Integration of Single-Cell RNA-Sequencing and Network Analysis to Investigate Mechanisms of Drug Resistance

Stephanie The; Patricia M Schnepp; Greg Shelley; Jill M Keller; Arvind Rao; Evan T Keller

doi:10.1007/978-1-0716-3163-8_7

Integration of Single-Cell RNA-Sequencing and Network Analysis to Investigate Mechanisms of Drug Resistance

Methods Mol Biol. 2023:2660:85-94. doi: 10.1007/978-1-0716-3163-8_7.

Authors

Stephanie The^{1

2}, Patricia M Schnepp^{1

3}, Greg Shelley^{1

3}, Jill M Keller^{1

3

4}, Arvind Rao^{5

2

6}, Evan T Keller^{7

8

9

10

11}

Affiliations

¹ Biointerfaces Institute, University of Michigan, Ann Arbor, MI, USA.
² Department of Biostatistics, School of Public Health, University of Michigan, Ann Arbor, MI, USA.
³ Department of Urology, School of Medicine, University of Michigan, Ann Arbor, MI, USA.
⁴ Unit for Laboratory Animal Medicine, University of Michigan, Ann Arbor, MI, USA.
⁵ Single Cell Spatial Analysis Program, University of Michigan, Ann Arbor, MI, USA.
⁶ Computational Medicine and Bioinformatics, School of Medicine, University of Michigan, Ann Arbor, MI, USA.
⁷ Biointerfaces Institute, University of Michigan, Ann Arbor, MI, USA. etkeller@umich.edu.
⁸ Single Cell Spatial Analysis Program, University of Michigan, Ann Arbor, MI, USA. etkeller@umich.edu.
⁹ Department of Urology, School of Medicine, University of Michigan, Ann Arbor, MI, USA. etkeller@umich.edu.
¹⁰ Unit for Laboratory Animal Medicine, University of Michigan, Ann Arbor, MI, USA. etkeller@umich.edu.
¹¹ Computational Medicine and Bioinformatics, School of Medicine, University of Michigan, Ann Arbor, MI, USA. etkeller@umich.edu.

Abstract

Innate resistance and therapeutic-driven development of resistance to anticancer drugs is a common complication of cancer therapy. Understanding mechanisms of drug resistance can lead to development of alternative therapies. One strategy is to subject drug-sensitive and drug-resistant variants to single-cell RNA-seq (scRNA-seq) and to subject the scRNA-seq data to network analysis to identify pathways associated with drug resistance. This protocol describes a computational analysis pipeline to study drug resistance by subjecting scRNA-seq expression data to Passing Attributes between Networks for Data Assimilation (PANDA), an integrative network analysis tool that incorporates protein-protein interactions (PPI) and transcription factor (TF)-binding motifs.

Keywords: Connectivity map analysis; Data integration; Drug resistance network; Gene set enrichment analysis; Passing Attributes between Networks for Data Assimilation; Protein–protein interactions; Single-cell RNA-sequencing; Transcription factor-binding motifs.

Publication types

Research Support, N.I.H., Extramural

MeSH terms

Gene Expression Profiling* / methods
RNA*
Sequence Analysis, RNA / methods
Single-Cell Analysis / methods

Substances

RNA

Abstract

Publication types

MeSH terms

Substances

Grants and funding