Journal Article

DKFZ-2024-02534

http://join2-wiki.gsi.de/foswiki/pub/Main/Artwork/join2_logo100x88.png DysRegNet: Patient-specific and confounder-aware dysregulated network inference towards precision therapeutics.

Kersting, J. ; Lazareva, O.DKFZ* ; Louadi, Z. ; Baumbach, J. ; Blumenthal, D. B. ; List, M.

2026
Wiley Malden, MA

Abstract: Gene regulation is frequently altered in diseases in unique and patient-specific ways. Hence, personalised strategies have been proposed to infer patient-specific gene-regulatory networks. However, existing methods do not scale well because they often require recomputing the entire network per sample. Moreover, they do not account for clinically important confounding factors such as age, sex or treatment history. Finally, a user-friendly implementation for the analysis and interpretation of such networks is missing.We present DysRegNet, a method for inferring patient-specific regulatory alterations (dysregulations) from bulk gene expression profiles. We compared DysRegNet to the well-known SSN method, considering patient clustering, promoter methylation, mutations and cancer-stage data.We demonstrate that both SSN and DysRegNet produce interpretable and biologically meaningful networks across various cancer types. In contrast to SSN, DysRegNet can scale to arbitrary sample numbers and highlights the importance of confounders in network inference, revealing an age-specific bias in gene regulation in breast cancer. DysRegNet is available as a Python package (https://github.com/biomedbigdata/DysRegNet_package), and analysis results for 11 TCGA cancer types are available through an interactive web interface (https://exbio.wzw.tum.de/dysregnet).DysRegNet introduces a novel bioinformatics tool enabling confounder-aware and patient-specific network analysis to unravel regulatory alteration in complex diseases.

Keyword(s): cancer and carcinogenesis ; computational pharmacology ; epigenetics ; gene transcription ; mathematical modelling ; systems pharmacology

Note: 2026 Apr;183(8):1709-1724

---

Contributing Institute(s):

1. B260 Bioinformatik der Genomik und Systemgenetik (B260)

Research Program(s):

1. 312 - Funktionelle und strukturelle Genomforschung (POF4-312) (POF4-312)

Appears in the scientific report 2024

---

Database coverage:
; ; BIOSIS Previews ; Biological Abstracts ; Clarivate Analytics Master Journal List ; Current Contents - Life Sciences ; DEAL Wiley ; Ebsco Academic Search ; Essential Science Indicators ; IF >= 5 ; JCR ; PubMed Central ; SCOPUS ; Science Citation Index Expanded ; Web of Science Core Collection

---