Evidence map›Paper›PMID 42406591›Full record

ArticleAdvanced healthcare materials2026

High-Throughput Digital Decoding of Vascular Heterogeneity in Patient-Specific Tumor Microenvironments.

Jungseub Lee, Wooju Park, Sujin Hyung, Sangmin Jung, Kyungho Lee, Junseok Jeon, Noo Li Jeon, Jeeyun Lee, Hye Ryoun Jang, Jihoon Ko

Abstract read
In one paragraph

Article in Advanced healthcare materials, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

10 authors.

Jungseub LeeDepartment of Mechanical Engineering, Seoul National University, Seoul, Republic of Korea.
Wooju ParkDepartment of BioNano Technology, Gachon University, Seongnam-si, Gyeonggi-do, Republic of Korea.
Sujin HyungPrecision Medicine Research Institute, Samsung Medical Center, Seoul, Republic of Korea.
Sangmin JungDepartment of Mechanical Engineering, Seoul National University, Seoul, Republic of Korea.
Kyungho LeeDivision of Nephrology Department of Medicine, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Republic of Korea.
Junseok JeonDivision of Nephrology Department of Medicine, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Republic of Korea.
Noo Li JeonDepartment of Mechanical Engineering, Seoul National University, Seoul, Republic of Korea.
Jeeyun LeePrecision Medicine Research Institute, Samsung Medical Center, Seoul, Republic of Korea.
Hye Ryoun JangDivision of Nephrology Department of Medicine, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Republic of Korea.
Jihoon KoDepartment of BioNano Technology, Gachon University, Seongnam-si, Gyeonggi-do, Republic of Korea.ORCID https://orcid.org/0000-0002-6555-3728

Funding

Korea Health Industry Development InstituteMinistry of Education 0681-20260017Ministry of Health and WelfareMinistry of Trade, Industry and Energy RS-2024-00448560Ministry of Trade, Industry and Energy RS-2024-00512240National Research Foundation of Korea RS-2023-00218543National Research Foundation of Korea RS-2025-24534071National Research Foundation of Korea RS-2026-25498717
6 · The paper itself

Abstract

Quantitative characterization of vascular heterogeneity in complex microphysiological systems (MPS), particularly within patient-derived tumor microenvironments, remains a major challenge for scalable disease modeling and therapeutic evaluation. Existing analysis approaches primarily rely on vessel abundance-based morphometrics and often fail to resolve network connectivity and spatial remodeling in heterogeneous vascular systems. Here, we present the iMAP platform, a high-throughput digital vascular profiling framework that integrates an injection-molded microfluidic chip with an interactive image analysis tool (iMAP Analyzer). This platform enables topology-resolved and region-aware quantification of vascular architecture, capturing vessel morphology, branching complexity, connectivity, and spatial variation between tumor-proximal and distal regions. Applied to 3D co-cultures of patient-derived gastric cancer tumor spheroids with either donor-matched iPSC-derived endothelial cells (iPSC-ECs) or primary HUVECs, iMAP identified differences in network organization and spatial stability under standardized conditions, with iPSC-derived networks exhibiting increased fragmentation and peripheral instability. These findings demonstrate that connectivity-normalized and region-resolved analysis provides critical insight beyond conventional whole-image metrics. The iMAP framework offers a scalable and standardized approach for quantitative vascular phenotyping in complex MPS, supporting high-content analysis and advancing the development of vascularized in vitro disease models.

Indexed as

Stomach NeoplasmsTumor MicroenvironmentCoculture TechniquesEndothelial CellsHumansHuman Umbilical Vein Endothelial CellsInduced Pluripotent Stem CellsMicrophysiological SystemsSpheroids, Cellularhigh‐content imaging pipelineiMAP analyzerpatient‐derived iPSC‐ECsROI‐aware quantitative phenotypingspatial heterogeneityvascularized tumor microenvironmentvascularized tumor‐on‐a‐chip

Identifiers

PMID42406591
PMCPMC13447886

What Socratic holds

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Registered trials

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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 Socratic graph.