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Identification of a Tumor Cell Associated Type I IFN Resistance Gene Expression Signature of Human Melanoma, the Components of Which Have a Predictive Potential for Immunotherapy

We developed a human melanoma model using the HT168-M1 cell line to induce IFN-α2 resistance in vitro (HT168-M1res), which was proven to be maintained in vivo in SCID mice. Comparing the mRNA profile of in vitro cultured HT168-M1res cells to its sensitive counterpart, we found 79 differentially expr...

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Autores principales: Ladányi, Andrea, Rásó, Erzsébet, Barbai, Tamás, Vízkeleti, Laura, Puskás, László G., Kovács, Szonja A., Győrffy, Balázs, Tímár, József
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8911010/
https://www.ncbi.nlm.nih.gov/pubmed/35269844
http://dx.doi.org/10.3390/ijms23052704
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author Ladányi, Andrea
Rásó, Erzsébet
Barbai, Tamás
Vízkeleti, Laura
Puskás, László G.
Kovács, Szonja A.
Győrffy, Balázs
Tímár, József
author_facet Ladányi, Andrea
Rásó, Erzsébet
Barbai, Tamás
Vízkeleti, Laura
Puskás, László G.
Kovács, Szonja A.
Győrffy, Balázs
Tímár, József
author_sort Ladányi, Andrea
collection PubMed
description We developed a human melanoma model using the HT168-M1 cell line to induce IFN-α2 resistance in vitro (HT168-M1res), which was proven to be maintained in vivo in SCID mice. Comparing the mRNA profile of in vitro cultured HT168-M1res cells to its sensitive counterpart, we found 79 differentially expressed genes (DEGs). We found that only a 13-gene core of the DEGs was stable in vitro and only a 4-gene core was stable in vivo. Using an in silico cohort of IFN-treated melanoma tissues, we validated a differentially expressed 9-gene core of the DEGs. Furthermore, using an in silico cohort of immune checkpoint inhibitor (ICI)-treated melanoma tissues, we tested the predictive power of the DEGs for the response rate. Analysis of the top four upregulated and top four downregulated genes of the DEGs identified WFDC1, EFNA3, DDX10, and PTBP1 as predictive genes, and analysis of the “stable” genes of DEGs for predictive potential of ICI response revealed another 13 genes, out of which CDCA4, SOX4, DEK, and HSPA1B were identified as IFN-regulated genes. Interestingly, the IFN treatment associated genes and the ICI-therapy predictive genes overlapped by three genes: WFDC1, BCAN, and MT2A, suggesting a connection between the two biological processes.
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spelling pubmed-89110102022-03-11 Identification of a Tumor Cell Associated Type I IFN Resistance Gene Expression Signature of Human Melanoma, the Components of Which Have a Predictive Potential for Immunotherapy Ladányi, Andrea Rásó, Erzsébet Barbai, Tamás Vízkeleti, Laura Puskás, László G. Kovács, Szonja A. Győrffy, Balázs Tímár, József Int J Mol Sci Article We developed a human melanoma model using the HT168-M1 cell line to induce IFN-α2 resistance in vitro (HT168-M1res), which was proven to be maintained in vivo in SCID mice. Comparing the mRNA profile of in vitro cultured HT168-M1res cells to its sensitive counterpart, we found 79 differentially expressed genes (DEGs). We found that only a 13-gene core of the DEGs was stable in vitro and only a 4-gene core was stable in vivo. Using an in silico cohort of IFN-treated melanoma tissues, we validated a differentially expressed 9-gene core of the DEGs. Furthermore, using an in silico cohort of immune checkpoint inhibitor (ICI)-treated melanoma tissues, we tested the predictive power of the DEGs for the response rate. Analysis of the top four upregulated and top four downregulated genes of the DEGs identified WFDC1, EFNA3, DDX10, and PTBP1 as predictive genes, and analysis of the “stable” genes of DEGs for predictive potential of ICI response revealed another 13 genes, out of which CDCA4, SOX4, DEK, and HSPA1B were identified as IFN-regulated genes. Interestingly, the IFN treatment associated genes and the ICI-therapy predictive genes overlapped by three genes: WFDC1, BCAN, and MT2A, suggesting a connection between the two biological processes. MDPI 2022-02-28 /pmc/articles/PMC8911010/ /pubmed/35269844 http://dx.doi.org/10.3390/ijms23052704 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
Ladányi, Andrea
Rásó, Erzsébet
Barbai, Tamás
Vízkeleti, Laura
Puskás, László G.
Kovács, Szonja A.
Győrffy, Balázs
Tímár, József
Identification of a Tumor Cell Associated Type I IFN Resistance Gene Expression Signature of Human Melanoma, the Components of Which Have a Predictive Potential for Immunotherapy
title Identification of a Tumor Cell Associated Type I IFN Resistance Gene Expression Signature of Human Melanoma, the Components of Which Have a Predictive Potential for Immunotherapy
title_full Identification of a Tumor Cell Associated Type I IFN Resistance Gene Expression Signature of Human Melanoma, the Components of Which Have a Predictive Potential for Immunotherapy
title_fullStr Identification of a Tumor Cell Associated Type I IFN Resistance Gene Expression Signature of Human Melanoma, the Components of Which Have a Predictive Potential for Immunotherapy
title_full_unstemmed Identification of a Tumor Cell Associated Type I IFN Resistance Gene Expression Signature of Human Melanoma, the Components of Which Have a Predictive Potential for Immunotherapy
title_short Identification of a Tumor Cell Associated Type I IFN Resistance Gene Expression Signature of Human Melanoma, the Components of Which Have a Predictive Potential for Immunotherapy
title_sort identification of a tumor cell associated type i ifn resistance gene expression signature of human melanoma, the components of which have a predictive potential for immunotherapy
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8911010/
https://www.ncbi.nlm.nih.gov/pubmed/35269844
http://dx.doi.org/10.3390/ijms23052704
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