Evidence map›Paper›PMID 36879816›Full record

ArticleiScience2023

MSIMEP: Predicting microsatellite instability from microarray DNA methylation tumor profiles.

Martín Santamarina-García, Jenifer Brea-Iglesias, Jesper Bertram Bramsen, Mar Fuentes-Losada, Francisco Javier Caneiro-Gómez, José Ángel Vázquez-Bueno, Héctor Lázare-Iglesias, Natalia Fernández-Díaz, Laura Sánchez-Rivadulla, Yoel Z Betancor and 9 more

Open access · goldAbstract read
In one paragraph

Article in iScience, 2023. 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
1.0field-weighted citation impact, top 25% 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

1 citing paper in PubMed, 4 citations in OpenAlex.

  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

19 authors at 9 institutions in 3 countries.

Martín Santamarina-GarcíaGenomes and Disease, Centre for Research in Molecular Medicine and Chronic Diseases (CiMUS), University of Santiago de Compostela (USC), 15706 Santiago de Compostela, Spain.
Jenifer Brea-IglesiasGenomes and Disease, Centre for Research in Molecular Medicine and Chronic Diseases (CiMUS), University of Santiago de Compostela (USC), 15706 Santiago de Compostela, Spain.
Jesper Bertram BramsenDepartment of Molecular Medicine, Aarhus University Hospital, 8200 Aarhus, Denmark.
Mar Fuentes-LosadaDepartment of Medical Oncology, University Clinical Hospital of Santiago de Compostela (SERGAS), University of Santiago de Compostela (USC), 15706 Santiago de Compostela, Spain.
Francisco Javier Caneiro-GómezDepartment of Pathology, University Clinical Hospital of Santiago de Compostela, University of Santiago de Compostela (USC), 15706 Santiago de Compostela, Spain.
José Ángel Vázquez-BuenoDepartment of Pathology, Complejo Hospitalario Universitario de Ferrol, 15405 Ferrol, Spain.
Héctor Lázare-IglesiasDepartment of Pathology, University Clinical Hospital of Santiago de Compostela, University of Santiago de Compostela (USC), 15706 Santiago de Compostela, Spain.
Natalia Fernández-DíazDepartment of Medical Oncology, University Clinical Hospital of Santiago de Compostela (SERGAS), University of Santiago de Compostela (USC), 15706 Santiago de Compostela, Spain.
Laura Sánchez-RivadullaDepartment of Gynaecology and Obstetrics, Complejo Hospitalario Universitario de Ferrol, 15405 Ferrol, Spain.
Yoel Z BetancorGenomes and Disease, Centre for Research in Molecular Medicine and Chronic Diseases (CiMUS), University of Santiago de Compostela (USC), 15706 Santiago de Compostela, Spain.
Miriam Ferreiro-PantínGenomes and Disease, Centre for Research in Molecular Medicine and Chronic Diseases (CiMUS), University of Santiago de Compostela (USC), 15706 Santiago de Compostela, Spain.
Pablo Conesa-ZamoraDepartment of Clinical Analysis, Santa Lucía University Hospital, 30202 Cartagena, Spain.
José Ramón Antúnez-LópezDepartment of Pathology, University Clinical Hospital of Santiago de Compostela, University of Santiago de Compostela (USC), 15706 Santiago de Compostela, Spain.
Masahito KawazuChiba Cancer Center, Research Institute, 260-0801 Chiba, Japan.
Manel EstellerJosep Carreras Leukaemia Research Institute (IJC), 08916 Badalona, Barcelona, Spain.
Claus Lindbjerg AndersenDepartment of Molecular Medicine, Aarhus University Hospital, 8200 Aarhus, Denmark.
Jose M C TubioGenomes and Disease, Centre for Research in Molecular Medicine and Chronic Diseases (CiMUS), University of Santiago de Compostela (USC), 15706 Santiago de Compostela, Spain.
Rafael López-LópezDepartment of Medical Oncology, University Clinical Hospital of Santiago de Compostela (SERGAS), University of Santiago de Compostela (USC), 15706 Santiago de Compostela, Spain.
Juan Ruiz-BañobreGenomes and Disease, Centre for Research in Molecular Medicine and Chronic Diseases (CiMUS), University of Santiago de Compostela (USC), 15706 Santiago de Compostela, Spain.
Universidade de Santiago de Compostela · ESServicio Gallego de Salud · ESAarhus University Hospital · DKCenter for Research in Molecular Medicine and Chronic Diseases · ESCentro de Investigación Biomédica en Red de Cáncer · ESChiba Cancer Center · JPComplejo Hospitalario Universitario de Ferrol · ESSanta Lucía University General Hospital · ESUniversitat de Barcelona · ES

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Deficiency in DNA MMR activity results in tumors with a hypermutator phenotype, termed microsatellite instability (MSI). Beyond its utility in Lynch syndrome screening algorithms, today MSI has gained importance as predictive biomarker for various anti-PD-1 therapies across many different tumor types. Over the past years, many computational methods have emerged to infer MSI using either DNA- or RNA-based approaches. Considering this together with the fact that MSI-high tumors frequently exhibit a hypermethylated phenotype, herein we developed and validated MSIMEP, a computational tool for predicting MSI status from microarray DNA methylation tumor profiles of colorectal cancer samples. We demonstrated that MSIMEP optimized and reduced models have high performance in predicting MSI in different colorectal cancer cohorts. Moreover, we tested its consistency in other tumor types with high prevalence of MSI such as gastric and endometrial cancers. Finally, we demonstrated better performance of both MSIMEP models vis-à-vis a MLH1 promoter methylation-based one in colorectal cancer.

Indexed as

Cancer systems biologyGenomic analysisMedical informatics

Identifiers

PMID36879816
PMCPMC9984554
OpenAlexW4319072029

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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.