Transcription Factor Activation Profiles (TFAP) identify compounds promoting differentiation of Acute Myeloid Leukemia cell lines

Federica Riccio,Claudia Fuoco,Giorgia Massacci,Giulio Giuliani,Simone Vumbaca,Elisa Micarelli,Luisa Castagnoli,Riccardo Secci,Gianni Cesareni

doi:10.1038/s41420-021-00811-7

Abstract

Repurposing of drugs for new therapeutic use has received considerable attention for its potential to limit time and cost of drug development. Here we present a new strategy to identify chemicals that are likely to promote a desired phenotype. We used data from the Connectivity Map (CMap) to produce a ranked list of drugs according to their potential to activate transcription factors that mediate myeloid differentiation of leukemic progenitor cells. To validate our strategy, we tested the in vitro differentiation potential of candidate compounds using the HL-60 human cell line as a myeloid differentiation model. Ten out of 22 compounds, which were ranked high in the inferred list, were confirmed to promote significant differentiation of HL-60. These compounds may be considered candidate for differentiation therapy. The method that we have developed is versatile and it can be adapted to different drug repurposing projects.

Highlights

Pharmaceutical companies experience considerable hurdles in the development and marketing of new drugs [1]
It is possible to infer the impact of a drug on activation of a transcription factors (TFs) by looking at the fraction of target genes that are up- or downregulated after drug treatment. This procedure is often referred to as TF enrichment analysis. We show that this approach is less sensitive to experimental noise when compared with conventional expression profile methods and we used it to infer drugs that are likely to induce myeloid differentiation of HL-60, a cell line derived from a patient with acute myeloid leukemia
Identification of compounds promoting differentiation in Acute Myeloid Leukemia by Transcription Factor Activation Profile (TFAP) approach Repositioning strategies based on comparison of transcriptional signatures have encountered some success [7]

Summary

Introduction

Pharmaceutical companies experience considerable hurdles in the development and marketing of new drugs [1] This is because of the escalating cost and time required for preclinical research, clinical trials and regulatory requirements [2]. In principle a complete understanding of a pathology and a detailed annotation of each drug effects and side-effects should allow the design of new rational treatments to revert a disease phenotype. In practice such a direct approach is often not possible and the most successful cases of drug repurposing to date are the result of serendipitous observations and not of rational design or systematic approaches. Gene expression profiles obtained by RNA-seq or proteomics approaches, chemical structures and electronic health records have been used for this purpose [5]

Methods

Results

Conclusion