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Oscillatory ERK Signaling and Morphology Determine Heterogeneity of Breast Cancer Cell Chemotaxis via MEK-ERK and p38-MAPK Signaling Pathways

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Ho, Kenneth K. Y., Srivastava, Siddhartha, Kinnunen, Patrick C., Garikipati, Krishna, Luker, Gary D., Luker, Kathryn E.·2023·Bioengineering
DOI 10.3390/bioengineering10020269PMC PMC9952091
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Abstract

Chemotaxis, regulated by oscillatory signals, drives critical processes in cancer metastasis. Crucial chemoattractant molecules in breast cancer, CXCL12 and EGF, drive the activation of ERK and Akt. Regulated by feedback and crosstalk mechanisms, oscillatory signals in ERK and Akt control resultant changes in cell morphology and chemotaxis. While commonly studied at the population scale, metastasis arises from small numbers of cells that successfully disseminate, underscoring the need to analyze processes that cancer cells use to connect oscillatory signaling to chemotaxis at single-cell resolution. Furthermore, little is known about how to successfully target fast-migrating cells to block metastasis. We investigated to what extent oscillatory networks in single cells associate with heterogeneous chemotactic responses and how targeted inhibitors block signaling processes in chemotaxis. We integrated live, single-cell imaging with time-dependent data processing to discover oscillatory signal processes defining heterogeneous chemotactic responses. We identified that short ERK and Akt waves, regulated by MEK-ERK and p38-MAPK signaling pathways, determine the heterogeneous random migration of cancer cells. By comparison, long ERK waves and the morphological changes regulated by MEK-ERK signaling, determine heterogeneous directed motion. This study indicates that treatments against chemotaxis in consider must interrupt oscillatory signaling.

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  • Variational System Identification has been applied to identify governing equations for the evolution of materials, the spatiotemporal spread of COVID-19, and constitutive models of soft materials.

    “Variational System Identification has been applied to identify governing equations for the evolution of materials17,20,19, the spatiotemporal spread of COVID-1921,18, as well as constitutive models of soft materials22,23.”

    From Inference of weak-form partial differential equations describing migration and proliferation mechanisms in wound healing experiments on cancer cells (2025) · cites this paper as [18]

    The cited paper’s Methods §2.7 applies Variational System Identification to breast-cancer cell migration, not to constitutive models of soft materials. Its References identify a separate Wang et al. (2021) paper on inferring the constitutive response of soft-material surrogates using that method; that is the work matching the clause to which this citation is attached. (LLM, conf=0.84) It matches “Inference of deformation mechanisms and constitutive response of soft material surrogates of biological tissue by full-field characterization and data-driven variational system identification” (2021) instead.

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  • Variational System Identification extends SINDy to inferring PDEs in weak form, thereby offering advantages in the presence of noise and high derivatives.

    “It extends the popular SINDy approach12,13,14,15,16 to inferring PDEs in weak form, thereby offering advantages in the presence of noise and high derivatives17,18,19.”

    From Inference of weak-form partial differential equations describing migration and proliferation mechanisms in wound healing experiments on cancer cells (2025) · cites this paper as [18]

    Section 2.7 (page unavailable) says the authors used VSI to infer mechanisms and parameters of an advection–diffusion PDE. It does not say that VSI extends SINDy, uses a weak form, or offers advantages with noise or high derivatives; searches for those terms found no supporting passage. (LLM, conf=0.85)

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Cited by

Sorted by citations

Authors
Ho, K. K. Y., Srivastava, S., Kinnunen, P. C., Garikipati, K., Luker, G. D., & Luker, K. E.
Affiliations
University of Michigan (US)
Corresponding author
  • Luker, Gary D.
  • Luker, Kathryn E.
ORCID
Venue
Bioengineering
Publisher
MDPI AG
Published
2023-02-18
Volume
10
Issue
2
Pages
269
ISSN
2306-5354 (ISSN-L)
DOI
10.3390/bioengineering10020269
PMC
PMC9952091
OpenAlex
W4321377807
Cited by
8
References
3
Citations by year
2026: 2 · 2025: 3 · 2024: 1 · 2023: 1
FWCI
0.62
Type
journal article
Language
en
Open access
Licence
Locations
  • Bioengineering (publishedVersion, cc-by)
  • PubMed Central (publishedVersion, cc-by)
  • PubMed (publishedVersion)
  • DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
Funders
  • NIH (R01CA238042, U01CA210152, R01CA238023, R33CA225549, R50CA221807, R37CA222563)
  • W.M. Keck Foundation (R01CA238042, U01CA210152, R01CA238023, R33CA225549, R50CA221807, R37CA222563)
Topics
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Gene Regulatory Network Analysis
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Protein Kinase Regulation and GTPase Signaling
  • Physical Sciences › Mathematics › Modeling and Simulation › Mathematical Biology Tumor Growth
Keywords
breast cancer, cell chemotaxis, ERK signaling, MEK/ERK signaling, p38 MAPK pathway, Akt signaling, cell morphology, CXCL12, epidermal growth factor, single-cell imaging, metastasis, directed cell migration, signaling inhibitors

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