Linking Expression of Cell-Surface Receptors with Transcription Factors by Computational Analysis of Paired...

Area of Science:

• Cellular and Molecular Biology
• Computational Biology
• Cancer Research

Background:

• Complex signaling and transcriptional programs govern cell development and physiology.
• Genetic alterations in these programs can lead to diverse human cancers.
• Understanding these systems is crucial for developing cancer immunotherapies and identifying drug targets.

Purpose of the Study:

• To introduce SPaRTAN (Single-cell Proteomic and RNA-based Transcription factor Activity Network), a computational framework.
• To link transcription factors with cell-surface protein expression using single-cell multi-omics data.
• To model the impact of transcription factor and cell-surface receptor interactions on gene expression.

Main Methods:

• Utilized CITE-seq (cellular indexing of transcriptomes and epitopes by sequencing) data.
• Integrated cis-regulatory site information.
• Developed a computational framework (SPaRTAN) to analyze transcription factor activity and cell-surface protein expression.

Main Results:

• Demonstrated the SPaRTAN pipeline using CITE-seq data from peripheral blood mononuclear cells.
• Successfully linked transcription factor activity to cell-surface protein expression.
• Modeled the regulatory effects of these interactions on gene expression.

Conclusions:

• SPaRTAN provides a novel computational approach to connect transcription factors with cell-surface proteins.
• This framework aids in understanding the molecular basis of specialized cell types and their role in cancer.
• The methodology has implications for identifying novel therapeutic targets in cancer treatment.