Network models of protein phosphorylation, acetylation, and ubiquitination connect metabolic and cell signaling pathways in lung cancer.
We analyzed large-scale post-translational modification (PTM) data to outline cell signaling pathways affected by tyrosine kinase inhibitors (TKIs) in ten lung cancer cell lines. Tyrosine phosphorylated, lysine ubiquitinated, and lysine acetylated proteins were concomitantly identified using sequent...
| Main Authors: | , , , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Public Library of Science (PLoS)
2023-03-01
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| Series: | PLoS Computational Biology |
| Online Access: | https://doi.org/10.1371/journal.pcbi.1010690 |
| _version_ | 1797831694152105984 |
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| author | Karen E Ross Guolin Zhang Cuneyt Akcora Yu Lin Bin Fang John Koomen Eric B Haura Mark Grimes |
| author_facet | Karen E Ross Guolin Zhang Cuneyt Akcora Yu Lin Bin Fang John Koomen Eric B Haura Mark Grimes |
| author_sort | Karen E Ross |
| collection | DOAJ |
| description | We analyzed large-scale post-translational modification (PTM) data to outline cell signaling pathways affected by tyrosine kinase inhibitors (TKIs) in ten lung cancer cell lines. Tyrosine phosphorylated, lysine ubiquitinated, and lysine acetylated proteins were concomitantly identified using sequential enrichment of post translational modification (SEPTM) proteomics. Machine learning was used to identify PTM clusters that represent functional modules that respond to TKIs. To model lung cancer signaling at the protein level, PTM clusters were used to create a co-cluster correlation network (CCCN) and select protein-protein interactions (PPIs) from a large network of curated PPIs to create a cluster-filtered network (CFN). Next, we constructed a Pathway Crosstalk Network (PCN) by connecting pathways from NCATS BioPlanet whose member proteins have PTMs that co-cluster. Interrogating the CCCN, CFN, and PCN individually and in combination yields insights into the response of lung cancer cells to TKIs. We highlight examples where cell signaling pathways involving EGFR and ALK exhibit crosstalk with BioPlanet pathways: Transmembrane transport of small molecules; and Glycolysis and gluconeogenesis. These data identify known and previously unappreciated connections between receptor tyrosine kinase (RTK) signal transduction and oncogenic metabolic reprogramming in lung cancer. Comparison to a CFN generated from a previous multi-PTM analysis of lung cancer cell lines reveals a common core of PPIs involving heat shock/chaperone proteins, metabolic enzymes, cytoskeletal components, and RNA-binding proteins. Elucidation of points of crosstalk among signaling pathways employing different PTMs reveals new potential drug targets and candidates for synergistic attack through combination drug therapy. |
| first_indexed | 2024-04-09T13:55:54Z |
| format | Article |
| id | doaj.art-92f7c2e322a64533a13b1a50cb4a282b |
| institution | Directory Open Access Journal |
| issn | 1553-734X 1553-7358 |
| language | English |
| last_indexed | 2024-04-09T13:55:54Z |
| publishDate | 2023-03-01 |
| publisher | Public Library of Science (PLoS) |
| record_format | Article |
| series | PLoS Computational Biology |
| spelling | doaj.art-92f7c2e322a64533a13b1a50cb4a282b2023-05-08T05:31:19ZengPublic Library of Science (PLoS)PLoS Computational Biology1553-734X1553-73582023-03-01193e101069010.1371/journal.pcbi.1010690Network models of protein phosphorylation, acetylation, and ubiquitination connect metabolic and cell signaling pathways in lung cancer.Karen E RossGuolin ZhangCuneyt AkcoraYu LinBin FangJohn KoomenEric B HauraMark GrimesWe analyzed large-scale post-translational modification (PTM) data to outline cell signaling pathways affected by tyrosine kinase inhibitors (TKIs) in ten lung cancer cell lines. Tyrosine phosphorylated, lysine ubiquitinated, and lysine acetylated proteins were concomitantly identified using sequential enrichment of post translational modification (SEPTM) proteomics. Machine learning was used to identify PTM clusters that represent functional modules that respond to TKIs. To model lung cancer signaling at the protein level, PTM clusters were used to create a co-cluster correlation network (CCCN) and select protein-protein interactions (PPIs) from a large network of curated PPIs to create a cluster-filtered network (CFN). Next, we constructed a Pathway Crosstalk Network (PCN) by connecting pathways from NCATS BioPlanet whose member proteins have PTMs that co-cluster. Interrogating the CCCN, CFN, and PCN individually and in combination yields insights into the response of lung cancer cells to TKIs. We highlight examples where cell signaling pathways involving EGFR and ALK exhibit crosstalk with BioPlanet pathways: Transmembrane transport of small molecules; and Glycolysis and gluconeogenesis. These data identify known and previously unappreciated connections between receptor tyrosine kinase (RTK) signal transduction and oncogenic metabolic reprogramming in lung cancer. Comparison to a CFN generated from a previous multi-PTM analysis of lung cancer cell lines reveals a common core of PPIs involving heat shock/chaperone proteins, metabolic enzymes, cytoskeletal components, and RNA-binding proteins. Elucidation of points of crosstalk among signaling pathways employing different PTMs reveals new potential drug targets and candidates for synergistic attack through combination drug therapy.https://doi.org/10.1371/journal.pcbi.1010690 |
| spellingShingle | Karen E Ross Guolin Zhang Cuneyt Akcora Yu Lin Bin Fang John Koomen Eric B Haura Mark Grimes Network models of protein phosphorylation, acetylation, and ubiquitination connect metabolic and cell signaling pathways in lung cancer. PLoS Computational Biology |
| title | Network models of protein phosphorylation, acetylation, and ubiquitination connect metabolic and cell signaling pathways in lung cancer. |
| title_full | Network models of protein phosphorylation, acetylation, and ubiquitination connect metabolic and cell signaling pathways in lung cancer. |
| title_fullStr | Network models of protein phosphorylation, acetylation, and ubiquitination connect metabolic and cell signaling pathways in lung cancer. |
| title_full_unstemmed | Network models of protein phosphorylation, acetylation, and ubiquitination connect metabolic and cell signaling pathways in lung cancer. |
| title_short | Network models of protein phosphorylation, acetylation, and ubiquitination connect metabolic and cell signaling pathways in lung cancer. |
| title_sort | network models of protein phosphorylation acetylation and ubiquitination connect metabolic and cell signaling pathways in lung cancer |
| url | https://doi.org/10.1371/journal.pcbi.1010690 |
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