Evidence map›Paper›PMID 42057835›Full record

ArticleFrontiers in oncology2026

Osteosarcoma pulmonary metastasis: the hemodynamic mechanical-filtration hypothesis for subpleural predominance.

Kaihua Zhang

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Article in Frontiers in oncology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

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2 · The registry

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3 · Its place in the literature

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4 · The record

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5 · Who and what money

Authors and funding

1 author.

Kaihua ZhangDepartment of Thoracic Surgery, Beijing Genertec Aerospace Hospital, Beijing, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Pulmonary metastasis remains the leading cause of death in osteosarcoma; however, the pronounced and long-recognized subpleural predominance of metastatic nodules remains mechanistically unexplained. Contemporary "seed-and-soil" and pre-metastatic niche frameworks emphasize microenvironmental conditioning and spatial heterogeneity, but they do not explain why metastatic seeding consistently localizes to the peripheral 1-2 cm of the lung. Likewise, modern mechanical perspectives acknowledge that circulating tumor cells can be retained at multiple sites within the pulmonary microvasculature (including capillaries and pre-capillary arterioles), yet they do not account for a reproducible intra-organ, subpleural spatial bias. Knowledge gap: A testable model that links pulmonary microvascular geometry and hemodynamics to the consistent subpleural localization of early osteosarcoma metastatic seeding has yet to be established. Hypothesis: We propose the Hemodynamic Mechanical-Filtration Hypothesis: a clinically relevant subset of osteosarcoma circulating material may travel as larger, relatively stiff embolic units, including circulating tumor cell clusters (CTC clusters) and/or complex aggregates involving platelets and fibrin (CTC-platelet aggregates). Because these units have less instantaneous deformability than single cells, they may undergo size-selective mechanical arrest in terminal pre-alveolar arterioles (20-40 μm), which constitute a functional bottleneck immediately proximal to the capillary bed. We further hypothesize that filtration-prone distal arteriolar segments are preferentially distributed within a defined subpleural distance, an explicitly testable quantitative anatomical premise. This initial mechanical arrest establishes a spatial template for seeding, upon which post-arrest metastatic niche maturation and outgrowth can proceed, potentially modulated by upstream pre-metastatic niche (PMN) priming. Approach: The hypothesis integrates pulmonary microvascular anatomy, tumor biomechanics, cluster/aggregate rheology, and hemodynamic gradients. We outline falsifiable predictions and multi-level validation strategies, including intravital imaging, compliant/endothelialized microfluidic models, computational flow simulations, and clinical spatial mapping of metastatic nodules as a function of distance from the pleura. Key insights: By explicitly coupling embolic physical properties with hierarchical vascular geometry and regional hemodynamics, this framework provides a spatially resolved extension of mechanical arrest models and generates testable explanations for subpleural predominance as well as for the conditions under which the site of arrest may shift. Significance: If validated, this hypothesis would reframe early osteosarcoma lung seeding as a process constrained by microvascular biomechanics and could guide future mechanistic studies aimed at developing preventive strategies targeting embolic integrity and pulmonary microcirculatory conditions.

Indexed as

biomechanical metastasiscirculating tumor cell clustershemodynamic filtrationosteosarcomapulmonary metastasispulmonary microcirculationsubpleural predominance

Identifiers

PMID42057835
PMCPMC13121290

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.