Cargando…
Systems Analysis of Insulin and IGF1 Receptors Networks in Breast Cancer Cells Identifies Commonalities and Divergences in Expression Patterns
Insulin and insulin-like growth factor-1 (IGF1), acting respectively via the insulin (INSR) and IGF1 (IGF1R) receptors, play key developmental and metabolic roles throughout life. In addition, both signaling pathways fulfill important roles in cancer initiation and progression. The present study was...
Autores principales: | , , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2020
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7359857/ https://www.ncbi.nlm.nih.gov/pubmed/32733384 http://dx.doi.org/10.3389/fendo.2020.00435 |
_version_ | 1783559127532830720 |
---|---|
author | Sarfstein, Rive Yeheskel, Adva Sinai-Livne, Tali Pasmanik-Chor, Metsada Werner, Haim |
author_facet | Sarfstein, Rive Yeheskel, Adva Sinai-Livne, Tali Pasmanik-Chor, Metsada Werner, Haim |
author_sort | Sarfstein, Rive |
collection | PubMed |
description | Insulin and insulin-like growth factor-1 (IGF1), acting respectively via the insulin (INSR) and IGF1 (IGF1R) receptors, play key developmental and metabolic roles throughout life. In addition, both signaling pathways fulfill important roles in cancer initiation and progression. The present study was aimed at identifying mechanistic differences between INSR and IGF1R using a recently developed bioinformatics tool, the Biological Network Simulator (BioNSi). This application allows to import and merge multiple pathways and interaction information from the KEGG database into a single network representation. The BioNsi network simulation tool allowed us to exploit the availability of gene expression data derived from breast cancer cell lines with specific disruptions of the INSR or IGF1R genes in order to investigate potential differences in protein expression that might be linked to biological attributes of the specific receptor networks. Modeling-generated information was corroborated by experimental and biological assays. BioNSi analyses revealed that the expression of 75 and 71 genes changed during simulation of IGF1R-KD and INSR-KD, compared to control cells, respectively. Out of 16 proteins that BioNSi analysis was based on, validated by Western blotting, nine were shown to be involved in DNA repair, eight in cell cycle checkpoints, six in proliferation, eight in apoptosis, seven in oxidative stress, six in cell migration, two in energy homeostasis, and three in senescence. Taken together, analyses identified a number of commonalities and, most importantly, dissimilarities between the IGF1R and INSR pathways that might help explain the basis for the biological differences between these networks. |
format | Online Article Text |
id | pubmed-7359857 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-73598572020-07-29 Systems Analysis of Insulin and IGF1 Receptors Networks in Breast Cancer Cells Identifies Commonalities and Divergences in Expression Patterns Sarfstein, Rive Yeheskel, Adva Sinai-Livne, Tali Pasmanik-Chor, Metsada Werner, Haim Front Endocrinol (Lausanne) Endocrinology Insulin and insulin-like growth factor-1 (IGF1), acting respectively via the insulin (INSR) and IGF1 (IGF1R) receptors, play key developmental and metabolic roles throughout life. In addition, both signaling pathways fulfill important roles in cancer initiation and progression. The present study was aimed at identifying mechanistic differences between INSR and IGF1R using a recently developed bioinformatics tool, the Biological Network Simulator (BioNSi). This application allows to import and merge multiple pathways and interaction information from the KEGG database into a single network representation. The BioNsi network simulation tool allowed us to exploit the availability of gene expression data derived from breast cancer cell lines with specific disruptions of the INSR or IGF1R genes in order to investigate potential differences in protein expression that might be linked to biological attributes of the specific receptor networks. Modeling-generated information was corroborated by experimental and biological assays. BioNSi analyses revealed that the expression of 75 and 71 genes changed during simulation of IGF1R-KD and INSR-KD, compared to control cells, respectively. Out of 16 proteins that BioNSi analysis was based on, validated by Western blotting, nine were shown to be involved in DNA repair, eight in cell cycle checkpoints, six in proliferation, eight in apoptosis, seven in oxidative stress, six in cell migration, two in energy homeostasis, and three in senescence. Taken together, analyses identified a number of commonalities and, most importantly, dissimilarities between the IGF1R and INSR pathways that might help explain the basis for the biological differences between these networks. Frontiers Media S.A. 2020-07-07 /pmc/articles/PMC7359857/ /pubmed/32733384 http://dx.doi.org/10.3389/fendo.2020.00435 Text en Copyright © 2020 Sarfstein, Yeheskel, Sinai-Livne, Pasmanik-Chor and Werner. http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. |
spellingShingle | Endocrinology Sarfstein, Rive Yeheskel, Adva Sinai-Livne, Tali Pasmanik-Chor, Metsada Werner, Haim Systems Analysis of Insulin and IGF1 Receptors Networks in Breast Cancer Cells Identifies Commonalities and Divergences in Expression Patterns |
title | Systems Analysis of Insulin and IGF1 Receptors Networks in Breast Cancer Cells Identifies Commonalities and Divergences in Expression Patterns |
title_full | Systems Analysis of Insulin and IGF1 Receptors Networks in Breast Cancer Cells Identifies Commonalities and Divergences in Expression Patterns |
title_fullStr | Systems Analysis of Insulin and IGF1 Receptors Networks in Breast Cancer Cells Identifies Commonalities and Divergences in Expression Patterns |
title_full_unstemmed | Systems Analysis of Insulin and IGF1 Receptors Networks in Breast Cancer Cells Identifies Commonalities and Divergences in Expression Patterns |
title_short | Systems Analysis of Insulin and IGF1 Receptors Networks in Breast Cancer Cells Identifies Commonalities and Divergences in Expression Patterns |
title_sort | systems analysis of insulin and igf1 receptors networks in breast cancer cells identifies commonalities and divergences in expression patterns |
topic | Endocrinology |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7359857/ https://www.ncbi.nlm.nih.gov/pubmed/32733384 http://dx.doi.org/10.3389/fendo.2020.00435 |
work_keys_str_mv | AT sarfsteinrive systemsanalysisofinsulinandigf1receptorsnetworksinbreastcancercellsidentifiescommonalitiesanddivergencesinexpressionpatterns AT yeheskeladva systemsanalysisofinsulinandigf1receptorsnetworksinbreastcancercellsidentifiescommonalitiesanddivergencesinexpressionpatterns AT sinailivnetali systemsanalysisofinsulinandigf1receptorsnetworksinbreastcancercellsidentifiescommonalitiesanddivergencesinexpressionpatterns AT pasmanikchormetsada systemsanalysisofinsulinandigf1receptorsnetworksinbreastcancercellsidentifiescommonalitiesanddivergencesinexpressionpatterns AT wernerhaim systemsanalysisofinsulinandigf1receptorsnetworksinbreastcancercellsidentifiescommonalitiesanddivergencesinexpressionpatterns |