Single-Cell RNA Sequencing of Ovarian Cancer: Promises and Challenges

Shobhana Talukdar, Zenas Chang, Boris Winterhoff, Timothy K. Starr

Research output: Chapter in Book/Report/Conference proceedingChapter

3 Scopus citations

Abstract

Ovarian cancer remains the leading cause of death from gynecologic malignancy in the Western world. Tumors are comprised of heterogeneous populations of various cancer, immune, and stromal cells; it is hypothesized that rare cancer stem cells within these subpopulations lead to disease recurrence and treatment resistance. Technological advances now allow for the analysis of tumor genomes and transcriptomes at the single-cell level, which provides the resolution to potentially identify these rare cancer stem cells within the larger tumor. In this chapter, we review the evolution of next-generation RNA sequencing techniques, the methodology of single-cell isolation and sequencing, sequencing data analysis, and the potential applications in ovarian cancer. We also summarize the current published work using single-cell sequencing in ovarian cancer. By utilizing this novel technique to characterize the gene expression of rare subpopulations, new targets and treatment pathways may be identified in ovarian cancer to change treatment paradigms.

Original languageEnglish (US)
Title of host publicationAdvances in Experimental Medicine and Biology
PublisherSpringer
Pages113-123
Number of pages11
DOIs
StatePublished - 2021

Publication series

NameAdvances in Experimental Medicine and Biology
Volume1330
ISSN (Print)0065-2598
ISSN (Electronic)2214-8019

Bibliographical note

Publisher Copyright:
© 2021, Springer Nature Switzerland AG.

Keywords

  • Gene expression
  • Next generation RNA sequencing
  • Ovarian cancer
  • Rare cancer stem cells
  • Rare cancer subpopulations
  • Single cell isolation
  • Single cell sequencing
  • Treatment
  • Humans
  • Neoplasm Recurrence, Local
  • Ovarian Neoplasms/genetics
  • Neoplastic Stem Cells
  • Sequence Analysis, RNA
  • Carcinoma, Ovarian Epithelial
  • Female

PubMed: MeSH publication types

  • Review
  • Journal Article

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