different non-cancerous tissue must be used.
  It has been estimated that discovery of all somatic mutations in a tumor would require 30-fold sequencing coverage of the tumor genome and a matched normal tissue. By comparison, the original draft of the human genome had approximately 65-fold coverage.
  A major goal of cancer genome sequencing is to identify driver mutations: genetic changes which increase the mutation rate in the cell, leading to more rapid tumor evolution and metastasis. It is difficult to determine driver mutations from DNA sequence alone; but drivers tend to be the most commonly shared mutations amongst tumors, cluster around known oncogenes, and are tend to be non-silent. Passenger mutations, which are not important in the progression of the disease, are randomly distributed throughout the genome. It has been estimated that the average tumor carries c.a. 80 somatic mutations, fewer than 15 of which are expected to be drivers.
  A personal-genomics analysis requires further functional characterization of the detected mutant genes, and the development of a basic model of the origin and progression of the tumor. This analysis can be used to make pharmacological treatment recommendations. As of February 2012, this has only been done for patients clinical trials designed to assess the personal genomics approach to cancer treatment.
caption: The work-flow of the sequencing of a tumor from biopsy to treatment recommendation.
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