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...
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| Format: | Article |
| Language: | English |
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Frontiers Media S.A.
2020-07-01
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| Series: | Frontiers in Endocrinology |
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| Online Access: | https://www.frontiersin.org/article/10.3389/fendo.2020.00435/full |
| _version_ | 1818408477585833984 |
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| author | Rive Sarfstein Adva Yeheskel Tali Sinai-Livne Metsada Pasmanik-Chor Haim Werner Haim Werner |
| author_facet | Rive Sarfstein Adva Yeheskel Tali Sinai-Livne Metsada Pasmanik-Chor Haim Werner Haim Werner |
| author_sort | Rive Sarfstein |
| collection | DOAJ |
| 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. |
| first_indexed | 2024-12-14T09:44:21Z |
| format | Article |
| id | doaj.art-2649fdf8246445f0b41a26908d4eff1c |
| institution | Directory Open Access Journal |
| issn | 1664-2392 |
| language | English |
| last_indexed | 2024-12-14T09:44:21Z |
| publishDate | 2020-07-01 |
| publisher | Frontiers Media S.A. |
| record_format | Article |
| series | Frontiers in Endocrinology |
| spelling | doaj.art-2649fdf8246445f0b41a26908d4eff1c2022-12-21T23:07:41ZengFrontiers Media S.A.Frontiers in Endocrinology1664-23922020-07-011110.3389/fendo.2020.00435535704Systems Analysis of Insulin and IGF1 Receptors Networks in Breast Cancer Cells Identifies Commonalities and Divergences in Expression PatternsRive Sarfstein0Adva Yeheskel1Tali Sinai-Livne2Metsada Pasmanik-Chor3Haim Werner4Haim Werner5Department of Human Molecular Genetics and Biochemistry, Sackler School of Medicine, Tel Aviv University, Tel Aviv, IsraelBioinformatics Unit, George Wise Faculty of Life Sciences, Tel Aviv University, Tel Aviv, IsraelDepartment of Human Molecular Genetics and Biochemistry, Sackler School of Medicine, Tel Aviv University, Tel Aviv, IsraelBioinformatics Unit, George Wise Faculty of Life Sciences, Tel Aviv University, Tel Aviv, IsraelDepartment of Human Molecular Genetics and Biochemistry, Sackler School of Medicine, Tel Aviv University, Tel Aviv, IsraelYoran Institute for Human Genome Research, Tel Aviv University, Tel Aviv, IsraelInsulin 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.https://www.frontiersin.org/article/10.3389/fendo.2020.00435/fullinsulin-like growth factor-1 (IGF1)IGF1 receptor (IGF1R)insulin receptor (INSR)systems analysisBioNSinetwork simulation |
| spellingShingle | Rive Sarfstein Adva Yeheskel Tali Sinai-Livne Metsada Pasmanik-Chor Haim Werner Haim Werner Systems Analysis of Insulin and IGF1 Receptors Networks in Breast Cancer Cells Identifies Commonalities and Divergences in Expression Patterns Frontiers in Endocrinology insulin-like growth factor-1 (IGF1) IGF1 receptor (IGF1R) insulin receptor (INSR) systems analysis BioNSi network simulation |
| 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 | insulin-like growth factor-1 (IGF1) IGF1 receptor (IGF1R) insulin receptor (INSR) systems analysis BioNSi network simulation |
| url | https://www.frontiersin.org/article/10.3389/fendo.2020.00435/full |
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