Evidence map›Paper›PMID 39474071›Full record

ArticleiScience2024

Mesothelioma survival prediction based on a six-gene transcriptomic signature.

Kiarash Behrouzfar, Steve E Mutsaers, Wee Loong Chin, Kimberley Patrick, Isaac Trinstern Ng, Fiona J Pixley, Grant Morahan, Richard A Lake, Scott A Fisher

Abstract read
In one paragraph

Article in iScience, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. Article
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

9 authors.

Kiarash BehrouzfarNational Centre for Asbestos Related Diseases, University of Western Australia, Nedlands, WA, Australia.
Steve E MutsaersSchool of Biomedical Sciences, University of Western Australia, Perth, WA, Australia.
Wee Loong ChinNational Centre for Asbestos Related Diseases, University of Western Australia, Nedlands, WA, Australia.
Kimberley PatrickNational Centre for Asbestos Related Diseases, University of Western Australia, Nedlands, WA, Australia.
Isaac Trinstern NgSchool of Biomedical Sciences, University of Western Australia, Perth, WA, Australia.
Fiona J PixleySchool of Biomedical Sciences, University of Western Australia, Perth, WA, Australia.
Grant MorahanCentre for Diabetes Research, Harry Perkins Institute of Medical Research, Perth, WA, Australia.
Richard A LakeNational Centre for Asbestos Related Diseases, University of Western Australia, Nedlands, WA, Australia.
Scott A FisherNational Centre for Asbestos Related Diseases, University of Western Australia, Nedlands, WA, Australia.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Mesothelioma is a lethal cancer. Despite promising outcomes associated with immunotherapy, durable responses remain restricted to a minority of patients, highlighting the need for improved strategies that better predict outcome. Here, we described the development of a mesothelioma-specific gene signature that accurately predicts survival. Comprehensive gene expression analysis of asbestos exposed MexTAg Collaborative Cross mouse tumors revealed distinct tumor clusters characterized by epithelial mesenchymal transition/extracellular matrix, or immune infiltrate related gene expression profiles. Weighted gene co-expression network analysis (WGCNA) identified 20 hub genes that drove differential gene expression. Human homologues of these 20 hub genes were refined through univariate Cox regression and least absolute shrinkage and selection operator (LASSO) regression analyses to identify a six-gene mesothelioma-specific prognostic signature that accurately predicted patient survival across four independent human mesothelioma datasets. Furthermore, this six-gene signature demonstrated the potential to predict treatment response, thus advancing the management of this challenging malignancy.

Indexed as

Biological sciencesCancerGenetics

Identifiers

PMID39474071
PMCPMC11519557

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.