Evidence map›Paper›PMID 42013840›Full record

ArticleCell systems2026

Cell shapes decode molecular phenotypes in image-based spatial proteomics.

Trang Le, William D Leineweber, Matheus P Viana, Anthony Cesnik, Jan N Hansen, Wei Ouyang, Susanne M Rafelski, Emma Lundberg

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Cell systems, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

8 authors.

Trang LeDepartment of Bioengineering, Stanford University, Stanford, CA, USA; Science for Life Laboratory, School of Engineering Sciences in Chemistry, Biotechnology and Health, KTH - Royal Institute of Technology, Stockholm, Sweden.
William D LeineweberDepartment of Bioengineering, Stanford University, Stanford, CA, USA.
Matheus P VianaAllen Institute for Cell Sciences, Seattle, WA, USA.
Anthony CesnikDepartment of Bioengineering, Stanford University, Stanford, CA, USA.
Jan N HansenDepartment of Bioengineering, Stanford University, Stanford, CA, USA; Science for Life Laboratory, School of Engineering Sciences in Chemistry, Biotechnology and Health, KTH - Royal Institute of Technology, Stockholm, Sweden.
Wei OuyangScience for Life Laboratory, School of Engineering Sciences in Chemistry, Biotechnology and Health, KTH - Royal Institute of Technology, Stockholm, Sweden; Department of Applied Physics, Science for Life Laboratory, KTH - Royal Institute of Technology, Stockholm, Sweden.
Susanne M RafelskiAllen Institute for Cell Sciences, Seattle, WA, USA.
Emma LundbergDepartment of Bioengineering, Stanford University, Stanford, CA, USA; Science for Life Laboratory, School of Engineering Sciences in Chemistry, Biotechnology and Health, KTH - Royal Institute of Technology, Stockholm, Sweden; Department of Pathology, Stanford University, Stanford, CA, USA. Electronic address: emmalu@stanford.edu.

Funding

Bridge2AI: Cell Maps for AI (CM4AI) Data Generation ProjectOT2OD032742 · OD · UNIVERSITY OF CALIFORNIA, SAN DIEGO · PI Jean-Christophe Bélisle-Pipon, TIMOTHY W CLARK · 2022 to 2026
$21.5M
The Cancer Cell Map Initiative v2.0U54CA274502 · NCI · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI Trey Ideker · 2022 to 2026
$14.2M
NCI NIH HHS U54 CA274502NIH HHS OT2 OD032742
6 · The paper itself

Abstract

Cellular and tissue structures arise from a few cell shapes, which undergo transformations based on biophysical constraints. Despite links between signaling pathways and cellular geometry, whole-proteome orchestration in association with cell shape is underexplored. In this study, over 1 million single cells stained for 11,998 proteins across 11 cell lines in the Human Protein Atlas were analyzed for organelle, pathway, and single-protein levels in association with cellular shapespace. We found that cell and nuclear shapes across cell lines exist in a shared continuum. The subcellular organelle topology varies across cell lines but remains consistent within each cell line's shapespace. At the single-protein level, cells of different shapes in the same cell-cycle phase might be preparing for different fates, and many non-cell-cycle proteins expressed shape-based abundance variation. Using a shape-based coordinate framework, we analyzed the distribution shift of protein spatial localization under drug perturbation.

Indexed as

Cell ShapeProteomicsCell LineHumansPhenotypeProteomeSignal TransductionProteomecell shapeinterpretable machine learningmolecular variationmorphological variationsingle cellspatial proteomics

Identifiers

PMID42013840
PMCPMC13138879

What OpenQuestion 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 OpenQuestion graph.