2025 Hot Topic in Basic & Translational Science: Small Cell Lung Cancer - Posters-PP01.24: Integrating chromatin profiling with gene expression to construct gene regulatory networks in small-cell lung cancer

PP01.24: Integrating chromatin profiling with gene expression to construct gene regulatory networks in small-cell lung cancer

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The study integrates chromatin profiling with gene expression data to construct gene regulatory networks for small-cell lung cancer (SCLC). The focus is on identifying gene programs and transcription factor (TF) modules across various SCLC cell lines by employing several analytical methods.<br /><br />Four main regulatory evidence classes were used to link TFs with gene programs: 1) Correlation between gene programs and TF expression levels, 2) Correlation between gene programs and TF activity, measured using ChromVAR scores, 3) Enrichment of TF motifs in regulatory elements associated with gene programs, and 4) Anti-correlation between gene programs and cell fitness affected by TF knockout, indicating essential TFs for cell proliferation.<br /><br />The study applied Leiden clustering to z-scored log-transformed expression values across 46 cell lines to identify gene programs. Simultaneously, they undertook ATAC-seq across 19 cell lines to compute ChromVAR-derived global TF activity scores, then clustered the TFs based on their ChromVAR profile.<br /><br />Cell lines were categorized by predicted molecular subtypes, and gene expression was visualized in a heatmap, revealing distinct gene programs. For instance, programs related to cell differentiation, adhesion, migration, and development were noted in specific SCLC subtypes.<br /><br />A key part of the analysis was constructing a relationship between TF modules and gene programs via Pearson correlations, linking each TF module to gene programs across cell lines. This relationship was illustrated in a UMAP representation of TF ChromVAR scores, demonstrating similarities in TF activity patterns.<br /><br />Overall, this research developed a framework for using integrated multi-omic analyses to delineate gene-TF regulatory networks in SCLC, ultimately aiding in identifying critical TFs linked to cancer cell characteristics and potential therapeutic targets.

Asset Subtitle

Oana Ursu

Keywords

chromatin profiling

gene expression

small-cell lung cancer

gene regulatory networks

transcription factor modules

ChromVAR scores

ATAC-seq

Leiden clustering

molecular subtypes

multi-omic analyses