Translating Cancer Molecular Variability into Personalized Information Using Bulk and Single Cell Approaches

Nataly Kravchenko-Balasha*

*Corresponding author for this work

Research output: Contribution to journalReview articlepeer-review

10 Scopus citations

Abstract

Cancer research is striving toward new frontiers of assigning the correct personalized drug(s) to a given patient. However, extensive tumor heterogeneity poses a major obstacle. Tumors of the same type often respond differently to therapy, due to patient-specific molecular aberrations and/or untargeted tumor subpopulations. It is frequently not possible to determine a priori which patients will respond to a certain therapy or how an efficient patient-specific combined therapy should be designed. Large-scale datasets have been growing at an accelerated pace and various technologies and analytical tools for single cell and bulk level analyses are being developed to extract significant individualized signals from such heterogeneous data. However, personalized therapies that dramatically alter the course of the disease remain scarce, and most tumors still respond poorly to medical care. In this review, the basic concepts of bulk and single cell approaches are discussed, as well as their emerging role in individualized designs of drug therapies, including the advantages and limitations of their applications in personalized medicine.

Original languageAmerican English
Article number1900227
JournalProteomics
Volume20
Issue number13
DOIs
StatePublished - 1 Jul 2020

Bibliographical note

Publisher Copyright:
© 2020 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim

Keywords

  • bulk proteomics
  • cancer heterogeneity
  • personalized medicine
  • single cell analysis

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