Evidence mapPaperPMID 37519903Full record

ArticleiScience2023

Spatial topology of organelle is a new breast cancer cell classifier.

Ling Wang, Joshua Goldwag, Megan Bouyea, Jonathan Barra, Kailie Matteson, Niva Maharjan, Amina Eladdadi, Mark J Embrechts, Xavier Intes, Uwe Kruger and 1 more

Abstract read
In one paragraph

Article in iScience, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing 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

9 citing papers in PubMed.

  1. Article
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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

11 authors.

Ling WangDepartment of Molecular and Cellular Physiology, Albany Medical College, Albany, NY 12208, USA.
Joshua GoldwagDepartment of Molecular and Cellular Physiology, Albany Medical College, Albany, NY 12208, USA.
Megan BouyeaDepartment of Molecular and Cellular Physiology, Albany Medical College, Albany, NY 12208, USA.
Jonathan BarraDepartment of Molecular and Cellular Physiology, Albany Medical College, Albany, NY 12208, USA.
Kailie MattesonDepartment of Molecular and Cellular Physiology, Albany Medical College, Albany, NY 12208, USA.
Niva MaharjanDepartment of Mathematics, The College of Saint Rose, Albany, NY 12203, USA.
Amina EladdadiDepartment of Mathematics, The College of Saint Rose, Albany, NY 12203, USA.
Mark J EmbrechtsDepartment of Industrial and Systems Engineering, Rensselaer Polytechnic Institute, Troy, NY 12180, USA.
Xavier IntesDepartment of Biomedical Engineering, Rensselaer Polytechnic Institute, Troy, NY 12180, USA.
Uwe KrugerDepartment of Biomedical Engineering, Rensselaer Polytechnic Institute, Troy, NY 12180, USA.
Margarida BarrosoDepartment of Molecular and Cellular Physiology, Albany Medical College, Albany, NY 12208, USA.

Funding

Endosome-mitochondria interactions in breast cancer cellsR01CA233188 · NCI · ALBANY MEDICAL COLLEGE · PI Margarida Barroso · 2022 to 2023
$1.1M
NCI NIH HHS R01 CA207725NCI NIH HHS R01 CA233188NCI NIH HHS R21 CA274622
6 · The paper itself

Abstract

Genomics and proteomics have been central to identify tumor cell populations, but more accurate approaches to classify cell subtypes are still lacking. We propose a new methodology to accurately classify cancer cells based on their organelle spatial topology. Herein, we developed an organelle topology-based cell classification pipeline (OTCCP), which integrates artificial intelligence (AI) and imaging quantification to analyze organelle spatial distribution and inter-organelle topology. OTCCP was used to classify a panel of human breast cancer cells, grown as 2D monolayer or 3D tumor spheroids using early endosomes, mitochondria, and their inter-organelle contacts. Organelle topology allows for a highly precise differentiation between cell lines of different subtypes and aggressiveness. These findings lay the groundwork for using organelle topological profiling as a fast and efficient method for phenotyping breast cancer function as well as a discovery tool to advance our understanding of cancer cell biology at the subcellular level.

Indexed as

CancerCell biologyOrganizational aspects of cell biology

Identifiers

PMID37519903
PMCPMC10384275

What Socratic holds

Textmetadata
LicenceCC BY-NC-ND
Read underepoch 390

Registered trials

None linked

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.