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Utilizing Functional Genomics Screening to Identify Potentially Novel Drug Targets in Cancer Cell Spheroid Cultures
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Profiling the Non-genetic Origins of Cancer Drug Resistance with a Single-Cell Functional Genomics Approach Using

Mickael Meyer1, Agnès Paquet2, Marie-Jeanne Arguel2

  • 1Université Côte d'Azur, CNRS UMR 7284, Inserm U 1081, Institut de Recherche sur le Cancer et le Vieillissement de Nice, Centre Antoine Lacassagne, 06107 Nice, France.

Cell Systems
|October 25, 2020
PubMed

Insights

This study introduces fate-seq, a novel method linking cell behavior to gene expression for understanding drug resistance. It reveals molecular drivers of resistance in clonal cells, offering new therapeutic targets.

Area of Science:

  • Cell Biology
  • Genomics
  • Pharmacology

Background:

  • Non-genetic heterogeneity in clonal cell populations contributes to drug resistance.
  • The transient nature of this heterogeneity makes it difficult to study and profile.
  • Understanding these dynamics is crucial for developing effective cancer therapies.

Purpose of the Study:

  • To develop a method for linking individual cell responses to drug treatment with their genome-wide transcriptomic profiles.
  • To investigate the transient transcriptional states underlying cell fate decisions in response to drug treatment.
  • To identify molecular factors driving non-genetic drug resistance.

Main Methods:

  • Coupling of three single-cell technologies to create the fate-seq approach.
  • Analysis of tumor-necrosis-factor-related apoptosis-inducing ligand (TRAIL) response in HeLa cells.
  • Genome-wide transcriptomic profiling of individual cells linked to their drug response.

Main Results:

  • Demonstrated that cell dynamics can discriminate transient transcriptional states related to drug sensitivity and resistance.
  • Successfully linked predicted drug response to individual cell transcriptomic profiles.
  • Identified potential molecular factors regulating drug efficacy in clonal cell populations.

Conclusions:

  • The fate-seq approach provides a powerful tool for dissecting non-genetic drug resistance mechanisms.
  • This method can reveal therapeutic targets previously obscured by gene expression noise.
  • Understanding cell dynamics is key to overcoming drug resistance in cancer treatment.
Keywords:
cancer drug resistancecell-to-cell variabilitylaser-capture microdissectionlive-cell microscopypharmacogenomicssingle-cellsystems biologytranscriptomics

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