Evidence map›Paper›PMID 32081986›Full record

ArticleCell death and differentiation2020

Convergence of pathway analysis and pattern recognition predicts sensitization to latest generation TRAIL therapeutics by IAP antagonism.

Vesna Vetma, Cristiano Guttà, Nathalie Peters, Christian Praetorius, Meike Hutt, Oliver Seifert, Friedegund Meier, Roland Kontermann, Dagmar Kulms, Markus Rehm

Open access · hybridAbstract read
In one paragraph

Article in Cell death and differentiation, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.

0numbers the graph read from it
0cells of the map it votes in
14citing papers in PubMed
2.2field-weighted citation impact, top 10% 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

14 citing papers in PubMed, 25 citations in OpenAlex.

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  8. No Time to Die: How Kidney Cancer Evades Cell Death.International journal of molecular sciences · 2022
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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

10 authors at 3 institutions in 2 countries.

Vesna Vetma *Institute of Cell Biology and Immunology, University of Stuttgart, Stuttgart, Germany.
Cristiano Guttà *Institute of Cell Biology and Immunology, University of Stuttgart, Stuttgart, Germany.
Nathalie PetersInstitute of Cell Biology and Immunology, University of Stuttgart, Stuttgart, Germany.
Christian PraetoriusCenter for Regenerative Therapies, Technical University Dresden, Dresden, Germany.ORCID http://orcid.org/0000-0001-7514-5333
Meike HuttInstitute of Cell Biology and Immunology, University of Stuttgart, Stuttgart, Germany.
Oliver SeifertInstitute of Cell Biology and Immunology, University of Stuttgart, Stuttgart, Germany.
Friedegund MeierSkin Cancer Center at the University Cancer Centre, Department of Dermatology, Faculty of Medicine, University Hospital Carl Gustav Carus, Technical University Dresden, Dresden, Germany.
Roland KontermannInstitute of Cell Biology and Immunology, University of Stuttgart, Stuttgart, Germany.
Dagmar KulmsCenter for Regenerative Therapies, Technical University Dresden, Dresden, Germany.
Markus RehmInstitute of Cell Biology and Immunology, University of Stuttgart, Stuttgart, Germany. markus.morrison@izi.uni-stuttgart.de.ORCID http://orcid.org/0000-0001-6149-9261
University of Stuttgart · DEUniversity Hospital Carl Gustav Carus · DEGerman Cancer Research Center · DE

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Second generation TRAIL-based therapeutics, combined with sensitising co-treatments, have recently entered clinical trials. However, reliable response predictors for optimal patient selection are not yet available. Here, we demonstrate that a novel and translationally relevant hexavalent TRAIL receptor agonist, IZI1551, in combination with Birinapant, a clinically tested IAP antagonist, efficiently induces cell death in various melanoma models, and that responsiveness can be predicted by combining pathway analysis, data-driven modelling and pattern recognition. Across a panel of 16 melanoma cell lines, responsiveness to IZI1551/Birinapant was heterogeneous, with complete resistance and pronounced synergies observed. Expression patterns of TRAIL pathway regulators allowed us to develop a combinatorial marker that predicts potent cell killing with high accuracy. IZI1551/Birinapant responsiveness could be predicted not only for cell lines, but also for 3D tumour cell spheroids and for cells directly isolated from patient melanoma metastases (80-100% prediction accuracies). Mathematical parameter reduction identified 11 proteins crucial to ensure prediction accuracy, with x-linked inhibitor of apoptosis protein (XIAP) and procaspase-3 scoring highest, and Bcl-2 family members strongly represented. Applied to expression data of a cohort of n = 365 metastatic melanoma patients in a proof of concept in silico trial, the predictor suggested that IZI1551/Birinapant responsiveness could be expected for up to 30% of patient tumours. Overall, response frequencies in melanoma models were very encouraging, and the capability to predict melanoma sensitivity to combinations of latest generation TRAIL-based therapeutics and IAP antagonists can address the need for patient selection strategies in clinical trials based on these novel drugs.

Indexed as

Pattern Recognition, AutomatedApoptosisCell Line, TumorCell ProliferationDipeptidesHumansIndolesInhibitor of Apoptosis ProteinsNeoplasm MetastasisTNF-Related Apoptosis-Inducing LigandbirinapantDipeptidesIndolesInhibitor of Apoptosis ProteinsTNF-Related Apoptosis-Inducing Ligand

Identifiers

PMID32081986
PMCPMC7370234
OpenAlexW3007079969

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.