Evidence map›Paper›PMID 38349551›Full record

ArticleCancer research communications2024

Stromal Signals Dominate Gene Expression Signature Scores That Aim to Describe Cancer Cell-intrinsic Stemness or Mesenchymality Characteristics.

Julian Kreis, Bogac Aybey, Felix Geist, Benedikt Brors, Eike Staub

Open access · goldAbstract read
In one paragraph

Article in Cancer research communications, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.

0numbers the graph read from it
0cells of the map it votes in
12citing papers in PubMed
2.5field-weighted citation impact, top 9% 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

12 citing papers in PubMed, 9 citations in OpenAlex.

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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

5 authors at 2 institutions in 1 country.

Julian KreisThe healthcare business of Merck KGaA, Darmstadt, Germany.ORCID 0000-0002-1084-8481
Bogac AybeyThe healthcare business of Merck KGaA, Darmstadt, Germany.ORCID 0000-0002-8183-831X
Felix GeistThe healthcare business of Merck KGaA, Darmstadt, Germany.ORCID 0000-0002-4196-9550
Benedikt BrorsDivision of Applied Bioinformatics, German Cancer Research Center (DKFZ), Heidelberg University, Heidelberg, Germany.ORCID 0000-0001-5940-3101
Eike StaubThe healthcare business of Merck KGaA, Darmstadt, Germany.ORCID 0000-0002-5039-3098
Merck (Germany) · DEGerman Cancer Research Center · DE

Funding

Merck | Merck Healthcare KGaA (Merck Healthcare) 10.13039/100009945
6 · The paper itself

Abstract

Epithelial-to-mesenchymal transition (EMT) in cancer cells confers migratory abilities, a crucial aspect in the metastasis of tumors that frequently leads to death. In multiple studies, authors proposed gene expression signatures for EMT, stemness, or mesenchymality of tumors based on bulk tumor expression profiling. However, recent studies suggested that noncancerous cells from the microenvironment or macroenvironment heavily influence such signature profiles. Here, we strengthen these findings by investigating 11 published and frequently referenced gene expression signatures that were proposed to describe EMT-related (EMT, mesenchymal, or stemness) characteristics in various cancer types. By analyses of bulk, single-cell, and pseudobulk expression data, we show that the cell type composition of a tumor sample frequently dominates scores of these EMT-related signatures. A comprehensive, integrated analysis of bulk RNA sequencing (RNA-seq) and single-cell RNA-seq data shows that stromal cells, most often fibroblasts, are the main drivers of EMT-related signature scores. We call attention to the risk of false conclusions about tumor properties when interpreting EMT-related signatures, especially in a clinical setting: high patient scores of EMT-related signatures or calls of "stemness subtypes" often result from low cancer cell content in tumor biopsies rather than cancer cell-specific stemness or mesenchymal/EMT characteristics. SIGNIFICANCE: Cancer self-renewal and migratory abilities are often characterized via gene module expression profiles, also called EMT or stemness gene expression signatures. Using published clinical tumor samples, cancer cell lines, and single cancer cells, we highlight the dominating influence of noncancer cells in low cancer cell content biopsies on their scores. We caution on their application for low cancer cell content clinical cancer samples with the intent to assign such characteristics or subtypes.

Indexed as

NeoplasmsTranscriptomeEpithelial-Mesenchymal TransitionHumansStromal CellsTumor Microenvironment

Identifiers

PMID38349551
PMCPMC10885853
OpenAlexW4391775741

What OpenQuestion holds

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LicenceCC BY
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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.