DREIMT: a drug repositioning database and prioritization tool for immunomodulation

Motivation Drug immunomodulation modifies the response of the immune system and can be therapeutically exploited in pathologies such as cancer and autoimmune diseases. Results DREIMT is a new hypothesis-generation web tool which performs drug prioritization analysis for immunomodulation. DREIMT provides significant immunomodulatory drugs targeting up to 70 immune cells subtypes through a curated database that integrates 4,960 drug profiles and ~2,6K immune gene expression signatures. The tool also suggests potential immunomodulatory drugs targeting user-supplied gene expression signatures. Final output includes drug-signature association scores, FDRs and downloadable plots and results tables. Availability http://www.dreimt.org Contact falshahrour@cnio.es; ggomez@cnio.es

[1]  J. Kremer,et al.  Baricitinib in Patients with Refractory Rheumatoid Arthritis. , 2016, The New England journal of medicine.

[2]  Robert Langer,et al.  Delivery technologies for cancer immunotherapy , 2019, Nature Reviews Drug Discovery.

[3]  M. Merad,et al.  Macrophages orchestrate breast cancer early dissemination and metastasis , 2018, Nature Communications.

[4]  Gennady Korotkevich,et al.  Fast gene set enrichment analysis , 2021 .

[5]  Angela N. Brooks,et al.  A Next Generation Connectivity Map: L1000 Platform and the First 1,000,000 Profiles , 2017, Cell.

[6]  R. Roychoudhuri,et al.  Regulation of regulatory T cells in cancer , 2019, Immunology.

[7]  Laurence Zitvogel,et al.  The immune contexture in cancer prognosis and treatment , 2017, Nature Reviews Clinical Oncology.

[8]  A. Phelan,et al.  Baricitinib as potential treatment for 2019-nCoV acute respiratory disease , 2020, The Lancet.

[9]  Ronnie H. Fang,et al.  Nanoparticle-Based Modulation of the Immune System. , 2016, Annual review of chemical and biomolecular engineering.

[10]  Elena Piñeiro-Yáñez,et al.  vulcanSpot: a tool to prioritize therapeutic vulnerabilities in cancer , 2019, Bioinform..

[11]  N. Rose Prediction and Prevention of Autoimmune Disease in the 21st Century: A Review and Preview. , 2016, American journal of epidemiology.

[12]  Jianying Hu,et al.  Cell-specific prediction and application of drug-induced gene expression profiles , 2017, PSB.

[13]  Alexey Sergushichev,et al.  An algorithm for fast preranked gene set enrichment analysis using cumulative statistic calculation , 2016 .

[14]  E. Song,et al.  Complement Signals Determine Opposite Effects of B Cells in Chemotherapy-Induced Immunity , 2020, Cell.