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Transcription factor enrichment analysis (TFEA): Quantifying the activity of hundreds of TFs from a single experiment

ABSTRACT: Detecting differential activation of transcription factors (TFs) in response to perturbation provides insight into global cellular processes. We present here Transcription Factor Enrichment Analysis (TFEA), a robust and reliable computational method that can detect differential activity of hundreds of TFs given any set of perturbation data. TFEA draws inspiration from GSEA and detects positional motif enrichment within an ordered list of regions of interest (ROI). As ROI are typically directly inferred from the data, we also introduce muMerge, a statistically principled method that generates a consensus list of ROIs from multiple replicates and conditions. TFEA is broadly applicable to data types that inform on transcriptional regulation, including CAGE data, ChIP-Seq, and accessibility data (e.g. ATAC-Seq). We demonstrate that TFEA can not only identify key TFs that respond to a perturbation, but also temporally unravel complex regulatory networks with time series data. Consequently, TFEA serves as a “hypothesis-generating engine” that provides an easy, rigorous, and cost-effective means to broadly assess TF activity to yield new biological insights about basic cellular processes.

ORGANISM(S): Homo sapiens

PROVIDER: GSE142419 | GEO | 2020/12/18

REPOSITORIES: GEO

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Project description:Genomic and epigenomic studies support that adenocarcinomas of the gallbladder develop according to a metaplasia-biliary intraepithelial neoplasia (BilIN)-adenocarcinoma histogenic sequence, in which metaplasia and BilIN are non-cancerous lesions of the epithelium. Moreover, recent genomic data suggest that adenocarcinoma can develop in a BilIN-dependent or -independent way, pointing toward patient-specific tumourigenic processes. Spatial transcriptomic data addressing these processes are still missing. Here, using GeoMx digital spatial profiling (NanoString), we characterized the spatial transcriptome of normal gallbladder epithelium, BilINs and adenocarcinoma coexisting within the same samples. To address intra-patient variability we profiled the whole transcriptome of a high number of regions of interest (ROIs) per sample in two patients (Patient #1, 81 year old woman: 24 ROIs; Patient #2, 53-year old man:32 ROIs), with each ROI covering approximately 200 cells of normal epithelium, low-grade BilIN, high-grade BilIN or adenocarcinoma. Our results showed that each type of lesion displayed little transcriptomic variability within the same patient, but differed significantly between patients. They also suggested that adenocarcinoma can derive from high-grade BilIN or from low-grade BilIN, with co-existing high-grade BilIN evolving via a distinct process in the latter case. We also provide strong evidence for patient-specific tumourigenic mechanisms, characterized by distinct sequences of signalling pathway activation. Among those pathways, we functionally investigated SEMAPHORIN 4A (SEMA4A) and provided evidence that repression of SEMA4A expression, as is observed in the gallbladder samples of the two patients, can enhance cell migration and survival, and perturb polarisation of the epithelial cells. In conclusion, our results support that gallbladder adenocarcinoma develops according to patient-specific processes that can be promoted by repression of SEMA4A. They underscore the need to gain gene expression data in addition to histological information to evaluate the risk of low-grade preneoplastic lesions.

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Transcription factor enrichment analysis (TFEA): Quantifying the activity of hundreds of TFs from a single experiment

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