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Cited by 3Chronic Lymphocytic Leukemia ResearchBioinformatics and Genomic NetworksComputational Drug Discovery Methods

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A Systems Biology Analysis of Chronic Lymphocytic Leukemia

Open access
Pozzati, Giulia, Zhou, Jinrui, Hazan, Hananel, Klement, Giannoula Lakka, Siegelmann, Hava T., Tuszynski, Jack A., Rietman, Edward A.·2024·Onco
DOI 10.3390/onco4030013

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Abstract

Whole-genome sequencing has revealed that TP53, NOTCH1, ATM, SF3B1, BIRC3, ABL, NXF1, BCR, and ZAP70 are often mutated in CLL, but not consistently across all CLL patients. This paper employs a statistical thermodynamics approach in combination with the systems biology of the CLL protein–protein interaction networks to identify the most significant participant proteins in the cancerous transformation. Betti number (a topology of complexity) estimates highlight a protein hierarchy, primarily in the Wnt pathway known for aberrant CLL activation. These individually identified proteins suggest a network-targeted strategy over single-target drug development. The findings advocate for a multi-target inhibition approach, limited to several key proteins to minimize side effects, thereby providing a foundation for designing therapies. This study emphasizes a shift towards a comprehensive, multi-scale analysis to enhance personalized treatment strategies for CLL, which could be experimentally validated using siRNA or small-molecule inhibitors. The result is not just the identification of these proteins but their rank-order, offering a potent signal amplification in the context of the 20,000 proteins produced by the human body, thus providing a strategic basis for therapeutic intervention in CLL, underscoring the necessity for a more holistic, cellular, chromosomal, and genome-wide study to develop tailored treatments for CLL patients.

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Metadata

Authors
Pozzati, G., Zhou, J., Hazan, H., Klement, G. L., Siegelmann, H. T., Tuszynski, J. A., & Rietman, E. A.
Affiliations
  • Politecnico di Torino (IT)
  • Harvard University (US)
  • Tufts University (US)
  • CSTS Healthcare, Toronto, ON M5B 2H9, Canada
  • University of Massachusetts Amherst (US)
  • Dipartimento di Ingegneria Meccanica e Aerospaziale (DIMEAS), Politecnico di Torino, 10129 Turin, Italy
  • Silesian University of Technology (PL)
ORCID
Venue
Onco
Publisher
MDPI AG
Published
2024-08-06
Volume
4
Issue
3
Pages
163-191
ISSN
2673-7523 (ISSN-L)
DOI
10.3390/onco4030013
OpenAlex
W4401352446
Cited by
3
References
4
Citations by year
2026: 1 · 2025: 2
FWCI
0.84
Type
journal article
Language
en
Open access
Licence
Locations
  • Onco (publishedVersion, cc-by)
  • bioRxiv (Cold Spring Harbor Laboratory) (acceptedVersion, cc-by)
  • DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion)
Funders
NSERC (Canada)
Topics
  • Health Sciences › Medicine › Hematology › Chronic Lymphocytic Leukemia Research
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Bioinformatics and Genomic Networks
  • Life Sciences › Pharmacology, Toxicology and Pharmaceutics › Drug Discovery › Computational Drug Discovery Methods
Keywords
chronic lymphocytic leukemia, protein-protein interaction network, Betti numbers, network topology, Wnt signaling, cancer transformation, TP53 mutation, NOTCH1 mutation, B cell receptor signaling, ZAP-70, precision oncology

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