Next-Generation Sequencing

Adv Exp Med Biol. 2017:943:119-148. doi: 10.1007/978-3-319-43139-0_5.

Abstract

Endometrial cancers are the most frequently diagnosed gynecological malignancy and were expected to be the seventh leading cause of cancer death among American women in 2015. The majority of endometrial cancers are of serous or endometrioid histology. Most human tumors, including endometrial tumors, are driven by the acquisition of pathogenic mutations in cancer genes. Thus, the identification of somatic mutations within tumor genomes is an entry point toward cancer gene discovery. However, efforts to pinpoint somatic mutations in human cancers have, until recently, relied on high-throughput sequencing of single genes or gene families using Sanger sequencing. Although this approach has been fruitful, the cost and throughput of Sanger sequencing generally prohibits systematic sequencing of the ~22,000 genes that make up the exome. The recent development of next-generation sequencing technologies changed this paradigm by providing the capability to rapidly sequence exomes, transcriptomes, and genomes at relatively low cost. Remarkably, the application of this technology to catalog the mutational landscapes of endometrial tumor exomes, transcriptomes, and genomes has revealed, for the first time, that serous and endometrioid endometrial cancers can be classified into four distinct molecular subgroups. In this chapter, we overview the characteristic genomic features of each subgroup and discuss the known and putative cancer genes that have emerged from next-generation sequencing of endometrial carcinomas.

Keywords: Cancer; Endometrial; Exome; Genetic; Genomic; Mutation; Next-generation sequencing; Uterine.

Publication types

  • Review

MeSH terms

  • Endometrial Neoplasms / classification
  • Endometrial Neoplasms / genetics*
  • Exome / genetics*
  • Female
  • Genetic Predisposition to Disease / genetics
  • Genome, Human / genetics*
  • Genomics / methods
  • Genomics / trends
  • High-Throughput Nucleotide Sequencing / methods*
  • High-Throughput Nucleotide Sequencing / trends
  • Humans
  • Mutation
  • Transcriptome / genetics*