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

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.

journal_name

Proteomics

journal_title

Proteomics

authors

Kravchenko-Balasha N

doi

10.1002/pmic.201900227

subject

Has Abstract

pub_date

2020-07-01 00:00:00

pages

e1900227

issue

13

eissn

1615-9853

issn

1615-9861

journal_volume

20

pub_type

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