Gene expression is a fundamental process that dictates cellular identity and plasticity by translating genetic information into functional molecules. Remarkably, even within genetically identical cell populations, gene expression often exhibits significant heterogeneity. This variability is thought to be crucial for cell survival, particularly in challenging environments. In cancer, such fluctuations can lead to the emergence of rare cells capable of withstanding treatment. Since drug resistance is a major obstacle in cancer therapy it is essential to understand how gene expression heterogeneity arises.
Transcription is orchestrated by transcription factors (TFs), which recruit cofactors (CoFs) to modulate gene expression. However, the impact of co-acting TF/CoF pairs on transcriptome at single cell resolutions is still an enigma. This project aims to address this question by developing a method that simultaneously quantifies co-occurring TF/CoF pairs and the transcriptome, at the single-cell level. In this way, we aim to characterize the correlation between the TF/CoF pair interactions and the resulting transcriptomic changes. Our approach has the potential to reveal interactions that occur in subpopulations of cells, which are obscured in bulk studies. Apart from its application on TF/CoF pairs, this approach can be extended to investigate the impact of other protein-protein interactions of interest, opening new avenues for future research.
Here, we will present the first data showing the heterogeneity of c-MYC/MAX interactions and the nuclear RNA expression patterns in single colon cancer cells. In future research we will examine these cells under challenging conditions, such as exposure to c-MYC antagonists or inhibitors of the c-MYC/MAX complex. As these cooperating transcription factors are key regulators of cell proliferation, we are particularly interested in subpopulations that emerge.