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Optimized Transcriptional Signature for Evaluation of MEK/ERK Pathway Baseline Activity and Long-Term Modulations in Ovarian Cancer

Ovarian cancer is the most aggressive and lethal of all gynecologic malignancies. The high activity of the MEK/ERK signaling pathway is tightly associated with tumor growth, high recurrence rate, and treatment resistance. Several transcriptional signatures were proposed recently for evaluation of ME...

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Detalles Bibliográficos
Autores principales: Chesnokov, Mikhail S., Yadav, Anil, Chefetz, Ilana
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9654336/
https://www.ncbi.nlm.nih.gov/pubmed/36362153
http://dx.doi.org/10.3390/ijms232113365
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author Chesnokov, Mikhail S.
Yadav, Anil
Chefetz, Ilana
author_facet Chesnokov, Mikhail S.
Yadav, Anil
Chefetz, Ilana
author_sort Chesnokov, Mikhail S.
collection PubMed
description Ovarian cancer is the most aggressive and lethal of all gynecologic malignancies. The high activity of the MEK/ERK signaling pathway is tightly associated with tumor growth, high recurrence rate, and treatment resistance. Several transcriptional signatures were proposed recently for evaluation of MEK/ERK activity in tumor tissue. In the present study, we validated the performance of a robust multi-cancer MPAS 10-gene signature in various experimental models and publicly available sets of ovarian cancer samples. Expression of four MPAS genes (PHLDA1, DUSP4, EPHA2, and SPRY4) displayed reproducible responses to MEK/ERK activity modulations across several experimental models in vitro and in vivo. Levels of PHLDA1, DUSP4, and EPHA2 expression were also significantly associated with baseline levels of MEK/ERK pathway activity in multiple human ovarian cancer cell lines and ovarian cancer patient samples available from the TCGA database. Initial platinum therapy resistance and advanced age at diagnosis were independently associated with poor overall patient survival. Taken together, our results demonstrate that the performance of transcriptional signatures is significantly affected by tissue specificity and aspects of particular experimental models. We therefore propose that gene expression signatures derived from comprehensive multi-cancer studies should be always validated for each cancer type.
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spelling pubmed-96543362022-11-15 Optimized Transcriptional Signature for Evaluation of MEK/ERK Pathway Baseline Activity and Long-Term Modulations in Ovarian Cancer Chesnokov, Mikhail S. Yadav, Anil Chefetz, Ilana Int J Mol Sci Article Ovarian cancer is the most aggressive and lethal of all gynecologic malignancies. The high activity of the MEK/ERK signaling pathway is tightly associated with tumor growth, high recurrence rate, and treatment resistance. Several transcriptional signatures were proposed recently for evaluation of MEK/ERK activity in tumor tissue. In the present study, we validated the performance of a robust multi-cancer MPAS 10-gene signature in various experimental models and publicly available sets of ovarian cancer samples. Expression of four MPAS genes (PHLDA1, DUSP4, EPHA2, and SPRY4) displayed reproducible responses to MEK/ERK activity modulations across several experimental models in vitro and in vivo. Levels of PHLDA1, DUSP4, and EPHA2 expression were also significantly associated with baseline levels of MEK/ERK pathway activity in multiple human ovarian cancer cell lines and ovarian cancer patient samples available from the TCGA database. Initial platinum therapy resistance and advanced age at diagnosis were independently associated with poor overall patient survival. Taken together, our results demonstrate that the performance of transcriptional signatures is significantly affected by tissue specificity and aspects of particular experimental models. We therefore propose that gene expression signatures derived from comprehensive multi-cancer studies should be always validated for each cancer type. MDPI 2022-11-01 /pmc/articles/PMC9654336/ /pubmed/36362153 http://dx.doi.org/10.3390/ijms232113365 Text en © 2022 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
Chesnokov, Mikhail S.
Yadav, Anil
Chefetz, Ilana
Optimized Transcriptional Signature for Evaluation of MEK/ERK Pathway Baseline Activity and Long-Term Modulations in Ovarian Cancer
title Optimized Transcriptional Signature for Evaluation of MEK/ERK Pathway Baseline Activity and Long-Term Modulations in Ovarian Cancer
title_full Optimized Transcriptional Signature for Evaluation of MEK/ERK Pathway Baseline Activity and Long-Term Modulations in Ovarian Cancer
title_fullStr Optimized Transcriptional Signature for Evaluation of MEK/ERK Pathway Baseline Activity and Long-Term Modulations in Ovarian Cancer
title_full_unstemmed Optimized Transcriptional Signature for Evaluation of MEK/ERK Pathway Baseline Activity and Long-Term Modulations in Ovarian Cancer
title_short Optimized Transcriptional Signature for Evaluation of MEK/ERK Pathway Baseline Activity and Long-Term Modulations in Ovarian Cancer
title_sort optimized transcriptional signature for evaluation of mek/erk pathway baseline activity and long-term modulations in ovarian cancer
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9654336/
https://www.ncbi.nlm.nih.gov/pubmed/36362153
http://dx.doi.org/10.3390/ijms232113365
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