Evidence map›Paper›PMID 36921599›Full record

ArticleCell reports. Medicine2023

Multiplex imaging of breast cancer lymph node metastases identifies prognostic single-cell populations independent of clinical classifiers.

Jana Raja Fischer, Hartland Warren Jackson, Natalie de Souza, Zsuzsanna Varga, Peter Schraml, Holger Moch, Bernd Bodenmiller

Open access · goldAbstract read
In one paragraph

Article in Cell reports. Medicine, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 24 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
24citing papers in PubMed, 1 pooled it
5.4field-weighted citation impact, top 4% of its field
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

24 citing papers in PubMed, 1 synthesis or guideline pooled it, 36 citations in OpenAlex.

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  20. Multiplex protein imaging in tumour biology.Nature reviews. Cancer · 2024
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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

7 authors at 3 institutions in 1 country.

Jana Raja FischerDepartment of Quantitative Biomedicine, University of Zurich, Zurich, Switzerland; Institute of Molecular Health Sciences, ETH Zurich, Zurich, Switzerland; Life Science Zurich Graduate School, ETH Zurich and University of Zurich, Zurich, Switzerland.
Hartland Warren JacksonDepartment of Quantitative Biomedicine, University of Zurich, Zurich, Switzerland. Electronic address: hjackson@lunenfeld.ca.
Natalie de SouzaDepartment of Quantitative Biomedicine, University of Zurich, Zurich, Switzerland; Institute of Molecular Health Sciences, ETH Zurich, Zurich, Switzerland; Institute of Molecular Systems Biology, ETH Zurich, Zurich, Switzerland.
Zsuzsanna VargaDepartment of Pathology and Molecular Pathology, University and University Hospital Zurich, Zurich, Switzerland.
Peter SchramlDepartment of Pathology and Molecular Pathology, University and University Hospital Zurich, Zurich, Switzerland.
Holger MochDepartment of Pathology and Molecular Pathology, University and University Hospital Zurich, Zurich, Switzerland.
Bernd BodenmillerDepartment of Quantitative Biomedicine, University of Zurich, Zurich, Switzerland; Institute of Molecular Health Sciences, ETH Zurich, Zurich, Switzerland. Electronic address: bernd.bodenmiller@uzh.ch.
University Hospital of Zurich · CHUniversity of Zurich · CHLife Science Zurich · CH

Funding

Single-Cell Analyses of Human Islets in T1D Using Highly Multiplexed ImagingUC4DK108132 · NIDDK · UNIVERSITY OF FLORIDA · PI ATKINSON, MARK A., BODENMILLER, BERND · 2015 to 2015
$3.6M
NIDDK NIH HHS UC4 DK108132
6 · The paper itself

Abstract

Although breast cancer mortality is largely caused by metastasis, clinical decisions are based on analysis of the primary tumor and on lymph node involvement but not on the phenotype of disseminated cells. Here, we use multiplex imaging mass cytometry to compare single-cell phenotypes of primary breast tumors and matched lymph node metastases in 205 patients. We observe extensive phenotypic variability between primary and metastatic sites and that disseminated cell phenotypes frequently deviate from the clinical disease subtype. We identify single-cell phenotypes and spatial organizations of disseminated tumor cells that are associated with patient survival and a weaker survival association for high-risk phenotypes in the primary tumor. We show that p53 and GATA3 in lymph node metastases provide prognostic information beyond clinical classifiers and can be measured with standard methods. Molecular characterization of disseminated tumor cells is an untapped source of clinically applicable prognostic information for breast cancer.

Indexed as

Lymph NodesHumansLymphatic MetastasisPrognosisbreast cancerdisseminating tumor cellsimaging mass cytometrylymph node metastasesmetastasismetastatic processmultiplexed imagingprognostics signaturesingle-cell analysissurvival analysis

Identifiers

PMID36921599
PMCPMC10040454
OpenAlexW4324139446

What OpenQuestion 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 OpenQuestion graph.