Journal Article

DZNE-2023-01037

http://join2-wiki.gsi.de/foswiki/pub/Main/Artwork/join2_logo100x88.png Reconstructing disease dynamics for mechanistic insights and clinical benefit.

Frishberg, A. (First author)DZNE* ; Milman, N. ; Alpert, A. ; Spitzer, H. ; Asani, B. ; Schiefelbein, J. B. ; Bakin, E. ; Regev-Berman, K. ; Priglinger, S. G. ; Schultze, J. L.DZNE* ; Theis, F. J. ; Shen-Orr, S. S.

2023
Nature Publishing Group UK [London]

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Please use a persistent id in citations: doi:10.1038/s41467-023-42354-8

Abstract: Diseases change over time, both phenotypically and in their underlying molecular processes. Though understanding disease progression dynamics is critical for diagnostics and treatment, capturing these dynamics is difficult due to their complexity and the high heterogeneity in disease development between individuals. We present TimeAx, an algorithm which builds a comparative framework for capturing disease dynamics using high-dimensional, short time-series data. We demonstrate the utility of TimeAx by studying disease progression dynamics for multiple diseases and data types. Notably, for urothelial bladder cancer tumorigenesis, we identify a stromal pro-invasion point on the disease progression axis, characterized by massive immune cell infiltration to the tumor microenvironment and increased mortality. Moreover, the continuous TimeAx model differentiates between early and late tumors within the same tumor subtype, uncovering molecular transitions and potential targetable pathways. Overall, we present a powerful approach for studying disease progression dynamics-providing improved molecular interpretability and clinical benefits for patient stratification and outcome prediction.

Keyword(s): Humans (MeSH) ; Urinary Bladder Neoplasms: diagnosis (MeSH) ; Urinary Bladder Neoplasms: genetics (MeSH) ; Urinary Bladder Neoplasms: pathology (MeSH) ; Carcinoma, Transitional Cell: pathology (MeSH) ; Disease Progression (MeSH) ; Tumor Microenvironment (MeSH)

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Contributing Institute(s):

1. Clinical Single Cell Omics (CSCO) / Systems Medicine (AG Schultze)
2. Platform for Single Cell Genomics and Epigenomics (Schultze - PRECISE)

Research Program(s):

1. 354 - Disease Prevention and Healthy Aging (POF4-354) (POF4-354)
2. 352 - Disease Mechanisms (POF4-352) (POF4-352)

Experiment(s):

1. Platform for Single Cell Genomics and Epigenomics at DZNE University of Bonn

Appears in the scientific report 2023

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