Evidence map›Paper›PMID 26020769›Full record

ArticlePLoS computational biology2015

Causal Modeling of Cancer-Stromal Communication Identifies PAPPA as a Novel Stroma-Secreted Factor Activating NFκB Signaling in Hepatocellular Carcinoma.

Julia C Engelmann, Thomas Amann, Birgitta Ott-Rötzer, Margit Nützel, Yvonne Reinders, Jörg Reinders, Wolfgang E Thasler, Theresa Kristl, Andreas Teufel, Christian G Huber and 3 more

Open access · goldAbstract read
In one paragraph

Article in PLoS computational biology, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
18citing papers in PubMed, 1 pooled it
1.2field-weighted citation impact, top 21% 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

18 citing papers in PubMed, 1 synthesis or guideline pooled it, 33 citations in OpenAlex.

  1. Pooled it
  2. Article
  3. Pan-Cancer Analysis ofBiology · 2026
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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

13 authors at 4 institutions in 2 countries.

Julia C EngelmannDepartment of Statistical Bioinformatics, University of Regensburg, Regensburg, Germany.
Thomas AmannDepartment of Internal Medicine I, University Hospital Regensburg, Regensburg, Germany.
Birgitta Ott-RötzerDepartment of Internal Medicine I, University Hospital Regensburg, Regensburg, Germany.
Margit NützelDepartment of Internal Medicine I, University Hospital Regensburg, Regensburg, Germany.
Yvonne ReindersInstitute of Functional Genomics, University of Regensburg, Regensburg, Germany.
Jörg ReindersInstitute of Functional Genomics, University of Regensburg, Regensburg, Germany.
Wolfgang E ThaslerBiobank under the authority of Human Tissue and Cell Research (HTCR) and Center for Liver Cell Research, Department of General, Visceral, Transplantation, Vascular and Thoracic Surgery, Hospital of Ludwig-Maximilians-University of Munich, Munich, Germany.
Theresa KristlDepartment of Molecular Biology, Division of Chemistry and Bioanalytics, University of Salzburg, Salzburg, Austria.
Andreas TeufelDepartment of Internal Medicine I, University Hospital Regensburg, Regensburg, Germany.
Christian G HuberDepartment of Molecular Biology, Division of Chemistry and Bioanalytics, University of Salzburg, Salzburg, Austria.
Peter J OefnerInstitute of Functional Genomics, University of Regensburg, Regensburg, Germany.
Rainer SpangDepartment of Statistical Bioinformatics, University of Regensburg, Regensburg, Germany.
Claus HellerbrandDepartment of Internal Medicine I, University Hospital Regensburg, Regensburg, Germany.
University Hospital Regensburg · DEUniversity of Regensburg · DEUniversity of Salzburg · ATLudwig-Maximilians-Universität München · DE

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Inter-cellular communication with stromal cells is vital for cancer cells. Molecules involved in the communication are potential drug targets. To identify them systematically, we applied a systems level analysis that combined reverse network engineering with causal effect estimation. Using only observational transcriptome profiles we searched for paracrine factors sending messages from activated hepatic stellate cells (HSC) to hepatocellular carcinoma (HCC) cells. We condensed these messages to predict ten proteins that, acting in concert, cause the majority of the gene expression changes observed in HCC cells. Among the 10 paracrine factors were both known and unknown cancer promoting stromal factors, the former including Placental Growth Factor (PGF) and Periostin (POSTN), while Pregnancy-Associated Plasma Protein A (PAPPA) was among the latter. Further support for the predicted effect of PAPPA on HCC cells came from both in vitro studies that showed PAPPA to contribute to the activation of NFκB signaling, and clinical data, which linked higher expression levels of PAPPA to advanced stage HCC. In summary, this study demonstrates the potential of causal modeling in combination with a condensation step borrowed from gene set analysis [Model-based Gene Set Analysis (MGSA)] in the identification of stromal signaling molecules influencing the cancer phenotype.

Indexed as

Carcinoma, HepatocellularCell Adhesion MoleculesCell CommunicationCell Line, TumorComputational BiologyDrug DesignGene Expression ProfilingGene Expression Regulation, NeoplasticHepatic Stellate CellsHep G2 CellsHumansLiverLiver NeoplasmsNF-kappa BOligonucleotide Array Sequence AnalysisPlacenta Growth FactorCell Adhesion MoleculesNF-kappa BPAPPA protein, humanPGF protein, humanPlacenta Growth FactorPOSTN protein, humanPregnancy-Associated Plasma Protein-APregnancy Proteins

Identifiers

PMID26020769
PMCPMC4447342
OpenAlexW2149370533

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.