Evidence map›Paper›PMID 28372546›Full record

ArticleMolecular cancer2017

Cellular organization and molecular differentiation model of breast cancer-associated fibroblasts.

Susann Busch, Daniel Andersson, Eva Bom, Claire Walsh, Anders Ståhlberg, Göran Landberg

Abstract read
In one paragraph

Article in Molecular cancer, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 34 papers.

0numbers the graph read from it
0cells of the map it votes in
34citing 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

34 citing papers in PubMed.

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  10. Application of single-cell RNA sequencing in head and neck squamous cell carcinoma.Chinese journal of cancer research = Chung-kuo yen cheng yen chiu · 2023
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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

6 authors.

Susann BuschDepartment of Pathology, Sahlgrenska Cancer Center, Institute of Biomedicine, Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden. Susann.Busch@gu.se.ORCID 0000-0001-8119-086X
Daniel AnderssonDepartment of Pathology, Sahlgrenska Cancer Center, Institute of Biomedicine, Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden.
Eva BomDepartment of Surgery, Institute of Clinical Sciences, Transplantation and Regenerative Medicine, Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden.
Claire WalshDepartment of Pathology, Sahlgrenska Cancer Center, Institute of Biomedicine, Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden.
Anders StåhlbergDepartment of Pathology, Sahlgrenska Cancer Center, Institute of Biomedicine, Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden.
Göran LandbergDepartment of Pathology, Sahlgrenska Cancer Center, Institute of Biomedicine, Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThe role of cancer-associated fibroblasts (CAFs) during tumour progression is obscured by the inherently complex, heterotypic nature of fibroblast cells and behaviours in various subtypes of malignancies. Therefore, we sought to identify distinct fibroblast subpopulations at the single-cell level.

methodsUsing single-cell quantitative PCR as a powerful tool to study heterogeneity and rare cell events, in a high-throughput manner a panel of gene targets are run simultaneously on transcripts isolated from single cells obtained by fluorescence-activated cell sort. Assessment of cells with stem-like characteristics was attained by anchorage-independent, anoikis-resistant culture.

resultsSingle-cell analysis of fibroblasts and their tumour-activated counterparts demonstrated molecularly distinct cell types defined by differential expression of characteristic mesenchymal and fibroblast activation markers. Identified subpopulations presented overlapping gene expression patterns indicating transitional molecular states during fibroblast differentiation. Using single-cell resolution data we generated a molecular differentiation model which enabled the classification of patient-derived fibroblasts, validating our modelling approach. Remarkably, a subset of fibroblasts displayed expression of pluripotency markers, which was enriched for in non-adherent conditions. Yet the ability to form single-cell derived spheres was generally reduced in CAFs and upon fibroblast activation through TGFβ1 ligand and cancer cell-secreted factors. Hence, our data imply the existence of putative stem/progenitor cells as a physiological feature of undifferentiated fibroblasts.

conclusionsWithin this comprehensive study we have identified distinct and intersecting molecular profiles defining fibroblast activation states and propose that underlying cellular heterogeneity, fibroblasts are hierarchically organized. Understanding the molecular make-up of cellular organization and differentiation routes will facilitate the discovery of more specific markers for stromal subtypes and targets for anti-stromal therapies.

Indexed as

AnoikisBiomarkers, TumorBreast NeoplasmsCancer-Associated FibroblastsCell LineCluster AnalysisFemaleGene Expression ProfilingHumansSingle-Cell AnalysisTumor MicroenvironmentBiomarkers, TumorBreast cancerCancer-associated fibroblastSingle-cell analysisTumour stroma

Identifiers

PMID28372546
PMCPMC5376683

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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.