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Determination of the Cancer Genome Atlas (TCGA) Endometrial Cancer Molecular Subtypes Using the Variant Interpretation and Clinical Decision Support Software MH Guide
SIMPLE SUMMARY: Besides the diagnosis of endometrial carcinoma (EC), the identification of EC subtypes is an important precondition for the effective treatment of the disease. Molecular factors have an important role in this context. Biomedical analysis is already very possible in experimental appro...
Autores principales: | , , , , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10093381/ https://www.ncbi.nlm.nih.gov/pubmed/37046713 http://dx.doi.org/10.3390/cancers15072053 |
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author | Mustea, Alexander Ralser, Damian J. Egger, Eva Ziehm, Ulrike Vivas, Sonia Brock, Stephan Jackson, David Condic, Mateja Meisel, Christian Otten, Lucia Laib, Anna Cordova, Miguel Cubas Hartmann, Rahel Stein, Martin A. Koensgen, Dominique Stope, Matthias B. |
author_facet | Mustea, Alexander Ralser, Damian J. Egger, Eva Ziehm, Ulrike Vivas, Sonia Brock, Stephan Jackson, David Condic, Mateja Meisel, Christian Otten, Lucia Laib, Anna Cordova, Miguel Cubas Hartmann, Rahel Stein, Martin A. Koensgen, Dominique Stope, Matthias B. |
author_sort | Mustea, Alexander |
collection | PubMed |
description | SIMPLE SUMMARY: Besides the diagnosis of endometrial carcinoma (EC), the identification of EC subtypes is an important precondition for the effective treatment of the disease. Molecular factors have an important role in this context. Biomedical analysis is already very possible in experimental approaches. However, for clinical practice the procedures are often too complex, too expensive, and too time-consuming. In the present study, very good evaluated molecular markers were detected using an alternative method and compared with the original method. Analyses showed very good results. The important advantage of the new procedure is that the required molecular data can be obtained exclusively by sequencing. This may greatly simplify EC subtype classification and could be more easily incorporated into routine clinical diagnosis. ABSTRACT: Background: The Cancer Genome Atlas (TCGA) network (United States National Cancer Institute) identified four molecular endometrial cancer (EC) subtypes using an extensive multi-method approach. The aim of this study was to determine the four TCGA EC molecular subtypes using a single-method whole-exome sequencing (WES)-based approach provided by MH Guide (Molecular Health, Heidelberg, Germany). Methods: WES and clinical data of n = 232 EC patients were obtained from TCGA. The four TCGA EC molecular subtypes designated as (i) Mutated Polymerase ε (POLE), (ii) Microsatellite Instability (MSI), (iii) Copy Number (CN) low and, (iv) CN-high were determined using the MH Guide software. The prognostic value of the subtypes determined by MH Guide were compared with the TCGA classification. Results: Analysis of WES data using the MH Guide software led to the precise identification of the four EC molecular subtypes analogous to the TCGA classification. Both approaches displayed high concordance in terms of prognostic significance. Conclusions: The multi-method-based TCGA EC molecular subtypes can reliably be reproduced by the single-method-based MH Guide approach. The easy-to-implement single-method MH Guide approach represents a promising diagnostic tool. |
format | Online Article Text |
id | pubmed-10093381 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-100933812023-04-13 Determination of the Cancer Genome Atlas (TCGA) Endometrial Cancer Molecular Subtypes Using the Variant Interpretation and Clinical Decision Support Software MH Guide Mustea, Alexander Ralser, Damian J. Egger, Eva Ziehm, Ulrike Vivas, Sonia Brock, Stephan Jackson, David Condic, Mateja Meisel, Christian Otten, Lucia Laib, Anna Cordova, Miguel Cubas Hartmann, Rahel Stein, Martin A. Koensgen, Dominique Stope, Matthias B. Cancers (Basel) Article SIMPLE SUMMARY: Besides the diagnosis of endometrial carcinoma (EC), the identification of EC subtypes is an important precondition for the effective treatment of the disease. Molecular factors have an important role in this context. Biomedical analysis is already very possible in experimental approaches. However, for clinical practice the procedures are often too complex, too expensive, and too time-consuming. In the present study, very good evaluated molecular markers were detected using an alternative method and compared with the original method. Analyses showed very good results. The important advantage of the new procedure is that the required molecular data can be obtained exclusively by sequencing. This may greatly simplify EC subtype classification and could be more easily incorporated into routine clinical diagnosis. ABSTRACT: Background: The Cancer Genome Atlas (TCGA) network (United States National Cancer Institute) identified four molecular endometrial cancer (EC) subtypes using an extensive multi-method approach. The aim of this study was to determine the four TCGA EC molecular subtypes using a single-method whole-exome sequencing (WES)-based approach provided by MH Guide (Molecular Health, Heidelberg, Germany). Methods: WES and clinical data of n = 232 EC patients were obtained from TCGA. The four TCGA EC molecular subtypes designated as (i) Mutated Polymerase ε (POLE), (ii) Microsatellite Instability (MSI), (iii) Copy Number (CN) low and, (iv) CN-high were determined using the MH Guide software. The prognostic value of the subtypes determined by MH Guide were compared with the TCGA classification. Results: Analysis of WES data using the MH Guide software led to the precise identification of the four EC molecular subtypes analogous to the TCGA classification. Both approaches displayed high concordance in terms of prognostic significance. Conclusions: The multi-method-based TCGA EC molecular subtypes can reliably be reproduced by the single-method-based MH Guide approach. The easy-to-implement single-method MH Guide approach represents a promising diagnostic tool. MDPI 2023-03-30 /pmc/articles/PMC10093381/ /pubmed/37046713 http://dx.doi.org/10.3390/cancers15072053 Text en © 2023 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Mustea, Alexander Ralser, Damian J. Egger, Eva Ziehm, Ulrike Vivas, Sonia Brock, Stephan Jackson, David Condic, Mateja Meisel, Christian Otten, Lucia Laib, Anna Cordova, Miguel Cubas Hartmann, Rahel Stein, Martin A. Koensgen, Dominique Stope, Matthias B. Determination of the Cancer Genome Atlas (TCGA) Endometrial Cancer Molecular Subtypes Using the Variant Interpretation and Clinical Decision Support Software MH Guide |
title | Determination of the Cancer Genome Atlas (TCGA) Endometrial Cancer Molecular Subtypes Using the Variant Interpretation and Clinical Decision Support Software MH Guide |
title_full | Determination of the Cancer Genome Atlas (TCGA) Endometrial Cancer Molecular Subtypes Using the Variant Interpretation and Clinical Decision Support Software MH Guide |
title_fullStr | Determination of the Cancer Genome Atlas (TCGA) Endometrial Cancer Molecular Subtypes Using the Variant Interpretation and Clinical Decision Support Software MH Guide |
title_full_unstemmed | Determination of the Cancer Genome Atlas (TCGA) Endometrial Cancer Molecular Subtypes Using the Variant Interpretation and Clinical Decision Support Software MH Guide |
title_short | Determination of the Cancer Genome Atlas (TCGA) Endometrial Cancer Molecular Subtypes Using the Variant Interpretation and Clinical Decision Support Software MH Guide |
title_sort | determination of the cancer genome atlas (tcga) endometrial cancer molecular subtypes using the variant interpretation and clinical decision support software mh guide |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10093381/ https://www.ncbi.nlm.nih.gov/pubmed/37046713 http://dx.doi.org/10.3390/cancers15072053 |
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